Podcasts about Governance

Members of the International Seabed Authority (ISA) have been meeting in Jamaica to discuss regulations on seabed mining in the High Seas, as Canadian-based firm The Metals Company and its subsidiaries attempt to circumvent international laws and conventions whilst pushing for further exploration approvals.But to whom do the ocean's resources belong? And is it possible to regulate such an industry in international waters? In this rebroadcast, Ellycia Harrould-Kolieb from the University of Melbourne demystifies the governance of the High Seas. Image: Greenpeace Ellycia's research: https://www.sciencedirect.com/science/article/pii/S0308597X23005006Deep Ocean Stewardship Initiative: https://www.dosi-project.org/

This session I facilitated a panel considering volunteer organisations which was put on by Community Governance Aotearoa.  I am grateful to Rose and Alice and the team there for letting me put up the audio of the session on Seeds Podcast as well.    Volunteer boards (sports clubs, waka ama, arts groups and more) are the backbone of Aotearoa's not-for-profit sector. When there's no paid staff, committees and boards often juggle governance and operations, everything from managing subscriptions to compliance and community engagement. This talk is for anyone asking: How do we do it all and still lead well? Practical, actionable, and designed for community governance leaders. Our panelists for this talk were: Steven Moe – Partner at Parry Field Lawyers, specialising in social enterprises, not for profits Abby Golden – Co-founder at Te Ara Tīrama Charitable Trust Chris Joseph – Executive Director at Volunteer Kāpiti There is a youtube video of this session here as well: https://www.youtube.com/watch?v=vruUDbBLu40  For more content visit www.theseeds.nz

Sean Martin catches John Sotiropoulos and Rock Lambros at the end of the OWASP GenAI Security Summit, held alongside Infosecurity Europe 2026 at ExCeL London. Both are deep in the standards work: John Sotiropoulos co-leads the OWASP Agentic Security Initiative and sits on the board of the OWASP GenAI Security Project, and Rock Lambros serves as Director of AI Standards and Governance at Zenity and co-leads the OWASP Top 10 for LLM 2026 update. The headline from the day is the launch of the Agentic Security Council, bringing Oxford University, Queen's University Belfast, CSIT, and other research institutions into the same room as practitioners and industry. John Sotiropoulos frames the reasoning bluntly: content on its own does not create change. Papers and Top 10 lists matter, but they only matter if the people building and defending systems can act on them. The number that reframes everything is twenty-two seconds. That is the average time from an initial access event to the next attacker action, down from eight hours. John Sotiropoulos puts the question directly to anyone still running a human-speed playbook: how do you respond to that? A panel on incident response with participants from AWS and Microsoft, a keynote from Microsoft's National Security Officer, and a walkthrough of the State of Agentic Security and Governance report all point at the same shift toward runtime security. Rock Lambros brings a different kind of grounding. For the first time in the four-year history of the OWASP Top 10 for LLM, the update draws on a corpus of reported incidents rather than opinion and community vote alone. It is one data point among several, but it is data, and that changes what the list can claim. A panel with the heads of AI security at Deloitte supplies the operational counterweight. As one of them puts it, security has to stop being the Ministry of No, because people will route around it and ship anyway. The report's adoption tiers and maturity levels exist for exactly that reason: security that lives only inside a PDF is not security. The invitation from both John Sotiropoulos and Rock Lambros is the same. Join the work. Research, red teamers, defenders, builders, and SecOps all looking at one view of what is actually happening is the only version of this that scales to machine speed. ⬥HOST⬥ Sean Martin, CISSP | Co-Founder, ITSPmagazine & Studio C60 | Host, Redefining CyberSecurity Podcast & Music Evolves Podcast | https://www.seanmartin.com/ ⬥GUESTS⬥ John Sotiropoulos, Deep Cyber | Co-Lead, OWASP Agentic Security Initiative; Board Director, OWASP GenAI Security Project | On LinkedIn: https://www.linkedin.com/in/jsotiropoulos/ Rock Lambros, Director of AI Standards and Governance, Zenity; Founder, RockCyber | Co-Lead, OWASP Top 10 for LLM 2026 | On LinkedIn: https://www.linkedin.com/in/rocklambros/ ⬥RESOURCES⬥ Infosecurity Europe 2026 is taking place June 2-4, 2026 | ExCeL London. Follow our coverage: https://www.itspmagazine.com/infosecurity-europe-2026-infosec-london-cybersecurity-event-coverage OWASP GenAI Security Project | https://genai.owasp.org Contribute to the OWASP GenAI Security Project | https://genai.owasp.org/contribute The Future of Cybersecurity Newsletter | https://www.linkedin.com/newsletters/7108625890296614912/ Redefining CyberSecurity Podcast | https://www.seanmartin.com/redefining-cybersecurity-podcast On Location | https://www.itspmagazine.com/on-location

What prevents a successful AI experiment from becoming a dependable production system that delivers measurable business value? In this episode of Tech Talks Daily, I speak with Ed Macosky, Chief Product and Technology Officer at Boomi, about AI pilot purgatory, integration, governance, model selection, token costs, and the technical skills businesses may need as adoption grows. Ed leads Boomi's product and engineering teams while also using AI tools inside his own organization. That gives him a view from both sides: creating technology for enterprise customers and applying it within active product development workflows. He believes many AI pilots begin with the wrong question. Teams become interested in the latest model or feature before defining the business problem they want to solve. The experiment may work during a demonstration, then fail when it encounters real data, access controls, security policies, and production systems. Placing company information inside a data lake and adding a language model does not automatically create a business application. The system must access current data reliably, respect employee permissions, connect with existing applications, and operate within governance rules that security teams can approve. Ed recommends beginning with a defined business opportunity and establishing the access required to support it. Existing APIs can already provide authentication, permissions, and governance. MCP can offer another route into enterprise systems, but those connections still require security, monitoring, and management. Team alignment also matters. An AI center may be racing to test models while an integration center concentrates on a different set of priorities. When those groups fail to coordinate, the pilot lacks the connectivity and automation required to become part of a production workflow. The discussion then turns toward fragmentation. Every technology wave produces new vendors, frameworks, and specialist tools. Early experimentation benefits from variety, but mature companies can eventually find themselves maintaining a complicated collection of products held together with custom code and, occasionally, the digital equivalent of duct tape. Ed does not recommend placing every function with one provider. He does argue for enough consolidation and abstraction to prevent experimentation from creating years of technology debt. Governance and observability should also work horizontally across different environments, including platforms such as SAP, Salesforce, and several AI model providers. That becomes increasingly important as businesses introduce autonomous agents. Leaders need to know which agents exist, what systems they can access, what actions they can take, and how each decision is recorded. AI gateways and agent control towers can provide a wider view across otherwise separate technology environments. Ed also introduces the idea of the frontier engineer. A prompt engineer concentrates on communicating effectively with a model. A frontier engineer understands how the model works, including its logic, mathematics, algorithms, and suitability for different workloads. He does not believe every company needs a large team of these specialists. However, he argues that enterprises need at least one person capable of assessing vendor claims and deciding whether a frontier model, specialist model, or open weight model fits a particular workload. Cost creates another reason to examine model selection. Sending every employee request or agent task to the most capable frontier model can become expensive. Some repeatable workloads may run on open weight models inside the company's cloud or hardware environment, giving finance teams greater cost certainty. Boomi is developing Boomi Prompt to route requests according to their complexity and requirements. A simple factual request might go directly to an API. A forecasting task may use a smaller model. A difficult analytical request could be sent to a frontier model. Ed uses the weather as a helpful example. Retrieving next Tuesday's forecast does not require a language model when a public weather API can return the answer directly. Asking a model to perform every form of automation wastes tokens, computing power, energy, and money. The episode closes with practical advice for CIOs. Avoid starting with a broad objective such as agentifying the entire business. Choose a department, identify a small number of tasks, define the expected return, and work backward. Once the team proves value and understands the operating requirements, it can repeat the process elsewhere. Could intelligent routing, stronger integration, and clearer business outcomes finally move enterprise AI beyond pilot purgatory? Listen to the episode and share your thoughts with me.

A $6.9 million estimate. A $1.25 billion catastrophe. How fake deadlines, a rigged bid, and a steering committee allergic to bad news turned a routine payroll migration into one of the biggest project disasters in Australian history. What happens when project leadership treats risk management as optional, decision making gets diffused across committees, and a hard deadline turns out to be completely negotiable? You get one of the most instructive project failure case studies in project management history — and in this episode, Kim and Kate pour it out one painful lesson at a time. The subject is Queensland Health, the public healthcare provider for the Australian state of Queensland, employing roughly 85,000 people across about 300 sites. In 2005, their legacy payroll vendor gave them three years' notice: support ends June 30, 2008. Sounds like plenty of runway — until the organization waited two of those three years to act. By the time a consultant named Terry Burns (remember that name) ran the procurement and IBM signed a contract in December 2007, the original $6.9 million estimate had ballooned to a $98 million contract with just six months to deliver a system covering more than 24,000 unique payroll combinations. Why does this matter for project managers and leaders? Because almost nothing that went wrong here is exotic. Late project intake. Governance where a transition team, a steering committee, and an IT department all had partial authority but no single decision-making structure. Two weeks — total — for requirements gathering on a nine-figure program. A "lift and shift" strategy that preserved every broken process and demanded 2,500 custom software configurations to replicate them. As Kim and Kate walk through it, the episode becomes a masterclass in how ordinary project management failures compound into organizational catastrophe. The discussion highlights are equal parts horrifying and hilarious. There's the program's actual internal slogan, taken straight from the project materials: "Plan A or Die" — no continuity plan, no risk mitigation, no fallback. There's the June 2008 deadline that came and went with a simple change request and some extended support from the legacy vendor, prompting Kate's sharp observation that the date was fake and not fake at once: end-of-life risk is real even when the cliff turns out to be movable. There's the UAT phase in June 2009 that surfaced 2,422 severe defects — after which the steering committee simply reclassified high-severity defects as lower severity so the dashboards would show enough green to proceed. Watermelon project, indeed. And when frontline payroll staff kept failing the system in testing, leadership's answer was to remove the requirement for business sign-off entirely. The go-live in March 2010 delivered the reckoning: 35,000 payroll anomalies, roughly $400 million in accidental overpayments, zero-dollar paychecks for healthcare workers, and government debt collectors hounding nurses for money they never asked to receive. Queensland ultimately hired a thousand staff to manually prop up the new system — a 40 percent increase in labor over the old one — with a projected five-year cost to taxpayers of $1.25 billion. The commission of inquiry that followed, led by the Right Honourable Richard Noel Chesterman, revealed the final twist: Terry Burns, a former IBMer, had leaked a competitor's bid specs to IBM and browbeaten the selection panel into rescoring until IBM won. And when the state sued? A release buried in the fine print of a change order had signed away its right to litigate. Grab a drink and join us. Quotes from the Episode "Everyone's in charge, so no one's in charge." — Kate "If you've got a deadline, question the deadline." — Kim "I've heard the term watermelon project where they're green on the outside and red on the inside." — Kim "And you are paying that company that you're hiring to learn." — Kate "But ultimately, if your project options are plan A or die. Maybe sometimes the best option is die." — Kim Practical Takeaways Governance and decision rights — When multiple bodies share authority without a single decision-making structure, accountability evaporates ("everyone's in charge, so no one's in charge"). Deadline validation — Interrogate whether a project deadline is a true constraint or a negotiable date, and what options (like extended vendor support) exist beyond it. The watermelon project pattern — Recognizing status distortion, including reclassifying defect severity and removing sign-off requirements to force green dashboards. Parallel run as cutover risk mitigation — Why replacing a legacy business-critical system requires side-by-side operation and validation before go-live. Procurement integrity and vendor selection — The risks of conflicts of interest in vendor selection, of choosing a vendor with no prior experience delivering the solution, and of unreviewed contract fine print. Closing Reflection Nobody ever really "accepts" a risk on paper. When risks are realized, someone always pays—taxpayers, frontline workers, or the organization itself. Sometimes the bravest act of project leadership is admitting that Plan A deserves to die.

