Podcasts about Analytics

How good can the Minnesota Vikings be with Kyler Murray as their quarterback? Analytics expert Kevin Cole from Unexpected Points analyzes the Vikings' ceiling with Murray. Can they legitimately compete for a Super Bowl with Murray at quarterback? What factors will play into it? Would Kevin bail on JJ McCarthy after the Vikings signed Carson Wentz? Did the NFC North have a good free agency overall? Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

ITB analytics expert Sam Finkel joins ITB host Geoff Mosher to go inside athletic testing by tight ends at the NFL Scouting Combine, and which ones will be appealing fits for the Eagles' new offense.► Subscribe to our Patreon Channel for exclusive information not seen or heard anywhere else and become among smartest Birds fans out there (just ask our members!!) + get all of our shows commercial free!!https://www.patreon.com/insidethebirds► Sign up for our newsletter! • Visit http://eepurl.com/hZU4_n.►Support our sponsors!!► Simpli Safe Home Alert System: https://simplisafe.com/BIRDS for 60% OFF!► Camden Apothecary: https://camdenapothecary.com/Follow the Hosts!► Follow our Podcast on Twitter: https://twitter.com/InsideBirds► Follow Geoff Mosher on Twitter: https://twitter.com/geoffpmosher► Follow Adam Caplan on Twitter: https://twitter.com/caplannfl► Follow Sam Finkel on Twitter: https://twitter.com/sam_finkelNFL insider veterans take an in-depth look that no other show can offer! Be sure to subscribe to stay up to date with the latest news, rumors, and discussions.For more, be sure to check out our official website: https://www.insidethebirds.com.

What does it take to turn millions of customer interactions into meaningful relationships instead of missed opportunities? In this episode, recorded live at the Qualtrics X4 Summit in Seattle, I sit down with James Bauman, Senior Director and Head of Experience, Analytics, and Insights at TruGreen. James leads customer experience, analytics, and retention strategy across a business that manages around 60 million customer touchpoints every year. And as he explains, that scale creates both opportunity and risk. At the center of our conversation is a challenge he describes as the "leaky bucket." TruGreen was investing heavily in acquiring customers, but too many were slipping away due to inconsistent experiences and missed moments. The real question became how to understand what customers actually need, when they need it, and how to respond in a way that builds trust and long-term loyalty. We explore how TruGreen built an omnichannel customer experience program designed to listen across every interaction, from digital channels to service calls, and connect that feedback with real customer behavior. But what stood out to me was how they moved beyond simply collecting feedback and into taking action in the moment. That's where AI agents come in. Rather than relying solely on traditional follow-up processes, TruGreen is now embedding AI directly into customer check-ins and surveys. These agents respond in real time, using context from the customer's history and recent interactions to provide relevant, immediate support. It changes the experience from something reactive to something far more responsive. The impact has been significant. James shares how AI agents are now addressing around 51% of customer concerns upfront and cutting escalations by more than 30%. At the same time, they are freeing up human teams to focus on the conversations that truly require empathy and relationship-building, rather than spending time on repetitive follow-ups that may never get a response. We also talk about the reality behind making this work. There's no shortcut. The speed of implementation came from the groundwork TruGreen had already put in place, building a strong data foundation and connecting systems across the business. Without that, the AI would lack the context needed to be useful. James also challenges some of the common narratives around AI. It's not something you can simply switch on and expect instant results. But it's also far from hype when applied thoughtfully. In his experience, AI agents can deliver real value, both in customer outcomes and business performance, when they are placed in the right moments and supported by the right data. For me, this conversation is a reminder that customer experience is shifting. It's moving away from slow feedback loops and into something far more immediate, where businesses can listen, understand, and act in real time. And I'd love to hear your perspective. Are you seeing AI agents genuinely improve customer experience in your organization, or are you still trying to figure out where they fit? Useful Links Connect with James Bauman Learn more about TruGreen Qualtrics X4 Summit    

App Store Connect shows a lot of data, but it's not always easy to understand.In this video, Steve P. Young demos AppSignals, a new app analytics dashboard built specifically for indie app developers and small app teams.AppSignals simplifies your App Store analytics and shows the most important app growth metrics in one clear dashboard.Instead of digging through complicated reports, you can instantly see some important app metrics. If you're building or scaling an app and want a clear view of your installs, conversions, and revenue, this tool is designed to make app analytics much easier.Try it here

Cam Crow, Director of Data and Analytics at Vacatia, joins The Tech Trek to unpack what happens when a startup outgrows informal ways of working. This episode looks at how data teams can introduce project management frameworks without killing speed, how to manage stakeholder demand as complexity rises, and why the right operating model matters even more as AI begins to reshape analytics work.Cam shares a practical view from the middle of real growth, from startup scrappiness to acquisitions, migrations, and a much wider stakeholder base. He explains when process becomes necessary, how to build trust during that shift, and where AI is starting to change both delivery workflows and the future of business insights.In this episode• Why early stage teams should add process cautiously, not by default• The moment speed and quality start breaking under too many competing requests• How public communication and domain based stakeholder channels reduce friction• Why planning routines matter as much for stakeholders as they do for the data team• Where AI fits today, from faster delivery to semantic layers that support better answersHighlights00:00 Cam Crowe joins the show to discuss project management frameworks through the lens of data, startup growth, and stakeholder alignment01:58 Why Cam resisted formal sprint planning in the startup phase and why that made sense at the time05:58 The tipping point where too many priorities start hurting both velocity and quality11:49 How moving conversations out of direct messages and into domain channels changed team operations15:03 Inside the two week development cycle and the planning week that keeps stakeholders engaged21:08 How Cam is thinking about AI, semantic layers, and the future of on demand analyticsA standout idea from this conversation, process should be added conservatively, only when the business truly needs it.Practical takeaways• Do not formalize too early, but do not wait until the system is already breaking• Make prioritization visible once demand exceeds capacity• Use shared channels instead of one to one communication to reduce bottlenecks• Build stakeholder rituals into the operating model, not just team rituals• Treat AI readiness as an infrastructure challenge, not just a tooling decisionFollow The Tech Trek for more conversations with operators, builders, and technology leaders shaping how modern teams work and scale.

Guest: Lennart Hinrichs, Executive Vice President & General Manager of Americas, TWAICE Overview:In episode 318 of The Green Insider, Lennart Hinrichs shares how TWAICE's independent battery analytics software helps large‑scale energy storage operators identify issues early, optimize performance, and reduce financial and operational risk across the battery lifecycle. Key Topics Covered: Lennart's background and the founding of TWAICE, rooted in early hands‑on experience with battery energy storage systems in Munich that exposed gaps in performance visibility. How TWAICE evolved into a battery analytics platform designed to provide deep insight into large‑scale battery energy storage systems used for grid reliability and renewable energy integration. An overview of TWAICE's software, which analyzes battery systems at the cell level to detect imbalances, safety risks, and hidden performance losses without controlling charging or discharging. Why traditional battery troubleshooting is slow and reactive, and how predictive analytics enable faster root‑cause identification and proactive maintenance. Common battery challenges across the lifecycle, including early‑stage manufacturing defects, longer‑term degradation, and the risks of relying solely on OEMs for performance transparency. The role of independent, third‑party analytics in supporting warranty claims and holding manufacturers or integrators accountable for underperformance. A real‑world case study from California showing how analytics transformed maintenance practices from reactive firefighting to data‑driven optimization. The financial and trading implications of accurate battery performance data, including avoiding penalties through reliable state‑of‑charge assessments. Industry trends, scaling challenges, and Lennart's perspective from speaking at major battery and energy storage conferences. Key Takeaway:As battery energy storage scales globally, independent analytics are becoming essential for maintaining performance, managing degradation, and protecting long‑term investments. Become a Green Insider Be sure to subscribe to The Green Insider, powered by ERENEWABLE, wherever you get your podcasts—and don't forget to leave us a five‑star rating! To learn more about our guests or to inquire about sponsorship opportunities, please contact ERENEWABLE and The Green Insider Podcast. The post Battery Analytics Are Transforming Energy Storage appeared first on eRENEWABLE.