As AI agents move from pilots into live financial workflows, most institutions still can't answer a basic question: who authorized this action, and what evidence backs it up?   In this episode, Shahir Daya, Chief Product & Technology Officer at Zafin, examines why uniform governance policies fail at scale and what a tiered, control-tower approach to agent oversight looks like in practice. The conversation covers execution-layer governance, cost visibility across models, and the shift required to move agentic work from promising pilot to defensible production.   This episode is sponsored by Zafin.   Learn the exact strategies we use to help leading AI brands and startups connect with their ideal enterprise AI buyers: visit emerj.com/AD1  

This evening, we unpack the latest market movements with Otto1890, examine the governance reset at the PIC with Public Interest SA, discuss the implications of fiscal debt traps for long-term investors with Allan Gray, explore the growing AI-driven fraud crisis across Africa with Sumsub, reflect on Valterra Platinum,s record financial performance, and, in our Executive Lounge, we speak to Dr Tumelo Chaka, chief marketing officer at United Stations. SAfm Market Update - Podcasts and live stream

Financial governance is not reserved for large organisations. It starts with knowing your numbers, planning for uncertainty and building habits that support better decisions. In this episode, Cathy Love and Layland Webb unpack the practical difference between a budget and a forecast, and explain why uncertainty is a reason to scenario plan rather than delay it. They also challenge the industry's narrow focus on billable KPIs and explore how lead indicators can create better performance, accountability and support for employees. The episode closes with a listener question about turning an informal business relationship into a clear commercial partnership. Topics covered on financial governance, forecasting and meaningful KPIs: Financial governance through uncertainty: Why NDIS reform, Thriving Kids, cancellations and workforce changes should be built into different financial scenarios. Budgeting and forecasting: How a budget sets the destination while regular forecasting helps business owners respond to what is actually happening. KPIs beyond billables: The difference between lead and lag KPIs, and why behaviour, client satisfaction and employee satisfaction also matter. P.S. If this episode is hitting on pain points you're facing, let's chat. We can support you. Book a 20-minute complimentary call with us, and let's talk about how we can help you achieve your vision for your Allied Health business. Midroll Message: Join the Thriving Providers: The S.E.C.U.R.E. Game Plan Masterclass Connect with Nacre Consulting: Let's connect on Instagram Follow us on Facebook Let's connect on LinkedIn Join our Facebook Group online community More about The Allied Health Business Brilliance Podcast: The Allied Health Business Brilliance podcast (previously known as Private Practice Made Perfect) powered by Nacre Consulting features authentic conversations that offer real-life stories and expert perspectives for Australian Allied Health Business Owners. Cathy Love, our engaging host, gathers wisdom from Allied Health professionals and industry supporters alike. We dive into the real experiences of running and growing Allied Health businesses in Australia, revealing both the rewards and the inevitable challenges along the way. It's raw, sometimes vulnerable, but always valuable. Join us and stay tuned to keep up with every inspiring story and lesson shared.

"Frankenstein Mindset" Host: Darren Weeks Website for the show: https://governamerica.com COMPLETE SHOW NOTES AND CREDITS AT: https://governamerica.com/radio/radio-archives/22672-govern-america-july-25-2026-frankenstein-mindsetListen LIVE every Saturday at 11AM Eastern or 8AM Pacific at http://governamerica.net or on your favorite app. DISCLOSURE: AI used for top-of-the-hour newscasts and break bumper music.U.S. House passes 2027 National Defense Authorization Act with provision to merge U.S.-Israeli military supply chains, technology, data, equipment, and training. Ford partnering to build cars with the communist Chinese, even as China dumps the U.S. dollar. Depraved Zionists push for full scale war with Iran, claiming they are "willing to undergo those casualties", though they won't be doing the fighting. Government of Iran posts music video about Charlie Kirk assassination. Central banks go strangely silent on digital currency implementation. Board of Peace moves forward as Mexico phases out cash, and more.

Why do so many enterprise AI initiatives begin with impressive demonstrations but struggle to produce measurable business value? In this episode of Tech Talks Daily, I speak with Dom Selvon, CTO and value partner at Valiance, about enterprise AI ROI, outcome-based consulting, build versus buy decisions, proprietary data, ontologies, and governance. Valiance is an AI-native consultancy that charges against client outcomes rather than hours worked. Dom explains why his "value partner" title is deliberate. The company begins by identifying the financial or operational result a client wants and connects its own compensation with achieving that result. Dom argues that many AI initiatives begin without a clear definition of success. The pressure to adopt AI is real, but companies frequently select technology before agreeing on the business problem, desired outcome, or measurement. He identifies three recurring mistakes. The first is framing the project around AI rather than the business need. The second is failing to establish a metric and baseline before work begins. The third is using a consulting model that rewards billable time without connecting payment to the client's result. We also discuss how generative AI is changing traditional build versus buy decisions. Companies historically bought software because custom development was slow, expensive, and difficult to maintain. Coding agents can now reduce the time and cost required to create software for specific internal needs. Dom does not believe SaaS will simply disappear. However, vendors selling convenience, workflow wrappers, or integration glue face new competition from customers who can create similar capabilities themselves. He argues that stronger SaaS positions will depend on assets a model cannot easily regenerate, including proprietary data, networks, regulatory standing, and deep workflow adoption. This leads to a wider discussion about competitive advantage. When companies have access to similar models, generated code begins to converge. Dom believes lasting differentiation comes from company data, institutional knowledge, connected systems, employee experience, and the semantic context surrounding that information. Dom explains why ontologies matter to enterprise AI. Raw data tells an agent what is stored in a particular field. An ontology describes the customers, orders, contracts, payments, relationships, and business rules represented by that data. This context allows people and agents to reason about information in a way that reflects how the company actually works. Governance also needs to be designed from the beginning. Dom argues that security, permissions, accountability, and compliance allow successful pilots to expand without forcing the business to rebuild everything later. How can leaders tell when AI is genuinely being adopted? Dom offers a surprisingly simple signal: people stop talking about AI. The technology becomes part of ordinary Monday morning work, and employees focus on completing the task rather than explaining the tool. Has your company defined the business result, measurement, proprietary context, and governance required to turn AI enthusiasm into operational value? Listen to the episode and share your thoughts with me.

What has made this moment feel different is not the anxiety about incivility, which has always been there, but rather the performance of it. It's relentless.” — Molly Brady on incivility in the age of the smartphone Whatever happened to the American front porch? Builders killed it to save money, says the Harvard law professor Molly Brady — and with this death went one of the key stages on which Americans have practiced the art of being neighbors over the last 250 years. Brady is a contributor to America Unfinished: 250 Years of Law and Governance, a new volume of 62 essays from the Harvard Law School faculty edited by Alexandra Natapoff. Brady's subject is the land, real-estate and local government law determining neighborliness. Thus her interest in front porches. Brady grew up in Utica, New York — on the old Erie Canal — a Rust Belt town whose fracking fights, abandoned housing, and urban renewal steered her toward property law. Utica is also, despite its red politics, a place well versed in the art of neighborliness — with the town warmly welcoming recent Bosnian and Iraqi refugees. Incivility isn't new, Brady says. What's changed, she argues, is its performative virality. With a phone in every pocket, we can now watch our fellow “citizens” behaving badly. Meanwhile the physical infrastructure of community — the front porches and corner stores — has been zoned, sprawled, and value-engineered away. Analogue porches have been replaced by digital chatrooms. Brady's remedy is unfashionably local. On Zoom or in person, she advises, show up at your local planning meetings. Brady even requires her Harvard students to attend at least one local meeting so as to demystify the real work of governance. The republic, as Ben Franklin so famously warned, is ours if we can keep it. Keeping it, Molly Brady suggests, may require in-person attendance on a Wednesday night at your local planning commission. And it might also require hanging out on your porch. If the builders ever give them back to us. Five Takeaways •       The Performance of Incivility. Americans have always fretted about incivility — the republic itself was born out of Europe's religious civil wars. What has changed, Brady argues, is technology. When difference was mediated through traditional publishers, you had to grapple with the people in your physical world: the workplace, the water cooler, the town meeting. Now everyone carries a phone on which fellow citizens can be found behaving horribly at any given moment. It is not the presence of incivility that makes this moment feel different — it is the relentless performance of it.•       The Death of the Porch. Brady writes in the tradition of Robert Putnam's Bowling Alone, updated for the post-smartphone age: suburbanization, the loss of third places, remote work — and a thousand micro-choices in property law that removed the physical alternatives to online life. Builders dropped the front porch to save money; developers in the South and West build almost nothing outside homeowners associations, so there is no meaningful market choice. People are human — they yearn for connection — but in the absence of physical competition, technological community wins by default.•       Tocqueville's Scalability Problem. What Tocqueville admired in New England — every citizen (nominally) arguing policy with neighbors at the town meeting — may never have been scalable to a continental republic, a question America has been grappling with since the Louisiana Purchase. But the local still scrambles our politics in useful ways: party preference, as the scholar David Schleicher observes, tells you nothing about road paving. The darker local truth is Bill Fischel's homevoter hypothesis — homeowners dominate participation and vote to maximize home values, which has helped produce the national affordability crisis.•       Glimmers: Zoom, Newton, and Showing Up. The shift to Zoom planning meetings completely changed the demographics of who participates in land use decisions — young parents cannot spend Wednesday from seven to midnight debating a corner store. Newton has produced genuinely pro-housing policies; Cambridge ran a charter commission that drew in residents of every kind; groups like Abundant Homes Massachusetts organize contingents to make sure meetings are not left to the usual voices. Brady requires her students to attend at least one local meeting. The lesson: do not think this is for someone else.•       2076: Best Case, Worst Case. Asked to imagine America's 300th birthday, Brady hopes for less polarization and demonization, and for a real confrontation of the housing and environmental crises — collective work that might itself rebuild the habit of cooperation. The worst case runs through Margaret Atwood and civil war scenarios to environmental degradation and lives lost to our incapacity to work together. The warning signs are already banal: middle-aged men now pay consultants to teach them how to make friends. The skills have atrophied — and local participation, Brady suggests, is the gym where a republic gets them back. About the Guest Molly Brady is a professor of law at Harvard Law School, where she teaches property, land use, and local government law. Raised in Utica, New York, she is a graduate of Harvard College and Yale Law School, and her scholarship on the history of American property law has won wide recognition, as has her teaching. She lives in Belmont, Massachusetts, and is a contributor to America Unfinished: 250 Years of Law and Governance, edited by Alexandra Natapoff and Guy-Uriel E. Charles (MIT Press, July 2026). References: •       America Unfinished: 250 Years of Law and Governance, edited by Alexandra Natapoff and Guy-Uriel E. Charles (MIT Press, July 2026). Bryan Stevenson: “A valuable contribution to understanding America at a critical moment.”•       Bowling Alone by Robert Putnam — the 2000 classic on America's vanishing social capital, written, Brady notes, before the smartphone made things worse. Putnam is an old friend of this show.•       Democracy in America by Alexis de Tocqueville — the towering account of New England civic virtue that frames the episode's scalability question.•       Shade by Sam Bloch — the new book on the politics of shade that taught Brady about the money-saving death of the American front porch.•       Bill Fischel's “homevoter hypothesis” — the Dartmouth economist's account of why homeowner-dominated local politics maximizes home values and starves housing supply.•       Alexandra Natapoff — the volume's co-editor, whose own Keen On America conver...