Film breakdown, analytics insight and fantasy football projection for Zachariah Branch, an electric prospect with a poor analytical profile from the 2026 NFL Draft class patreon.com/rookiebigboard Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Film breakdown, analytics insight and fantasy football projection for Chris Brazzell II, a high upside prospect in the 2026 NFL Draft class patreon.com/rookiebigboard Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In healthcare, access to care ultimately comes down to one fundamental challenge: balancing supply and demand. In this episode of the Patient Access Collaborative podcast, Executive Director Elizabeth Woodcock speaks with Chris Profeta, Senior Director of Research and Analytics, about the emergence of ambulatory capacity management as a critical discipline within patient access. Together, they reflect on the rapid growth of the field - from a time when only a handful of professionals focused on capacity management to today's sold-out roadshows and growing national attention. The conversation explores why traditional market dynamics don't function in healthcare, how technological advances like automated waitlists are reshaping access to care, and why understanding true patient demand remains the next frontier for health systems.  

Mark and Marisa are joined once again by colleagues Chris Lafakis and Juan Pablo Fuentes to discuss the past week's developments in the Middle East and whether the forecast has changed as a result. Matt Colyar joins to review the week's release of inflation data, which show stickiness in inflation prior to the $40 jump in oil prices since the start of the year. After a review of weak reports on GDP, spending and confidence, Chris and Juan Pablo discuss how the jump in oil prices and the unprecedented supply shock will affect consumer spending and growth. The group posits their forecasts for how and when the conflict may end.  Guests: Matt Colyar, Chris Lafakis and Juan Pablo Fuentes For a deeper dive on AI and the macroeconomy, see our new paper, The Macroeconomic Consequences of Artificial Intelligence, where we model four potential economic paths over the next decade. We also walk through the scenarios in a companion webinar available now on-demand. Read the paper: https://www.economy.com/getfile?q=2B555C90-1118-4A49-BDAA-5C0A99F83A9E&app=download Watch the webinar: https://bit.ly/3OF6dn9 Email us at InsideEconomics@moodys.com for more info about the Moody's Summit '26 Conference in San Diego Hosts: Mark Zandi – Chief Economist, Moody's Analytics, Cris deRitis – Deputy Chief Economist, Moody's Analytics, and Marisa DiNatale – Senior Director - Head of Global Forecasting, Moody's Analytics Follow Mark Zandi on 'X' and BlueSky @MarkZandi, Cris deRitis on LinkedIn, and Marisa DiNatale on LinkedIn Questions or Comments, please email us at helpeconomy@moodys.com. We would love to hear from you. To stay informed and follow the insights of Moody's Analytics economists, visit Economic View. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Many agency leaders run their businesses on gut instinct. While intuition is important for speed, relying on it for your year-end forecast or retention metrics is a dangerous game. If your Agency Management System (AMS) is just spitting out numbers without context, you are effectively flying blind.My guest, Todd Dailey, creator of Premium Logic, joins me to discuss how his transition from the data-rich corporate world of Liberty Mutual to the independent agency side exposed a massive gap in analytics. We break down why traditional AMS platforms fall short, the critical difference between lagging metrics (like retention) and leading metrics (like client sentiment), and how to use data to collaborate with your producers rather than punish them. If you are ready to stop guessing and start making confident, calculated decisions to scale your agency, this episode is your blueprint.▶▶ Sign Up For Your Free Discovery Callcompletegameu.com/agaCONNECT WITH ANDY NEARY

Suresh Martha, Head of Data Driven Innovation and Analytics at EMD Serono, joins The Tech Trek for a practical conversation on what leadership looks like when your team is asked to take on new technical capabilities. This episode is about extending team impact, evaluating new tools, building credibility with stakeholders, and leading through change without pretending to be the deepest expert in every domain.For data leaders, analytics managers, technology executives, and operators, this conversation gets into the real work behind capability building. Suresh breaks down how to assess whether a new technology is worth pursuing, when to start with a pilot, how to upskill internal talent, and how to hire for skills your team does not yet have.In this episode• How to evaluate whether a new tool or technology actually adds business value• Why small pilots help leaders build trust before asking for larger investment• What it takes to lead technical work you have not personally done yourself• How to hire for capabilities your team does not yet have• Why business context and data knowledge still matter as much as technical depthTimestamped highlights00:04 Extending technical impact as a leader when new capabilities land on your team03:37 A simple framework for evaluating new tools, investment, and fit05:28 Hiring for skills your team does not yet have07:44 Upskilling as a leader so you can guide the work with confidence12:06 Managing experts whose technical depth goes beyond your own15:21 Making room for learning and experimentation while still deliveringStandout lineAs long as I understand the intricacies and can explain that, that is what matters, especially for a leader.A practical takeawayStart small. Pick a real business problem. Run a focused pilot. Measure the outcome. Earn the right to scale.Follow The Tech Trek for more conversations with leaders building teams, systems, and technical capability inside modern businesses.

In this episode of Home Health Revealed, Hannah Vale sits down with Alex Hartzman, Vice President of Research & Analytics at the National Alliance for Care at Home and Head of Operations at the Research Institute for Home Care, to discuss the policy, payment, and workforce trends shaping the future of home health. They explore the ongoing pressure from Medicare reimbursement changes, the impact of value-based purchasing and quality metrics, and the growing workforce challenges affecting agencies across the country. The conversation also dives into the increasing demand for home-based care, access-to-care concerns, and why the story of home health is not always reaching policymakers the way it should. If you're a home health leader trying to prepare for the years ahead, this episode offers an inside look at the data, policy conversations, and industry realities that will define the future of care at home. Listeners interested in getting involved in advocacy efforts can learn more through the National Alliance for Care at Home Advocacy Action Center and find details about Alliance membership opportunities on their website. The Alliance DC Advocacy Fly-In will take place September 13–16, and Alliance members will receive registration information directly. Chapters (00:00:03) - Home Health Revealed(00:00:25) - Alex Hartzman on Policy Influence in Home Care(00:01:27) - Top 3 issues facing home health agencies(00:05:30) - What Can an Average Home Health Agency Do to Improve Their Quality Score(00:09:37) - Risk of rehospitalization(00:10:35) - Home Health Agency Executives on Staff turnover(00:14:15) - The value of home health(00:19:49) - Home Health and Hospice: A Conversation

WIth consumers increasingly skeptical of advertising, what's the real difference between a brand that's being genuinely helpful and one that's just being creepy? Agility requires brands to not just react to consumer behavior, but to anticipate it with smarter technology. It's about shifting from broad assumptions to a nuanced understanding of intent, especially when economic uncertainty changes the rules of engagement. Today we are here at eTail Palm Springs, and we're going to talk about the evolution of performance marketing in an era of signal loss and consumer uncertainty. As traditional methods like third-party cookies fade away, marketers need new tools and strategies that are not just incrementally better, but fundamentally different in their approach to engaging customers and driving results. To help me discuss this topic, I'd like to welcome back to the show Jaysen Gillespie, Global Head of Analytics and Product Marketing at RTB House. About Jaysen Gillespie Jaysen Gillespie is a seasoned product and analytics leader with over 15 years in Adtech and data science. As VP of Global Product Commercialization and Analytics at RTB House, he's known for translating insights into simple narratives that marketers can actually use. Whether guiding global teams or speaking on stage, Jaysen has a knack for making performance results understandable and immediately relevant. His focus is always on what drives real business outcomes, not just what looks good on a dashboard. For him, data is only powerful when it leads to smarter decisions and measurable impact. Jaysen Gillespie on LinkedIn: https://www.linkedin.com/in/jaysengillespie/ Resources RTB House: https://www.rtbhouse.com Take your personal data back with Incogni! Use code AGILE at the link below and get 60% off an annual plan: https://aglbrnd.co/r/c43e68ce5cfb321e The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://aglbrnd.co/r/2868abd8085a9703 Drive your customers to new horizons at the premier retail event of the year for Retail and Brand marketers. Learn more at CRMC 2026, June 1-3. https://aglbrnd.co/r/d15ec37a537c0d74 Enjoyed the show? Tell us more at and give us a rating so others can find the show at: https://aglbrnd.co/r/faaed112fc9887f3 Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://aglbrnd.co/r/35ded3ccfb6716ba Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company