What happens when AI moves beyond writing emails and summarizing meetings and starts influencing who gets hired, promoted, and paid? In this episode of Tech Talks Daily, I speak with David Lloyd, Chief AI Officer at Dayforce, about why HR is becoming one of the highest-stakes environments for artificial intelligence and how companies can introduce AI while protecting employee data, maintaining human accountability, and preparing for growing regulatory scrutiny. HR systems contain some of the most sensitive information companies hold, from salaries and performance records to benefits and personal data. At the same time, AI is increasingly being introduced across recruitment, workforce management, compensation, performance, and employee experience. David explains why this combination creates enormous opportunities but also places greater responsibility on employers to understand how AI systems operate and how decisions are made. A major theme throughout our conversation is the role of AI governance. David challenges the assumption that governance slows innovation, arguing that the right processes can help companies evaluate AI ideas quickly while reducing the risk of introducing systems that lack appropriate data, transparency, or regulatory safeguards. Dayforce recently achieved ISO/IEC 42001 certification for AI management systems and NIST AI Risk Management Framework attestation. David explains what independent validation means in practice and why companies evaluating AI vendors should ask for evidence of how systems are governed, tested, monitored, and audited. We also discuss the principle of "AI by choice." David argues that CIOs and HR leaders should never discover that a new AI capability has suddenly been activated across hundreds of employees without their knowledge. Companies need visibility into where AI is being used, what data employees can provide to models, and whether customer information is being used to train external AI systems. The conversation examines AI literacy and why HR leaders need to become comfortable with the technology themselves before guiding employees through changes to jobs and working practices. Employees are already experimenting with AI, sometimes through personal tools outside approved company systems. Rather than ignoring this behavior, David explains why companies should provide safe environments where people can learn while establishing clear rules around sensitive data. Human accountability remains central as AI takes on more responsibility. David discusses why people using AI should remain accountable for its outputs and why human oversight matters when technology influences decisions involving recruitment, compensation, performance, and careers. For CEOs, CHROs, CIOs, HR technology leaders, and anyone responsible for enterprise AI, this conversation provides practical guidance on responsible AI adoption, employee data, AI bias, model monitoring, regulatory compliance, vendor selection, and building AI governance that can stand up to scrutiny. The lesson is that governance does not have to be a brake on AI adoption. Done well, it can give companies the structure and confidence to move faster, make better decisions about where AI belongs, and continue using the technology when regulators, employees, customers, and boards start asking harder questions. https://www.dayforce.com/ https://www.linkedin.com/company/dayforce/ https://www.linkedin.com/in/dtlloyd/

This week, Chris Caplice is joined by Andres Mendoza Pena, Partner at Kearney, to discuss the latest CSCMP State of Logistics Report, Forged in Disruption, and what it means for shippers navigating a more connected and unpredictable world.In this conversation, they cover:Why traditional cost-first supply chain playbooks are becoming less effectiveHow companies are building more flexibility across suppliers, countries, and transportation networksWhere AI is producing real results in logistics workflowsWhy autonomous trucking may reshape transportation economics and network designHow reactive decisions can create costly “network drift”Why scenario planning and “non-regret moves” can help companies prepare for multiple possible futuresIf you're responsible for supply chain strategy, transportation, or network planning, this episode offers a practical look at how to operate when disruption is no longer the exception.For previous episodes and to subscribe to our newsletter, visit: dat.com/podcast/freightvine Chapters00:00 Introduction 04:41 Understanding Ongoing Volatility in Supply Chains07:08 The Impact of Globalization and Interconnectedness09:46 Shifts in Supply Chain Strategies11:58 E-commerce Trends and Consumer Behavior14:24 The Role of AI in Supply Chain Management17:05 Governance and Implementation of AI Solutions24:08 Exploring Autonomous Driving and Trucking Technology28:56 Understanding Network Drift in Supply Chain Management33:46 Navigating Tariff Policies and Global Supply Chains38:23 Railway Mergers and Market Dynamics42:24 Forecasting Future Trends in Freight Markets44:32 Truckload Market Overview47:23 Spot vs Contract Rates Analysis

Having an AI policy is a great first step, but successful AI Governance Implementation goes much further. Governance isn't about creating documents that sit on a shelf—it's about building processes that become part of everyday development. As organizations continue integrating AI into products and workflows, the challenge shifts from whether to use AI to how to manage it responsibly. In Part 2 of our conversation with Dr. Latha Karthigaa, Co-Founder of the Global AI Certification Council (GAICC), we explored practical steps organizations of every size can take to introduce AI governance without slowing innovation. About Latha Karthigaa Dr. Latha Karthigaa is the Director & Head of AI Governance of the Global AI Certification Council (GAICC), where she helps organizations implement responsible AI through governance frameworks, certifications, and AI management systems. With a PhD in Software Engineering and experience in education, digital marketing, and AI strategy, she focuses on helping professionals and enterprises adopt AI responsibly. Learn more: GAICC: https://gaicc.org LinkedIn: https://www.linkedin.com/in/lathakarthigaa/ AI Governance Implementation Starts with Ownership One of the biggest risks organizations face isn't malicious AI—it's unmanaged AI. Many businesses experiment with AI tools, build internal assistants, or launch AI-powered features without assigning clear ownership. When something goes wrong, no one knows who is responsible for investigating, fixing, or improving the system. Every AI system should have a designated owner. That doesn't mean one person writes every line of code or monitors every prompt. It means someone is accountable for ensuring the system continues operating within acceptable boundaries as models evolve, data changes, and new risks emerge.

In this sponsored episode, Jonah Kowall from Spacelift joins the show to unpack the findings of the 2026 Infrastructure Automation Report. The discussion covers the “governance paradox”, where organizations have confidence in their AI oversight despite a lack of formal policies. Ned and Jonah provide actionable insights on bridging the gap between automation and the... Read more »

Most organizations deploying AI agents can’t answer a basic question: is it actually working? Not whether the agent runs — whether the process actually got better. In Episode 3 of our process mining and process intelligence series, Damian Pascale and Roz Parpia join host Bobby Brill to go deep on what it actually looks like to run process intelligence with AI in the mix — from the AI Visibility Gap, to a four-step framework for finding the right AI use cases, to what “closed loop intelligence” really means once agents are governing agents. This episode’s answer to the recurring question: don’t automate the chaos. Find it, understand it, improve it — then, and only then, streamline it. CHAPTERS 0:00 Introduction — Damian Pascale & Roz Parpia 0:56 “Don’t automate the chaos” — where the phrase comes from 2:25 Process mining vs. process intelligence — what actually changed 4:21 The linchpin: where AI fits across all three layers 5:36 The AI Visibility Gap — what most organizations are missing 6:56 A real example: when agent metrics look great, but quality doesn’t 8:13 The four-step framework: Find, Understand, Improve, Streamline 11:27 Where AI comes into streamlining — sizing the right use cases 13:19 Does the order of the four steps actually matter? 14:04 Task Mining — the human side process mining can’t see 15:19 A concrete example: the procurement approval bottleneck 16:31 The closed loop — six steps to continuous improvement 17:30 Why you can never skip the ‘detect’ step 18:05 Measuring real impact with the compare feature 19:25 Governance and AI Control Tower, explained simply 20:46 Mining the agents themselves — a third layer of visibility 21:36 Closed loop intelligence — the three layers, confirmed 22:48 Day one: what to do after deploying your first agent 23:38 Closing thoughts from both guests 24:26 Wrap-up IN THIS EPISODE • Why an AI agent doesn’t fix a broken process — it just runs the broken process faster • The real difference between process mining and process intelligence: three layers in one • The AI Visibility Gap: why almost every customer has deployed an agent, but few can prove it’s working • A real customer example — an agent that improved response time but quietly increased the reopen rate • The four-step framework for AI-ready process improvement: Find, Understand, Improve, Streamline • The 2–15 minute rule (and the 3–9 minute sweet spot) for sizing the right AI agent use cases • Why skipping straight to automation is exactly how you end up automating the chaos • Task Mining and the procurement approval example — 45 minutes across four systems, invisible to process mining alone • The six steps of the closed loop, and why the ‘detect’ step is the one everyone skips • Using the compare feature to measure whether an AI agent actually helped — or just moved the problem • AI Control Tower, explained simply — and how it becomes a third layer of process intelligence • Closed loop intelligence: the agent, the governance, and the agent’s own behavior — all observable, all improving GET STARTED If you’re a ServiceNow customer, you already have access to free evaluation projects — no license needed. https://www.servicenow.com/au/products/process-mining/get-started.html https://www.servicenow.com/docs/r/now-intelligence/process-mining/process-mining.html https://www.youtube.com/watch?v=TVrU0TQ7ldM https://www.youtube.com/watch?v=GLKROYqnc10 #ServiceNow #ProcessMining #ProcessIntelligence #AIAgents #AgenticAI #TaskMining #AIGovernance #AIControlTower #WorkflowAutomation #DigitalTransformation #ContinuousImprovement #ClosedLoopIntelligence #ServiceNowPodcast #EnterpriseAI #DontAutomateTheChaosSee omnystudio.com/listener for privacy information.