Enterprise data estates often optimize for platform expansion over decision velocity, producing reporting layers that signal activity but fail to accelerate strategic outcomes. In this episode, Barry McCardel, CEO at Hex, examines how leading organizations can compress the gap between executive questions and decision-grade insight to materially increase the enterprise value of data. The discussion focuses on tightening feedback loops, operationalizing collaborative and AI-augmented analysis, and redefining data ROI around adoption, trust, and measurable business impact rather than production metrics. This episode is sponsored by Hex. Learn how brands work with Emerj and other Emerj Media options at emerj.com/partner. Want to share your AI adoption story with executive peers? Click emerj.com/expert for more information and to be a potential future guest on the 'AI in Business' podcast!

Film breakdown, analytics insight and fantasy football projection for Skyler Bell, a sleeper from the 2026 NFL Draft class patreon.com/rookiebigboard Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Film breakdown, analytics insight and fantasy football projection for Eli Stowers, who could be one of the most valuable rookie picks from the 2026 NFL Draft class patreon.com/rookiebigboard Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Shawn Syed, of SumerSports, joined The Drive to give the analytical breakdown of the Chiefs addition of Kenneth Walker.

This is episode 319 recorded on February 6th, 2026, where John and Jason break down the Microsoft Fabric January 2026 Feature Summary — including the Osmos acquisition for AI-ready data engineering, Git branch improvements and Python SDK support for the Fabric API, expanded OneLake security, and new Real-Time Intelligence enhancements. For show notes please visit www.bifocal.show

In this conversation, Paul Blankley and Ryan Janssen, founders of Zenlytic, drop in to discuss the massive shift in how we build software and handle data. We trace their journey from studying early NLP and Transformers at Harvard right when the BERT paper dropped, to building a company that relies on cutting-edge LLMs. As far as I know, they're the first to use LLM's for analytics.We dive deep into the reality of the agentic era: engineers are no longer writing the bulk of the code; they are managing agents, verifying outputs, and maintaining ridiculously high standards. We also explore why the industry needs to embrace "net negative scaffolding" as models get smarter, and why having good "taste" might be the ultimate human moat left in tech.Bonus: To prove that software development is changing faster than ever, we literally "vibe coded" a brand-new CRM called "Slop Force" in 20 minutes during this episode. Zenlytic: https://www.zenlytic.com/

Most people create a LinkedIn event… and never look at the data behind it.But the analytics LinkedIn now provides can completely change how you promote and grow your events.In this episode, I break down the new LinkedIn Event analytics and how you can use them to understand what's actually working.You can now see insights like:• Daily increases or decreases in registrations• How many people are visiting the event page• Your overall engagement rate• Discovery metrics like impressions and members reachedBut it goes deeper than that.LinkedIn now shows whether people who discovered your event visited your profile, along with any profile activity generated, such as new views and followers.You can also see top attendee demographics, giving you clarity on whether the right audience is accepting your invitation.This data gives you real feedback so you can adjust your messaging, targeting, and promotion strategy while the event is still live.If you're hosting LinkedIn events and not reviewing these insights, you're missing one of the most powerful optimization tools the platform provides.Don't forget to sign up for our FREE LinkedIn Content That Converts Sales Workshop here: https://www.thetimetogrow.com/LinkedInContentRoadmap

Film breakdown, analytics insight and fantasy football projection for Omar Cooper Jr., one of the fastest rising rookie picks from the 2026 NFL Draft class patreon.com/rookiebigboard Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Film breakdown, analytics insight and fantasy football projection for Bryce Lance, who is one of the hottest risers rookie picks from the 2026 NFL Draft class patreon.com/rookiebigboard Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Who would have guessed that a panel about law & insurance would electrify the attendees at ACT Research Co.?I, for one, expected it.For 40 years, ‪ACT Research Co. has brought the trucking industry together to anticipate change and chart its future. What's more, ACT Research Co. recently hosted its 74th Market Vitals: The Current & Future Health of the Industry Seminar in Columbus, IN. The event marked a special milestone of 40 years delivering commercial vehicle and freight market intelligence to the industry.On the third panel of the day, ol' Armchair Attorney® brought some sizzle. It's easy to do that when you share the stage with the likes of Thom Albrecht, Chief Revenue Officer at Reliance Partners; Anthony Johnson, President at Marvin Johnson & Associates, and the imperturbable Timothy Denoyer as our esteemed moderator. We covered insurance and litigation pressures in the freight market. But so much more! We discussed the latest issues regarding non-domiciled CDLs, nuclear verdicts, IEEPA, and motor carrier insurance.This program is brought to you by DAT Freight & Analytics. Since 1978, DAT has helped truckers & brokers discover more available loads. Whether you're heading home or looking for your next adventure, DAT is building the most trusted marketplace in freight. New users of DAT can save 10% off for the first 12 months by following the link below. Built on the latest technology, DAT One gives you control over every aspect of moving freight, so that you can run your business with speed & efficiency. This program is also brought to you by our newest sponsor, GenLogs. GenLogs is setting a new standard of care for freight intelligence. Book your demo for GenLogs today at www.genlogs.io today!

705,027 views Streamed live on Mar 2, 2026 #donbass #army of ukraine #zelensky#arestovych #shelest #war #trump #iranFundraising for a car for the 80th Airborne Assault Brigade

Voice of the Chiefs Mitch Holthus and Senior Team Reporter Matt McMullen recap their experience at the NFL Scouting Combine and look ahead to free agency, plus NFL Network's Cynthia Frelund joins the show!See omnystudio.com/listener for privacy information.

The Inside Economics team tackles the tough economic data and developments of the past week. There was nothing redeeming in the February jobs numbers, as the economy struggles to create jobs and unemployment edges higher.  And this is before the fallout from the U.S. conflict with Iran hits the economy, which threatens to be considerable. The discussion ends on the question of how the fighting will be resolved, but there are no satisfying answers. Jenna Score: 7 Guests: Dante DeAntonio, Chris Lafakis, and Juan Pablo Fuentes For a deeper dive on AI and the macroeconomy, see our new paper, The Macroeconomic Consequences of Artificial Intelligence, where we model four potential economic paths over the next decade. We also walk through the scenarios in a companion webinar available now on-demand. Read the paper: https://www.economy.com/getfile?q=2B555C90-1118-4A49-BDAA-5C0A99F83A9E&app=download Watch the webinar: https://bit.ly/3OF6dn9 Email us at InsideEconomics@moodys.com for more info about the Moody's Summit '26 Conference in San Diego Hosts: Mark Zandi – Chief Economist, Moody's Analytics, Cris deRitis – Deputy Chief Economist, Moody's Analytics, and Marisa DiNatale – Senior Director - Head of Global Forecasting, Moody's Analytics Follow Mark Zandi on 'X' and BlueSky @MarkZandi, Cris deRitis on LinkedIn, and Marisa DiNatale on LinkedIn Questions or Comments, please email us at helpeconomy@moodys.com. We would love to hear from you. To stay informed and follow the insights of Moody's Analytics economists, visit Economic View. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In Montgomery v. Caribe Transport II, argued on Wednesday, March 4, the court  considers whether a federal law initially designed to deal with state trucking regulations supersedes state common-law claims holding freight brokers liable for negligently selecting dangerous motor carriers or drivers. That may not sound particularly fascinating, but the issue before the court, which involves the scope of the Federal Aviation Administration Authorization Act of 1994, could have broad liability implications for transportation logistics and the freight broker industry.These are the oral arguments before SCOTUS. Link here to the full transcript. This program is brought to you by DAT Freight & Analytics. Since 1978, DAT has helped truckers & brokers discover more available loads. Whether you're heading home or looking for your next adventure, DAT is building the most trusted marketplace in freight. New users of DAT can save 10% off for the first 12 months by following the link below. Built on the latest technology, DAT One gives you control over every aspect of moving freight, so that you can run your business with speed & efficiency. This program is also brought to you by our newest sponsor, GenLogs. GenLogs is setting a new standard of care for freight intelligence. Book your demo for GenLogs today at www.genlogs.io today!