Artificial intelligence is advancing at an incredible pace, but without an AI Governance Framework, organizations risk creating systems that are difficult to trust, maintain, or scale. Many people assume that governance slows innovation, but in reality, the opposite is often true. The right guardrails allow teams to move faster by reducing uncertainty and preventing costly mistakes before they happen. In Part 1 of our conversation with Dr. Latha Karthigaa, Co-Founder of the Global AI Certification Council (GAICC), we explored why AI governance is becoming a business necessity and why developers should view it as an enabler rather than a barrier. About Latha Karthigaa Dr. Latha Karthigaa is the Director & Head of AI Governance of the Global AI Certification Council (GAICC), where she helps organizations implement responsible AI through governance frameworks, certifications, and AI management systems. With a PhD in Software Engineering and experience in education, digital marketing, and AI strategy, she focuses on helping professionals and enterprises adopt AI responsibly. Learn more: GAICC: https://gaicc.org LinkedIn: https://www.linkedin.com/in/lathakarthigaa/ AI Governance Framework Is Like Guardrails on a Highway One of the best analogies from the discussion compared AI governance to the guardrails along a highway. Drivers can safely travel at higher speeds because guardrails help keep them on course. Remove those barriers, and everyone naturally slows down because the consequences of a mistake become much greater. AI works the same way. Governance isn't about preventing innovation. It's about creating confidence that allows organizations to innovate responsibly. When developers know the boundaries, they spend less time reacting to unexpected issues such as biased outputs, hallucinations, data misuse, or compliance failures.

Domo and AWS reveal how AI agents freed sales reps from 20 hours of weekly busywork, turning scattered data into real-time coaching and forecasting.Topics Include:Domo and AWS teams introduce today's session on AI agents in sales.Topic: using AI agents to transform sales operations, from insight to action.IT teams increasingly asked to turn data into actionable outcomes, not just access.Domo's CRO wanted AI agents to boost sales rep efficiency significantly.Reps act like "archaeologists," digging through scattered systems for basic context.This digging eats roughly 20 hours weekly, half of reps' time.Goal: personal AI agent per rep, understanding their book of business.Live demo begins: agent app surfaces urgent items needing attention.Agent tracks deal milestones, timelines, and forecasts from call and email data."Deal coach" feature grades rep performance and suggests next actions.Agent tone can be tuned from gentle to direct, aiding tough feedback.Architecture overview begins: building an AI-ready data foundation first.Data from CRM, calls, and emails flows into a cloud warehouse.Two agents built: automated deal analysis and personalized deal coach.Agents write insights back to CRM, preserving human edit control.Recipe: build foundation, activate with agents, distribute to people.Governance must be embedded throughout, not bolted on afterward.Second example: Fogo do Chão uses AI to analyze restaurant reviews.AWS architecture explained: Domo runs on Bedrock, defaulting to Anthropic models.Q&A: sales team adoption was immediate and enthusiastic post-rollout.Participants:Jason Longhurst – Head of Product Marketing, DomoAman Tiwari - Sr Solutions Architect, ISV, Amazon Web Services See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

Healthcare AI is moving faster than many health systems can govern it.In this episode of Straight Out of Health IT, David Hilderbrand, Chief Commercial Officer at Ferrum Health, joins Christopher Kunney to discuss the rapid rise of clinical AI, medical imaging AI consolidation, and the growing need for enterprise-level governance. He explains why health systems are no longer just asking which AI tools to buy, but how to monitor, manage, and understand the tools already running across their organizations. As AI enters through devices, platforms, service lines, and vendor relationships, CIOs and clinical leaders are facing a new kind of operational complexity. The conversation explores why effective AI oversight has become essential as adoption accelerates across healthcare.David breaks down the difference between AI committees, analytics, telemetry, and true governance. He explains that governance is not simply about knowing whether an algorithm is turned on, but about understanding how it behaves in clinical care and how it performs across different patient populations. Without that level of visibility, health systems risk overlooking issues such as bias, model drift, inconsistent performance, and patient impact. He argues that meaningful governance is critical to ensuring AI delivers safe, reliable, and measurable clinical value.David also shares how Ferrum Health approaches clinical AI through platforming, observability, and neutral model monitoring. Rather than recommending which AI tools organizations should adopt, Ferrum helps health systems gain visibility into their entire AI portfolio so they can make informed decisions about expanding, replacing, or retiring algorithms. The discussion also covers measuring ROI, recognizing the costs of underperforming AI models, and the importance of early disease detection. Hilderbrand concludes by explaining why AI governance should remain independent from vendor bias to support better long-term clinical and operational outcomes.Tune in to hear why clinical AI governance is becoming essential infrastructure for health systems, and why the future of healthcare AI depends on visibility, accountability, and trust.Key TakeawaysClinical AI is expanding quickly, but many health systems lack the tools to understand what is actually running across their environments. Vendor sprawl is creating new operational, financial, and clinical risks as AI tools enter through devices, platforms, and service lines. True AI governance goes beyond telemetry and analytics; it requires visibility into how algorithms interact with patients and clinical workflows. Health systems need unbiased observability to determine whether clinical AI tools are performing as promised. AI governance can help organizations reduce the cost of failed algorithms and improve the value of their AI investments. Early detection through clinical AI can improve patient outcomes while also reducing downstream care costs. Governance must remain separate from vendor bias so health systems can make clear decisions about which tools to keep, expand, replace, or remove. The next phase of clinical AI will require stronger infrastructure, especially as agentic AI and cloud-based workflow solutions grow.ResourcesConnect with David Hilderbrand on LinkedIn.Follow Ferrum Health on LinkedIn and visit their website.

Live recording of the fortnightly podcast Design Systems WTF (back for season two!), where Luke Murphy and Michelle Chin attempt to combat all the amazing wtf in design systems. In each episode, they answer a single question around design system troubles with a Q&A from the live audience.Governance seems to be one of those fancy words that gets thrown around a lot by design system people - but what level of governance is actually worthwhile, and how much of it is theater? Michelle and Luke will dive into governance, what level is good enough, and what bits they think you should scrap.Show notesBrad Frost's governance flowchart — the component approval flow Michelle borrowed and adapted: A Design System Governance Process. Also available as a Figma community file, and his lighter-touch follow-up: Master design system governance with this one weird trickNathan Curtis on governance and contribution — his writing on contribution models referenced in the episode: Contributions to Design Systems and Team Models for Scaling a Design SystemManaging Chaos: Digital Governance by Design by Lisa Welchman — Michelle's book recommendation for adding process in a way that isn't "gross", with a historical look at how web governance emerged: Rosenfeld MediaOrg Design for Design Orgs by Peter Merholz & Kristin Skinner — Luke's companion-piece recommendation on ritual and process for design teams, transferable to design systems: petermerholz.com / O'ReillyBig Vape: The Rise and Fall of Juul — the Netflix documentary on Juul and "how not to do a startup": Netflix

We told you co-governance was alive and kicking in local councils, and now the government has finally stepped in to stop it. While mainstream newsrooms looked the other way, local communities were left in the dark about major agreements affecting their rates and properties. Duncan is joined by Far North councillor Davina Smolders to break down what went wrong and how we fix local government. Learn more about your ad choices. Visit megaphone.fm/adchoices

(0:00) About the Boardroom Governance Summit (Aug 26-27, 2026)  (1:17) Intro (2:45) About the podcast sponsor: The American College of Governance Counsel. (3:31) Start of interview.  (4:39) AI and Governance Today (5:34) Data Center Politics (reference to moratorium by New York State) (6:48) About the 3rd Rome Conference on AI, Ethics and Governance (9:06) AI Hype and Job Fears (14:45) Birth and focus of The Chairs Circle and Limerick Lane Cellars. (22:53) CEO Succession Lessons (30:58) Founders versus Boards (37:04) EVs and China's Rise (44:58) Semiconductors, Chips and Geopolitics (49:03) Boards in a Fractured World "[W]e now need to have engaged board members, board members who are curious, who read, who stay up to speed on things, who keep asking more questions. You cannot have directors who are just calling it in anymore." (53:31) Government as Shareholder Karen Francis DeGolia is a board member at Vontier, CelLink, and NAUTO. Penny Herscher is a board member at Lumentum, Penguin Solutions, Forvia SA, and Modern Health. You can follow Evan on social media at:X: @evanepsteinLinkedIn: https://www.linkedin.com/in/epsteinevan/ Substack: https://evanepstein.substack.com/__To support this podcast you can join as a subscriber of the Boardroom Governance Newsletter at https://evanepstein.substack.com/__Music/Soundtrack (found via Free Music Archive): Seeing The Future by Dexter Britain is licensed under a Attribution-Noncommercial-Share Alike 3.0 United States License

In this episode of The Geek in Review, Greg Lambert hosts a solo conversation with Triona Buckley, Chief Product Officer at Actionstep, about generative AI's growing influence on mid-market law firms. Buckley challenges a common assumption about legal AI: faster task completion does not always remove friction. An associate might produce a draft within seconds, only to transfer the burden upstream to a senior lawyer responsible for reviewing sources, reconstructing reasoning, and correcting mistakes.Buckley argues law firms should shift their attention from speed to systems. Standalone drafting and research tools address individual tasks, while system-level AI connects work across an entire legal matter. Embedded within everyday workflows, AI helps lawyers locate information, reduce administrative work, and preserve more time for client advice and professional judgment. The goal is a smoother operating model, rather than a collection of isolated tools producing faster documents.The conversation also examines institutional knowledge, especially within firms lacking large knowledge management or innovation teams. Buckley describes an approach where AI captures decisions, context, and reasoning as lawyers work. This creates a continuously expanding record of how the firm handles matters, advises clients, and applies professional judgment. Governance still plays a central role, including clear audit trails showing whether a person or an AI agent performed each action.Greg and Triona then explore AI as an individual tutor for junior lawyers. Remote and hybrid work have weakened the traditional apprenticeship model built around observation and informal office conversations. Drawing upon decades of firm experience, an AI tutor might question an associate's assumptions, prompt additional research, and reinforce the firm's preferred methods. Such systems offer structured practice while preserving the essential mentoring relationship between senior and junior lawyers.Another major theme is the hidden cost of delayed time entry. Actionstep's Trace passive time capture technology monitors work across practice management, email, and document applications, then presents lawyers with matter-linked, billing-ready entries. More accurate records help firms recover otherwise forgotten time while producing better data for pricing, staffing, client estimates, and profitability analysis. Those insights grow more important as clients push firms toward fixed fees and output-based pricing.Buckley believes mid-market law firms hold several advantages during the AI transition. They often operate with fewer systems, maintain closer client relationships, and move through organizational change faster than larger enterprises. Success will still require disciplined implementation, trusted internal champions, connected data, and sustained attention to client service. Her message is optimistic but direct: firms with strong relationships, clean data, and a clear economic strategy will be better prepared for agentic AI and the changing business of law.Actionstep's U.S. Midsize Law Firm Priorities ReportMetatags: legal AI, mid-market law firms, Triona Buckley, Actionstep, law firm innovation, AI legal training, legal practice managementListen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠Substack⁠[Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ for their sponsoring this episode.]Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠Transcript:

What do you do when your first employer hands you a uniform and tells you to serve tea, despite having a law degree from Tokyo University? For Sachiko Ichikawa, the answer was to quit, pick up law again, and spend the next three decades collecting edges that no one else had. Now a founding member of BDTI (the Board Director Training Institute), a qualified lawyer and CPA, and a Business Lawyers Award winner in governance, Sachiko has trained over 4,000 board directors in Japan and sat in boardrooms where she has seen—up close—what separates the A team from the B team. If you enjoyed this episode and it inspired you in some way, we'd love to hear about it and know your biggest takeaway. Head over to Apple Podcasts to leave a review and we'd love it if you would leave us a message here!In this episode you'll hear:Sachiko's first job at a bank that saw her take control of her career and go into lawThe Livedoor securities fraud case that introduced Sachiko to corporate governanceWhat Sachiko observed in her very first boardroom that taught her how to be an excellent board memberHer favourite book and other fun facts About SachikoSachiko Ichikawa a lawyer at Tanabe & Partners, a director at Board Directors Training Institute, an independent director at Azbil, Olympus and Tokyo Electron Connect with Sachiko LinkedIn: https://www.linkedin.com/in/sachiko-ichikawa-203bb621/ LinksEnoura Observatory: https://www.odawara-af.com/ja/enoura/ Boards that lead: https://amzn.asia/d/02LOo8NO Connect with Catherine LinkedIn https://www.linkedin.com/in/oconnellcatherine/Instagram: https://www.instagram.com/lawyeronair

In this episode we seek to Louise Porteus, ESG Manager at Thor Explorations, a TSX-V & AIM listed gold producer and explorer focused on West Africa with operations and exploration assets in Nigeria, Senegal and Côte d'Ivoire We explore how environmental, social and governance practices have evolved from a compliance function into a key driver of value creation in the mining industry. Louise reflects on the pivotal moments in her career, discusses how ESG expectations differ across jurisdictions, shares how Thor Explorations is leading by example, and offers her perspective on the future of ESG over the next decade.  We also discuss her work supporting Women in Mining and hear her advice for anyone looking to build a career in international ESG and the mining sector. This episode is brought to you by Mining International, a global executive search partner to the mining industry. For bespoke search and advisory services, please visit www.mining-international.org KEY TAKEAWAYS ESG has successfully shifted from a rigid box-ticking exercise into a core driver of long-term value creation and operational viability in the mining industry. True project stability relies on integrating local community dynamics and cultural governance into decision-making rather than just depending on written local legislation. Implementing ESG successfully requires a practical, step-by-step approach to data gathering that builds local trust and capacity, rather than overwhelming teams with massive theoretical toolkits. Advancing women in the mining sector involves moving past token representation and actively training them for hands-on, technical roles that fundamentally transform lives. BEST MOMENTS "Most projects didn't fail because of technical reasons, they failed because of social." "There's a better understanding that it's not a tick-box, it's not just a spreadsheet, it's actually people that have to put the work behind it and do it." "I've been emphatic about bringing what I call cultural governance into our decision-making." "It's not just what you did, but so what? What did that mean? What did that lead to? Did it give more confidence to people?" VALUABLE RESOURCES Mail:        ⁠rob@mining-international.org⁠ LinkedIn: ⁠https://www.linkedin.com/in/rob-tyson-3a26a68/⁠ X:              ⁠https://twitter.com/MiningRobTyson⁠  YouTube: ⁠https://www.youtube.com/c/DigDeepTheMiningPodcast⁠  Web:        ⁠http://www.mining-international.org⁠ GUEST RESOURCES https://www.linkedin.com/company/thor-explorations-ltd/ https://www.linkedin.com/in/louise-porteus-65b2801/ Website: https://thorexpl.com/ Email Address: lporteus@thorexpl.com thorexplorations@yellowjerseypr.com CONTACT METHOD ⁠rob@mining-international.org⁠ ⁠https://www.linkedin.com/in/rob-tyson-3a26a68/⁠ Podcast Description Rob Tyson is an established recruiter in the mining and quarrying sector and decided to produce the “Dig Deep” The Mining Podcast to provide valuable and informative content around the mining industry. He has a passion and desire to promote the industry and the podcast aims to offer the mining community an insight into people's experiences and careers covering any mining discipline, giving the listeners helpful advice and guidance on industry topics.  This Podcast has been brought to you by Disruptive Media. https://disruptivemedia.co.uk/

SUMMARY: Steven Walchek, CEO at Liminal, discusses secure AI enablement for regulated industries and why most enterprises are stuck in perpetual AI pilots. We explore the "agentic cliff" and how Behavioral Agent Automation Platforms (BAAPs) discover and deploy agents by observing how work actually happens.SHOW: 1046SHOW TRANSCRIPT: The Enterprise AI Show #1046 TranscriptSHOW VIDEO: https://youtu.be/nVte_ZKDID4SHOW SPONSORS:ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoRESOURCES:Liminal AISteven Walchek - LinkedInKEY TOPICS:Horizontal security for generative AIData privacy and compliance in AISecurity layers in AI deploymentAgentic AI and behavioral automationFuture industry trends in AI securityTAKEAWAYSSecurity for AI must be integrated at the application layer, not just network or perimeter.Data privacy concerns are central to AI adoption in regulated industries.Organizations need a security layer that supports multi-model, multi-provider AI engagement.Behavioral automation and agentic AI require observability and policy enforcement.The AI industry is still in early adoption, with significant growth expected in the next five years.CHAPTERS/TOPICS:00:00 Introduction and guest introduction02:09 Steven's background and journey in tech03:54 The core problem of AI security in regulated industries07:45 Data privacy concerns and industry challenges12:01 Liminal's approach to AI security and compliance15:52 Security at the application layer and network layer20:02 Agentic AI, behavioral automation, and observability30:04 Future trends and industry outlook31:46 How to connect with Liminal and closing remarksFEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

In this podcast, Jandevman gives us an overview of what they do at Liquidy, how the project originated, and how they ended up building on THORChain.Swap now https://swap.thorchain.org/THORChain is a decentralized crypto exchange. THORChain is the first and biggest DEX for Bitcoin. You can use any self custody wallet to swap and there's no KYC required.Timestamps:00:00:00 Intro00:02:00 Kenton update — Keplr should be working! More integrations are coming!00:03:00 Affiliate page widget is ready for testing00:04:00 Air Canada story00:06:00 Jandevman introduction00:10:00 What was so different about Kujira that attracted you to it?00:13:00 Jandevman rebuilt everything from scratch00:16:00 Treasury discussion — what were the assets?00:17:00 What was MantaDAO?00:19:00 Website walkthrough00:21:00 Valuation breakdown — comparing Liquidy to TradFi00:23:00 Kenton explains NAV and asks about redemptions00:24:00 Financial reports and analytics breakdown00:26:00 Expense breakdown00:27:00 Revenue sources00:29:00 Governance process breakdown00:30:00 Simple majority or supermajority?00:31:00 Veto power through a multisig00:32:00 Bonk comparison00:36:00 Raising external capital?00:38:00 Growing the treasury00:39:00 How does market making work?00:43:00 Why isn't the LQDY token on the base layer?00:45:00 How many wallets support secured assets?00:47:00 Which other wallets should support secured assets?00:48:00 What other financial primitives will LQDY be involved in?00:52:00 Will LQDY get involved in lending?00:55:00 What other assets will be acquired?00:56:00 What about Auto Rujira?00:57:00 Liquidity swap router breakdown00:59:00 What's the difference between the swap router on Rujira and LQDY?01:02:00 Comparing different liquidity pools01:07:00 Will redacted functionality be available?01:09:00 bRUNE breakdown01:11:00 What is a good APY for users?01:13:00 Will STO use the LQDY API?01:15:00 Is there anything else you'd like to add?01:18:00 Transparency discussion01:19:00 Proposal discussion01:22:00 Everything is on-chain01:27:00 Thoughts on inflation01:30:00 The model is beautifully simple01:33:00 We need to do this again!01:34:00 Conclusion

Fewer than 100 companies have scaled enterprise AI from pilots to production to capture great value. Alexander Sukharevsky, who leads QuantumBlack, McKinsey's AI practice, joins Michael Krigsman to lay out the repeatable recipe behind those results and why the winners earn roughly three dollars back for every dollar invested. The conversation covers what capturing AI value really requires, why the CEO and board must own the transformation, and how to lead a hybrid workforce where agents work as colleagues, not tools.======This episode brought to you by Gartner IT Symposium/Xpo™: https://cxo.news/KGg8XY======YOU'LL DISCOVER✅ Why fewer than 100 companies captured two-thirds of AI's value, and what they did differently✅ The repeatable recipe: focus a few domains, ready your data, rewire architecture, and fix the economics✅ Why AI transformation must be led by the CEO and board, not handed to the CTO or chief digital officer✅ How to treat AI agents as accountable colleagues, and who stays accountable for the outcomes✅ Why reinventing a domain beats bolting AI onto an existing process✅ How the winners pursue cost savings and top-line reinvention at the same time✅ Why governance and digital trust belong in from day one, with adults in the room on ethics✅ How expertise and judgment become more valuable as agents speed up the work⏱️ TIMESTAMPS0:00 The repeatable recipe for AI value8:27 Treat agents as colleagues, not tools13:42 Why the CEO must own the transformation18:05 From token maxing to value maxing22:01 Managing a hybrid team of agents23:30 A flexible architecture for changing models26:25 Governance and digital trust from day one30:59 Cost savings versus reinventing the top line34:46 Human focus, judgment, and accountability44:12 Redesign workflows instead of bolting on AI46:24 Careers and apprenticeship in an agent world50:47 What real CEO ownership looks like

Can AI startups keep their promise to benefit humanity? Eric Ries explains why business success often leads to corporate "corruption" of the founder's mission.Eric Ries, creator of the Lean Startup Method, breaks down the inherent tensions between scaling a business and maintaining its core purpose. We examine why so many organizations lose sight of their initial mission as they grow, and what it takes for leadership to stay grounded.This discussion focuses specifically on how AI company ethics are being tested in the current market. Ries shares his perspective on advising Anthropic, offering a rare look at how a major firm attempts to protect its mission while navigating rapid growth. If you are interested in the intersection of philosophy and corporate strategy, this breakdown offers a practical look at the challenges modern founders face.Subscribe for weekly business strategy breakdowns, and let me know in the comments: what do you think is the biggest threat to a company's original mission?YOU'LL DISCOVER✅ Why corruption means making money without creating value, not breaking the law✅ The Sol Price story: how FedMart was liquidated, and Costco grew from the same idea✅ Why shareholder primacy is only about 40 years old, not a law of capitalism✅ The three-part formula for an incorruptible company: purpose, coherence, integrity✅ How alternative ownership structures (foundations like Novo Nordisk and Hershey, purpose trusts like Patagonia) make firms far more durable✅ Eric's idea of financial gravity and why your buying, working, and investing choices matter✅ The job interview question that can push a company to put its mission in its legal charter✅ Why Anthropic's public benefit corporation and long-term benefit trust protect its mission⏱️ TIMESTAMPS0:00 Why success corrupts good companies3:14 What corruption really means5:41 Shareholder primacy is a recent invention8:22 Sol Price, FedMart, and the founding of Costco13:08 Who decides which values matter18:22 Missionaries versus mercenaries19:44 How Google lost its way21:38 Governance structures that protect a mission28:01 Financial gravity and your power35:25 Red flags when vetting a company43:00 Why I am optimistic50:53 Advice for AI founders and AnthropicSubscribe to CXOTalk for weekly conversations with the business and technology leaders shaping the enterprise.Get the CXOTalk newsletter: https://newsletter.cxotalk.comShow notes, transcript, and summary: https://www.cxotalk.com/episode/can-you-build-an-incorruptible-ai-company-a-conversation-with-eric-riesEpisode 923 | Recorded June 26, 2026#CXOTalk #EricRies #Incorruptible #LeanStartup #CorporateGovernance #ShareholderPrimacy #MissionDriven #Leadership #Anthropic #BusinessEthics