In this episode of Run the Numbers, CJ sits down with Superhuman's Head of Analytics Chris Byington. They break down where analytics should sit inside a company, why dashboards often fail, and how the best teams connect metrics, OKRs, and forecasting to real decisions. Chris also explains why “ship goals” can mislead teams and what CEOs and CFOs should expect from a truly decision-driving data function.—SPONSORS:Tabs is an AI-native revenue platform that unifies billing, collections, and revenue recognition for companies running usage-based or complex contracts. By bringing together ERP, CRM, and real product usage data into a single system of record, Tabs eliminates manual reconciliations and speeds up close and cash collection. Companies like Cortex, Statsig, and Cursor trust Tabs to scale revenue efficiently. Learn more at https://www.tabs.com/runAbacum is a modern FP&A platform built by former CFOs to replace slow, consultant-heavy planning tools. With self-service integrations and AI-powered workflows for forecasting, variance analysis, and scenario modeling, Abacum helps finance teams scale without becoming software admins. Trusted by teams at Strava, Replit, and JG Wentworth—learn more at https://www.abacum.aiBrex is an intelligent finance platform that combines corporate cards, built-in expense management, and AI agents to eliminate manual finance work. By automating expense reviews and reconciliations, Brex gives CFOs more time for the high-impact work that drives growth. Join 35,000+ companies like Anthropic, Coinbase, and DoorDash at https://www.brex.com/metricsMetronome is real-time billing built for modern software companies. Metronome turns raw usage events into accurate invoices, gives customers bills they actually understand, and keeps finance, product, and engineering perfectly in sync. That's why category-defining companies like OpenAI and Anthropic trust Metronome to power usage-based pricing and enterprise contracts at scale. Focus on your product — not your billing. Learn more and get started at https://www.metronome.comRightRev is an automated revenue recognition platform built for modern pricing models like usage-based pricing, bundles, and mid-cycle upgrades. RightRev lets companies scale monetization without slowing down close or compliance. For RevRec that keeps growth moving, visit https://www.rightrev.comRillet is an AI-native ERP built for modern finance teams that want to close faster without fighting legacy systems. Designed to support complex revenue recognition, multi-entity operations, and real-time reporting, Rillet helps teams achieve a true zero-day close—with some customers closing in hours, not days. If you're scaling on an ERP that wasn't built in the 90s, book a demo at https://www.rillet.com/cj—LINKS: Mostly Talent: https://mostlymetrics.typeform.com/to/cLTxtAsNChris: https://www.linkedin.com/in/chris-byington/Superhuman: https://superhuman.com/CJ: https://www.linkedin.com/in/cj-gustafson-13140948/Mostly metrics: https://www.mostlymetrics.com—RELATED EPISODES:Matt Hudson Episodehttps://youtu.be/_FWGYkzhymQ—TIMESTAMPS:0:00 Preview and intro3:29 Centralized analytics team7:29 Start analytics with problems not tools9:41 Lead with the problem10:14 Align on growth model11:46 Pre-commit to decisions13:14 Sponsors — Tabs | Abacum | Brex16:35 Dashboards need growth context19:10 Where analytics should sit21:18 Pros and cons of analytics in finance23:18 Operations vs revenue org placement24:11 Hub-and-spoke analytics model25:18 What “embedded” actually means26:14 Sponsors — Metronome | RightRev | Rillet29:38 When self-service analytics works32:04 Self-serve pitfalls33:44 Buy vs build BI35:44 Analytics owns metrics38:26 Hero metric example41:41 Outcomes > shipping42:14 Set goals before build43:57 Metrics are outcome proxies46:40 Easy way to say no48:29 Start answers with yes52:17 Proving analytics impact56:19 Credits#RunTheNumbersPodcast