In this episode of the AI Agent & Copilot Podcast, John Siefert, Founder and CEO of Cloud Wars, is joined by Cedric Wells, IT leader and former Senior Manager of Infrastructure and Operations at Gorilla Glue. Together, they explore how AI is reshaping IT leadership, software development, governance, and enterprise transformation. Wells shares why continuous learning, balancing strategic vision with execution, and maintaining strong security and data governance will define successful organizations in the AI Era. Their conversation also reflects many of the leadership themes that attendees explored at the 2026 AI Agent & Copilot Summit NA. Key Takeaways Growth mindset is becoming the most valuable IT skill. Wells believes technical expertise alone is no longer enough. The speed of AI innovation requires professionals at every level to continuously refresh their knowledge and remain adaptable. He explains that technologies evolve so rapidly that learning has become a permanent responsibility rather than a periodic exercise. As Wells notes, "Having a mindset that's really around learning as much as I can as things are changing" is essential. He also reminds listeners, "It's changing so fast," making curiosity and adaptability foundational qualities for future IT leaders. AI enhances leadership — but doesn't replace technical understanding. Wells argues that AI is helping close the gap between technical specialists and business leaders, allowing executives to understand complex technologies more quickly. However, leaders still need enough technical context to ask intelligent questions and make informed decisions. As he explains, "Being able to really as a leader leverage AI as much as possible" creates significant advantages. He also emphasizes that "bridging that gap with your leadership skills and leveraging AI on the technical side" will define successful IT leadership moving forward. Governance and security are becoming even more important. Throughout the conversation, Wells repeatedly emphasizes that AI initiatives require close collaboration between infrastructure, information security, governance, and data teams. Without proper oversight, organizations risk exposing sensitive information, creating compliance issues, or building unreliable AI systems. Wells reminds listeners that "It's very important to make sure that those two departments are aligned" and warns that "Employees are doing it whether or not you like it," making proactive governance and secure enablement far more effective than restrictive policies alone. Visit Cloud Wars for more.

Reggie Townsend: Making Responsible AI Irresistible Responsible AI has a design problem. Too often, it is treated as a compliance exercise, a policy document, or a late-stage control, when it should be the operating system that enables organizations to innovate with confidence. In this episode of Scouting for Growth, Sabine VanderLinden welcomes back Reggie Townsend, Vice President of AI Ethics, Governance and Social Impact at SAS, to explore one compelling idea: making responsible AI irresistible. Drawing on decades of experience helping enterprises embed trustworthy AI into their operations, Reggie explains why governance must evolve from abstract principles to practical systems people actually use. As organizations race to deploy generative and agentic AI, the conversation has shifted. Responsible AI is no longer just about avoiding harm—it is about creating the conditions for innovation, resilience, and long-term competitive advantage. Boards are asking tougher questions. Regulators are raising expectations. Employees increasingly need guidance they can apply in real-world decisions, not just policies they acknowledge once a year. This conversation is essential listening for CEOs, board directors, Chief Risk Officers, compliance leaders, AI product teams, and founders navigating the transition from responsible AI intentions to responsible AI execution.   KEY TAKEAWAYS One of the biggest insights I took from this conversation is that responsible AI is fundamentally a design challenge. We have spent years writing principles and policies, yet many organizations still struggle to translate those aspirations into everyday decisions. Reggie reminded me that if governance feels complicated, disconnected, or burdensome, people will naturally work around it. Our challenge as leaders is to make responsible behavior the easiest path rather than the hardest one. I was also struck by how governance is becoming inseparable from business strategy. As generative and agentic AI systems begin making increasingly autonomous decisions, governance can no longer be treated as a legal or compliance function operating at the edge of the organization. It has to become part of product design, procurement, operations, and executive decision-making. Trust is no longer something we communicate after deployment; it is something we engineer from the beginning. Another important theme was the preservation of human agency. While AI can dramatically enhance productivity and decision-making, Reggie reminds us that organizations must remain intentional about where humans stay accountable. The future is unlikely to be defined by replacing people with AI, but by designing systems where humans and intelligent machines complement one another in transparent and meaningful ways. However, perhaps my greatest takeaway is that responsible AI should become a competitive advantage rather than a regulatory obligation. Organizations that embed governance in their innovation will move with greater confidence because customers, regulators, employees, and investors will increasingly reward trust. Making responsible AI irresistible is ultimately about making good governance so practical, intuitive and valuable that people actively choose to adopt it—and that may prove to be one of the most important leadership capabilities of the next decade.   BEST MOMENTS "Responsible AI isn't about slowing innovation. It's about creating the confidence to innovate at scale." – Reggie Townsend "If responsible AI feels like extra work, we've designed it wrong. We have to make it irresistible." – Reggie Townsend "Governance shouldn't be something you visit once a year. It should be embedded into every decision, every workflow, and every system we build." – Reggie Townsend "The question isn't whether AI will make decisions. It's whether we've designed those decisions to preserve human agency." – Reggie Townsend "Trust isn't something you add after deployment. It's something you architect from the very beginning." – Reggie Townsend "We're moving from governing models to governing systems of intelligence—and that's an entirely different challenge." – Reggie Townsend "The organizations that thrive won't be the ones that adopt AI the fastest. They'll be the ones that build trust the fastest." – Reggie Townsend "Responsible AI is no longer just an ethics conversation. It's becoming a leadership conversation, an operational conversation, and ultimately a competitive advantage." – Sabine VanderLinden "As AI becomes more autonomous, our responsibility as leaders becomes even more intentional." – Sabine VanderLinden "The future belongs to organizations that can turn responsible AI from a policy into a practice." – Sabine VanderLinden   ABOUT THE GUEST Reggie Townsend is Vice President of AI Ethics, Governance and Social Impact at SAS, where he leads SAS' global AI Ethics, Governance and Social Impact organization. His remit includes the company's Data & AI Ethics Practice, AI & Society initiatives, AI Governance Advisory, Standards, Regulations & Risk Intelligence programs, and Accessible & Adaptive AI efforts. He drives SAS' work on trustworthy, human-centric innovation across products, policies, and partnerships.  Reggie is recognized as one of the clearest voices in responsible and trustworthy AI. He has served as a member of the White House National AI Advisory Committee, sits on the board of EqualAI, and works at the intersection of responsible innovation, enterprise governance, social impact, and emerging AI regulation. In this conversation, he explores how organizations can turn AI governance from a source of friction into a driver of adoption, accountability, and growth.    ABOUT THE HOST Sabine VanderLinden is a corporate strategist turned entrepreneur and the CEO of Alchemy Crew Ventures. She leads venture-client labs that help Fortune 500 companies adopt and scale cutting-edge technologies from global tech ventures. A builder of accelerators, investor, and co-editor of the bestseller The INSURTECH Book, Sabine is known for asking the uncomfortable questions—about AI governance, risk, and trust. On Scouting for Growth, she decodes how real growth happens—where capital, collaboration, and courage meet. If this episode sparked your thinking, follow Sabine VanderLinden on LinkedIn, Twitter, and Instagram for more insights. And if you're interested in sponsoring the podcast, reach out to the team at hello@alchemycrew.ventures

If you tell your AI NOT to delete your database you're good right? In this episode of IT Visionaries, Chris Brandt sits down with Daniel Meyer, CTO of Camunda, to explore why prompts alone are not enough to govern AI. They discuss the difference between governance by instruction and governance by structure, why enterprises are struggling to turn AI investments into meaningful outcomes, and why adding agents to legacy processes often creates faster versions of the same old problems. Daniel also explains how one company reduced a four-day process to just 17 minutes—and why results like that only happen when organizations fundamentally rebuild how work gets done. Highlights: • Why enterprises need guardrails AI cannot override • How orchestration connects people, systems, and AI agents • Why process redesign matters more than simple automation • How businesses can safely enable non-technical teams to build with AI • What the orchestrated enterprise could look like over the next five years Connect Daniel Meyer on LinkedIn Camunda IT Visionaries   Chapters 2:16 Why Business Processes Are Enterprise Algorithms 2:40 Why AI Investment Isn't Delivering Bigger Outcomes 4:29 What Real AI Leverage Looks Like 6:35 Rebuilding the Software Development Process Around AI 11:19 Why Companies Struggle to Understand Their Own Processes 15:29 How Harmony Made a Process 90x Faster 16:40 How ProcessOS Reengineers Business Processes 19:54 Building AI Agents You Can Actually Trust 21:49 When an AI Agent Deletes the Database 22:28 Governance by Instruction vs. Governance by Structure 25:03 What AI Governance Can Learn From Human Access Controls 38:45 How to Test and Switch Between AI Models 45:00 Is Enterprise Software Becoming Headless? 46:51 The Rise of the Orchestrated Enterprise -- This episode of IT Visionaries is brought to you by Meter - the company building better networks. Businesses today are frustrated with outdated providers, rigid pricing, and fragmented tools. Meter changes that with a single integrated solution that covers everything wired, wireless, and even cellular networking. They design the hardware, write the firmware, build the software, and manage it all so your team doesn't have to.That means you get fast, secure, and scalable connectivity without the complexity of juggling multiple providers. Thanks to meter for sponsoring. Go to meter.com/itv to book a demo.---IT Visionaries is made by the team at Mission.org. Learn more about our media studio and network of podcasts at mission.org. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

On this episode of Power House, Zeb sits down with Larry Bailey from Mortgage Workflow Partners, who began his career as a loan processor in 1993 and now champions a simple but disruptive idea: “workflow before technology.”  Bailey argues that most mortgage and real estate organizations have invested heavily in software and AI without first understanding how work actually gets done. Rather than improving efficiency, new technology is often layered onto disorganized processes because workflows were never clearly documented or owned. The conversation digs into how sales-led leadership shapes this reality. In lending, top leaders rise through sales, where adaptability is rewarded, but workflow is often overlooked. As a result, that critical knowledge resides with individuals rather than in documented processes. Bailey explains that workflow interviews quickly reveal the difference between employees eager to improve operations and those who rely on tribal knowledge to protect their value. Bailey defines workflow governance as documenting processes, assigning clear business ownership and continuously maintaining them as the organization evolves. He shares examples of large lenders where every branch operated differently, creating inefficiencies and making leadership nearly impossible. His approach establishes a standardized best-practice workflow while allowing teams flexibility beyond the core process if they choose. Looking ahead, Bailey believes technology alone will not reduce production costs or burnout. Despite years of investment, the cost per loan remains stubbornly high because organizations continue automating broken processes. Sustainable improvement comes from understanding the work first, then using that visibility to determine where technology belongs, what should be automated and how employees can focus on higher-value activities instead of repetitive tasks. Related to the episode: ⁠Zeb Lowe's LinkedIn⁠ Larry Bailey's LinkedIn Mortgage Workflow Partners Want more from Zeb? Don't forget to subscribe to LendingLife. The Power House podcast brings the biggest names in housing to answer hard-hitting questions about industry trends, operational and growth strategy, and leadership. Join HousingWire's Zeb Lowe every Thursday morning for candid conversations with industry leaders to learn how they're differentiating themselves from the competition. Hosted and produced by the HousingWire Content Studio.

Andrew Burt is a lawyer, entrepreneur, and former national security official widely recognized as one of the world's leading experts in the intersection of law and artificial intelligence.  Over the last decade, he has built companies, law firms, and software systems that have revolutionized how AI is managed for legal risks, and his work has impacted hundreds of millions of people around the world. As a pioneer in the field of legal engineering, he founded and led the world's first legal engineering team focused on automating data governance in 2016. In 2019, he co-founded and later sold the first-ever law firm run by lawyers and data scientists solely focused on artificial intelligence.  He is co-founder and CEO of Luminos.AI, the first AI governance company focused on legal risk, where he currently serves as CEO. In this episode… Companies are adopting AI faster than they can set guardrails around it. Privacy and legal teams can review an AI model or approve a vendor contract, but AI governance doesn't stop there. Risk varies by use case, including whether the system is internal or customer-facing and the level of human oversight involved. As organizations connect new AI tools, chatbots, and agents to more business processes and systems, AI governance has to move from policy to a scalable structure.  One of the biggest challenges companies face is making governance work at the same speed as AI adoption. Andrew Burt knows this well as a co-author of the NIST AI Risk Management Framework, where he helped shape how companies identify, document, and manage AI risk. Turning frameworks into action is where organizations often get stuck. Implementing AI guardrails requires involvement from legal, privacy, security, compliance, engineering, and other business teams. Yet when too many people share responsibility without a lead decision-maker, it can create what Andrew calls "governance debt." Effective governance starts with accountable leadership and a working connection between the teams writing the rules and the teams building the AI systems. This means moving beyond policy-heavy approaches so governance can scale with the business and the technology.  In this episode of She Said Privacy/He Said Security, Jodi and Justin Daniels talk with Andrew Burt, Co-founder and CEO of Luminos.AI, about the challenges of scaling AI governance. Andrew explains why traditional governance models struggle to keep up with how quickly AI systems are built and deployed. He breaks down the differences between managing risk at the model level and at the use-case level, including why the same AI tool can carry different risks depending on its use. Andrew also shares his prediction for the future of AI regulation in the United States and offers practical steps companies can take to strengthen AI governance.

Nick Almond and Proph3t on ENS's treasury fight, the BonkDAO heist, and why Proph3t would not touch Venice's VVV token. ======================================================== Thank you to our sponsor! ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Cape⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: Your biggest crypto vulnerability isn't your wallet, it's your phone number. Cape is America's privacy-first mobile carrier that rotates your SIM identity daily and blocks SIM swaps before they happen. Get 33% off your first six months at cape.co/unchained (use code: UNCHAINED). ======================================================== Nick Johnson, the founder of ENS Labs, used his own tokens to kill a vote renewing ENS DAO's Security Council, potentially clearing the way for a foundation to take over a treasury worth more than $100 million. Nick Almond, head of governance at the Jito Foundation, and Proph3t, cofounder of MetaDAO, join Laura Shin to untangle what that move reveals about who should control a DAO's money, and whether voting was ever the right way to decide it. They trace ENS cofounder Jeff Lau's warning that the treasury became a honeypot with zero accountability, and the collapsing voter turnout that let a 3% token stake decide the DAO's fate. Proph3t makes the case for MetaDAO's decision markets over voting entirely, while Nick argues curated delegates solve the same capture problem without giving up the vote. They also cover the $20 million BonkDAO heist, pulled off with one proposal and seven votes, and the backlash over Dragonfly's investment in Venice's VVV token. Both guests agree DAOs are near a bottom. What comes next depends on whether anyone tries something new. Host: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Laura Shin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Host / Unchained Guests: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Nick Almond - Head of Governance at the Jito Foundation ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Proph3t - Co-founder of MetaDAO Timestamps

We discussed a few things including: 1. Jonathan's career journey   2. Cranium AI   3. AI ecosystem and timeline 4. AI trends, opps and challenges   5. Outlook for 2026 Jonathan is CEO of Cranium AI, Inc. The company spun out of the KPMG Studio and came out of stealth mode in April 2023. Jonathan is a former Partner at KPMG, cyber security industry leader, and visionary.   Prior to KPMG, he led Prevalent to become a Gartner and Forrester industry leader in 3rd party risk management before its sale to Insight Venture Partners in late 2016. At KPMG he led third party security globally, AI Security services, and built Cranium in stealth.   He has been quoted in a number of publications and routinely speaks to groups of clients regarding trends in IT, information security, and compliance.   Jonathan received his MBA from The Pennsylvania State University, is a Certified Information Systems Security Professional (CISSP), and Certified Third Party Risk Professional (CTPRP). #podcast #AFewThingsPodcast

SUMMARY: On today's "Models and Markets" - we explore about the FinOps experience from Cloud is having to adapt to the changing demands of Enterprise AI. SHOW: 1045SHOW TRANSCRIPT: The Enterprise AI Show #1045 TranscriptSHOW VIDEO: https://youtu.be/Plb88y-IkZYSHOW SPONSORS:Nasuni - Activate your data for AI and request a demoShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!SHOW NOTES:Topic: Finops for AI?Why now? Cost of tokens goes up as model performance increases, but still needs subsidies…Past: FinOps for Cloud - prices grew out of control, needed centralization for expense management and capital allocationPresent: TokenMaxxing, the move from per-seat to per-token pricingFuture: What happens when you can't afford the Ferrari anymore? Will there be a glut of FinOps for AI startups? What happens when usage is regulated and centralized?FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

What does it actually take to govern a living system, instead of just managing one?In this conversation, Yoshi Pantera sits down with Gustavo Segovia, a long time member of the Traditional Dream Factory ecovillage in Portugal, who works at the intersection of decentralized technology and regenerative culture. Gustavo has spent years inside web3 governance, contributing to projects like Collabberry, GravityDAO, and Coh3rence, designing reward systems, conflict-resolution processes, and governance frameworks meant to help communities self-organize without extracting from the people or places that sustain them.He served as Academic Director at DAO Education and has taught Decentralized Organizational Systems at Universidad Complutense de Madrid. Grounded equally in enterprise systems and contemplative traditions, Gustavo brings a rare perspective. Someone fluent in both the technical architecture of decentralized systems and the deeper question underneath all of it: how do we actually live and decide together, without recreating the same extraction we are trying to move beyond?This conversation goes deep into decentralized governance, conflict resolution, reward systems that don't extract, and what regenerative technology looks like with governance when it's built to serve life rather than control it.This episode is part of our ongoing exploration of Regenerative Governance, the 5th Pillar of Regenerative Culture.Interested in practicing Regenerative Governance?You can apply to be part of our Regenerative Leaders Community. You will learn hands-on how to govern ourselves as individuals and as community in order to meet everyone's needs and the collective vision. This is useful for your leadership growth and for how your family, your community, ecovillage, business, company governs itself.

The United States is approaching the 250th anniversary of the Declaration of Independence—a milestone that invites both celebration and reflection. At the same time, the nation finds itself wrestling with profound questions about democracy, the rule of law, political polarization, economic opportunity, executive power, and the rapid rise of transformative technologies like artificial intelligence. Today's guest believes this is precisely the moment to ask difficult questions about who we are as a nation and where we're headed. Joining me is Alexandra Natapoff, the Lee S. Kreindler Professor of Law at Harvard Law School, an award-winning criminal justice scholar, and co-editor, with Guy-Uriel Charles, of America Unfinished: 250 Years of Law and Governance. Bringing together more than sixty Harvard Law School faculty members, this remarkable collection examines the enduring experiment in American democracy that began in 1776 and continues to evolve today. We'll discuss why America's constitutional project remains unfinished, how law both reflects and shapes our society, and what challenges—and opportunities—lie ahead as the nation enters its next quarter millennium.

Finally doing a solo episode! 'Bout time.I talked to 18 CMOs / Mktg VPs for 9 hours about what is super intense for them right now and then I analyzed what I heard and packaged it up for you. Here's the report. Let me know if you have any questions as you review + please share with your team and your marketing leader friends.Jump in:00:00 - Intro to the research00:33 - The motivation behind exploring in-depth insights01:14 - The "Aha Moment" skill for finding truths 01:57 - The scoring system02:45 - The mess AI leaves behind03:11 - What's going well05:09 - The surprising top needs06:02 - Governance over AI06:27 - The debate: buy or build07:07 - Internal marketing is even more important today07:53 - The challenge of product builds outpacing marketing playbooks08:13 - Leadership burnout08:41 - Visibility concerns from AI search and zero click09:02 - The bottleneck of editing content produced by AI10:04 - Creating a clear AI governance system to help avoid chaos11:35 - Product survival in an AI future12:38 - Example of a company moving towards in-house tool development13:32 - The importance of differentiation, distinction, positioning, story, brand14:06 - Winning through relationships, outcomes, and showing up at the right moments (memorable)15:01 - The case for powerful storytelling and brand15:38 - Organizational shifts - the org chart is changing16:11 - The impact of AI on headcount and organizational structures16:33 - CEOs' perspectives on AI replacing marketing jobs and the potential fallout17:19 - Leveraging AI to scale teams20:23 - The overall mood is that two things are trueSubscribe to Building With Buyers on Apple or Spotify or wherever you like to listen, and don't forget to leave a review if you're lovin' the show.marketing leaders intense needs report: https://marketing-needs-synthesis.vercel.app/Anna on LinkedIn: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠linkedin.com/in/annafurmanov⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Website: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠furmanovmarketing.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Newsletter: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠One Insight⁠⁠⁠

Send us Fan MailMaking Data Simple sits down with Dave Trieer, CEO of ModelOp, to explore therapidly evolving world of AI – particularly what happens when it starts actingautonomously. From safely deploying AI in regulated industries to navigatingcritical governance challenges, Dave offers invaluable insights on thistransformative technology.01:22 Meet Dave Trier04:22 The Terminator is Coming10:33 The Definition of Autonomous12:15 Pushing AI into Production17:33 AI Misconceptions21:12 Use Case Qualification22:53 ModelOp Value Prop29:59 The "One Thing" with AI Governance33:13 AI Regulation36:47 Predicting AI39:45 Lightening RoundLinkedIn: linkedin.com/in/davidetrierWebsite: https://www.modelop.com/Want to be featured as a guest on Making Data Simple?  Reach out to us at almartintalksdata@gmail.com and tell us why you should be next.  The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun. 

Send us Fan MailMaking Data Simple sits down with Dave Trieer, CEO of ModelOp, to explore therapidly evolving world of AI – particularly what happens when it starts actingautonomously. From safely deploying AI in regulated industries to navigatingcritical governance challenges, Dave offers invaluable insights on thistransformative technology.01:22 Meet Dave Trier04:22 The Terminator is Coming10:33 The Definition of Autonomous12:15 Pushing AI into Production17:33 AI Misconceptions21:12 Use Case Qualification22:53 ModelOp Value Prop29:59 The "One Thing" with AI Governance33:13 AI Regulation36:47 Predicting AI39:45 Lightening RoundLinkedIn: linkedin.com/in/davidetrierWebsite: https://www.modelop.com/Want to be featured as a guest on Making Data Simple?  Reach out to us at almartintalksdata@gmail.com and tell us why you should be next.  The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun. 

Patrick Phillips talks about AI governance, workforce readiness, and the future of enterprise AI adoption. Patrick is Chief Information Officer at Vasion, where he has helped drive the deployment of AI across the organization. His is an expert in frameworks for security, compliance, and responsible AI use. Listen for three action items you can use today. Host, Kevin Craine Do you want to be a guest? https://DigitalTransformationPodast.net/guest Do you want to be a sponsor? https://DigitalTransformationPodcast.net/advertise

What happens when the brightest minds in legal, technology, and innovation come together to shape the future of our profession? Welcome to the Legally Speaking Podcast Legal Tech Talk 2026 miniseries. As the UK's number one legal podcast and show ranked in the top 1% of podcasts globally, we're delighted to be returning as the official media partner for Legal Tech Talk for the third time. Having supported this event since the beginning. We've witnessed firsthand how it has become Europe's largest legal technology conference, bringing together the people, ideas, and innovations transforming the legal industry. Across this special series, we'll be speaking with some of the world's leading legal professionals, founders, technologists, change makers to explore what's next for law. Because our mission remains the same. Inspiring legal minds, transforming legal futures. Let's get into it. Jeffrey Shapiro is a legal tech and future-of-law thinker who talks about how AI is changing the legal industry, but not just as a tool problem — more as a mindset, culture, and integration challenge. He focuses on breaking down silos so firms can use data intelligently, staying ahead of regulation like the EU AI Act, and keeping human trust and authenticity central as technology advances. He also emphasises curiosity, continuous learning, and community as key traits for future legal leaders, often explaining complex ideas in memorable, down-to-earth ways. So why should you be listening in? You can hear Rob and Jeffrey discussing:- Cross-silo data integration matters- Human connection builds trust- Regulatory agility is critical- Curiosity shapes future leadership- Openness improves collaboration.Connect with Jeffrey Shapiro here - https://www.linkedin.com/in/jtshap/

Official commemorations of the 250th anniversary of the U.S. Declaration of Independence have now ended, with anticipated federally subsidized, countrywide conversations about the meaning of the U.S. never materializing. Instead, much of the commemorative and contemplative energy was consumed by a federal government temporarily captured by a White nationalist regime intent on narrowing rather than expanding both polity-wide memory and imagination.The country's ongoing inability to either manufacture or negotiate consensus, or forcefully reject its resurgent and desperate White nationalist virus, tells us something more important about the moment itself. We are living through the end stages of a roughly five-century period of Western global strength. As the order it birthed becomes increasingly brittle, narratives that sustain its power require ever more aggressive forms of maintenance.Donald Trump's Freedom 250 State Fair was a fitting illustration. Rather than presenting a negotiated national vision, it projected an anemic, market-driven EuroFuturism detached from the lived realities of the people being assaulted within and beyond it.Against that thin and fitfully curated spectacle stands far more vibrant and complicated social worlds produced through Governance formations of family, community, Cultural Meaning Making, Movement, and Memory.In Class With Carr has spent significant time displacing "250" as an anchoring historical marker, using an Africana Studies method and lens to break through narrowing Social Structure narratives in order to make space for self-determining forms of Governance, Ways of Knowing, and understanding time, belonging, and community.That work makes it increasingly possible to say, publicly and without apology, that Western-style polities need not define or contain our common humanity while remaining fully engaged with the institutions and social formations with and through which we must still struggle.Last week, in Session 330, we proposed moving "Beyond 250." Today, we use ongoing years of collective work informed by deep study and real-time responses to increasingly desperate acts of White political violence to engage in a thought exercise grounded in another way of organizing historical time.The question is not simply what happened in 1776 or even in 1865. The deeper question is why those dates organize our thinking in the first place.What are the odds that we can use this season of endings to harness a momentum of memory for a different and better collective purpose?Are you a member of Knarrative? If not, we invite you to join our community today by signing up at: https://www.knarrative.com. As a Knarrative subscriber, you'll gain immediate access to Knubia, our growing community of teachers, learners, thinkers, doers, artists, and creators. Together, we're making a generational commitment to our collective interests, work, and responsibilities. Join us at https://www.knarrative.com and download the Knubia app through your app store or by visiting https://community.knarrative.com.To shop Go to:TheGlobalMajorityMore from us:Follow on X: https://x.com/knarrative_https://x.com/inclasswithcarrFollow on Instagram IG / knarrative IG/ inclasswithcarr Follow Dr. Carr: https://www.drgregcarr.comhttps://x.com/AfricanaCarrFollow Karen Hunter: https://karenhuntershow.comhttps://x.com/karenhunter IG / karenhuntershowSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Baroness Dambisa Moyo is a global economist, author, board member, and investor who sits at the intersection of public policy, corporate governance, and capital allocation. Dambisa serves in the U.K. House of Lords, sits on the boards of Chevron, Starbucks, Condé Nast, and Oxford University's investment committee, is Chair of the Economic Club of New York, and oversees Altered Trajectory alongside her husband, Jared Smith, the family office formed after his sale of Qualtrics in 2018. Our conversation traces Dambisa's journey from growing up in Zambia to becoming a leading voice on global economic development and governance. We discuss how her experiences across more than 80 countries and on the boards of four global companies shaped her judgment on economic growth, governance, and decision-making. We then turn to the application of those lessons at Altered Trajectory, including the evolution away from an endowment-style portfolio, balancing Dambisa's macro convictions with Jared's moonshot investing style, and positioning for long-term themes. Along the way, we discuss the challenge of investing through structural change while avoiding ideological thinking. Any leader should see for themselves the benefits of elite coaching. Try ALEX: tryalex.admiredleadership.com. Learn More Follow Ted on Twitter at @tseides or LinkedIn Subscribe to the mailing list Access Transcript with Premium Membership   Editing and post-production work for this episode was provided by The Podcast Consultant (⁠https://thepodcastconsultant.com⁠)

In this podcast Michael Stiefel spoke to Sarah Wells about the relationship of governance to software architecture. Governance enables teams to work effectively by establishing procedures that minimize system complexity, improve security, and reduce repetitive tasks. Targeted checklists help engineers by reducing the stress over these procedures. This is especially critical in high pressure situations like critical incident response. Architecture should focus on the technical decisions that are difficult to reverse. The conversation then shifted to exploring the relationship of governance to agentic AI software development. While AI can be very effective for writing code, building internal tools, and automating tasks, experienced engineers still need to validate tests, review outputs, establish clear architectural guidelines, and demand that the AI agents be hypercritical of their own work. With the focus on AI software development, architectural skills are at a premium. Talented individuals that demonstrate architectural skills need to be found and sponsored. Read a transcript of this interview: https://bit.ly/4fndHG3 Newsletter: Subscribe to the Software Architects' Newsletter, a monthly roundup of the patterns and technologies senior practitioners are working through, with the news and lessons from people doing the work: https://www.infoq.com/software-architects-newsletter InfoQ Online Certification Programs: 5-week online cohorts for senior engineers and architects, built around QCon talks. Programs now cover software architecture, AI engineering, and organizational architecture. Each week you join a four-hour live session with a confidential peer group of practitioners from other companies, apply frameworks from QCon talks to the decisions you're making at work, and earn an InfoQ certification. You leave with new approaches, or confirmation that the calls you're already making are the right ones. Learn more: https://certification.qconferences.com/ Upcoming Events: QCon San Francisco 2026 (November 16-20, 2026) https://qconsf.com/ QCon London 2027 (April 13-16, 2027) https://qconlondon.com/ The InfoQ Podcasts: Weekly conversations with senior software leaders about how they build systems and teams, including what they'd do differently. Listen to all our podcasts and read interview transcripts: The InfoQ Podcast: https://www.infoq.com/podcasts/ Engineering Culture Podcast by InfoQ: https://www.infoq.com/podcasts/#engineering_culture Generally AI: https://www.infoq.com/generally-ai-podcast/ Follow InfoQ: Mastodon: https://techhub.social/@infoq X: https://x.com/InfoQ LinkedIn: https://www.linkedin.com/company/infoq/ Facebook: https://www.facebook.com/InfoQdotcom Instagram: https://www.instagram.com/infoqdotcom/ YouTube: https://www.youtube.com/infoq Bluesky: https://bsky.app/profile/infoq.com Write for InfoQ: Share what you've learned building software with a community of senior practitioners, and get your work in front of the people who read InfoQ. https://www.infoq.com/write-for-infoq

SUMMARY: Something new - "Models and Markets" - Aaron and Brian explore how recent news and macro trends are causing more companies to explore whether they should Buy, Build or Rent their AI future. SHOW: 1044SHOW TRANSCRIPT: The Enterprise AI Show #1044 TranscriptSHOW VIDEO: https://youtu.be/vcroGCXd3N4SHOW SPONSORS:ShareGate - ShareGate Protect. Microsoft 365 Governance, we got this!Nasuni - Activate your data for AI and request a demoSHOW NOTES:Topic: Own AI or Rent AI?Why now? Fable 5 and GPT 5.6 get restricted in the USPast: Private Cloud (on-prem/server huggers) vs. Public cloud vs. *gasp* hybrid cloudPresent: OSS Models vs. Big API modelsFuture: What happens when the subsidies go away, and rational business practices hit the industry??FEEDBACK?Email: show @ the enterprise ai show dot comeBluesky: @TheEntAIShow.bsky.socialTwitter/X: @TheEntAIShowInstagram: @TheEntAIShow

Coming to you today from the July Course in Newmarket as Nick his joined on track by Lydia Hislop to bring you the latest news stories from around the racing world. First up, Jockey Club CEO Jim Mullen talks all things Kempton, governance of the sport and his views on the financial risk assessments that the Gambling Commission gave the green light to this week. Lydia, listening in to this, shares her views and tries to infer what the Jockey Club's stance is on Kempton and what's likely to happen there. Trainer in form, Ed Bethell joins the show ahead of Danger Bay in the John Smiths Cup at York tomorrow and runs through his other weekend runners whilst Richard Ryan looks forward to Superlative Stakes hopeful, Green Sovereign, who was luckless at Royal Ascot. Lydia previews what looks to be a competitive and classy renewal of the July Cup tomorrow before proving an update on the classification of pattern races in Australia. Finally, Eva is at the sales speaking to Tattersalls's Jason Singh.

Preview for Later Today: Veronique de Rugy reflects on a Siena fresco contrasting good and bad government. She explores how arbitrary justice leads to societal decay and family destruction, noting that contemporary governance often struggles with these same issues. (2)1660 MILAN