You've held leadership roles across advertising, data, and now retail media. What excites you most about the journey that brought you to NielsenIQ, and how does it shape the way you approach this role?Retail media has become a critical investment area for CPGs. From your vantage point, what's next in retail media, and where do you see the biggest opportunities for innovation?As you focus on merchant analytics and collaboration, how do you see data helping to close the gap between retailers and CPGs in creating more aligned growth strategies?You've emphasized the role of automation and personalization in digital advertising. How can CPG brands deliver personalized retail media experiences at scale without sacrificing efficiency?With over 20 years in digital and advertising, what lessons have you learned about building and leading teams that can thrive in the fast-moving world of CPG and retail media?

A new study links driving behaviors to dementia risk. Dr. Chia-Ling Phuah, physician-scientist and co-director of the Barrow Neuro Analytics Center, explains the findings.

Juan and Tim rant about whats on their mind going into Gartner Data and Analytics conference: "Context" is going to be the word of the week, The Execution Gap, Decision intelligence might be the bridge and the thing nobody's talking about yet: context lock-in. See omnystudio.com/listener for privacy information.

Is 2026 the year AI finally has to prove it is worth the investment? In this episode, I'm joined by Chris Riche-Webber, VP of Business Intelligence and Analytics at SmartRecruiters, to explore why so many AI and agentic AI initiatives stall after the pilot phase and what separates the projects that scale from the ones that quietly disappear. With Gartner predicting that more than 40 percent of agentic AI programs could be cancelled by 2027, Chris brings a pragmatic, data-led perspective on what is really happening inside organizations as the hype meets operational reality. We talk about the fundamentals that have not changed despite the new technology. Influence, clearly defined problems, measurable impact, and adoption still determine success, yet they are often overlooked in the rush to deploy the latest tools. Chris explains why "good vibes" are no longer enough in front of a CFO, how to baseline outcomes properly, and why ownership of results is one of the most common missing pieces in enterprise AI programs. A big part of the conversation focuses on what Chris calls the "agent washing" problem. Just as products are sometimes marketed with fashionable labels that do not reflect their real value, many solutions are being positioned as agentic without delivering true autonomy or business outcomes. We discuss how leaders can cut through the noise by asking better questions, aligning technology to specific use cases, and recognizing when simple automation is the right answer. Trust, adoption, and measurable ROI emerge as the three signals that determine whether an AI initiative survives. Chris shares a clear framework for defining these signals in a way that is consistent, comparable over time, and meaningful to the executive team. We also explore how connecting talent decisions to revenue, productivity, and retention changes the conversation, especially in the context of SmartRecruiters' broader SAP ecosystem and the opportunity to link people data directly to business performance. This is a conversation about moving from experimentation to accountability, from buying narratives to solving real problems, and from technology-first thinking to outcome-first leadership. So as the window for easy wins closes and the demand for proof of value grows, will your AI strategy be remembered as a pilot that generated excitement or as an initiative that delivered measurable business impact?

Theo Epstein, Senior Advisor and part owner of Fenway Sports Group and former executive with the Boston Red Sox and Chicago Cubs, explains how integrating analytics with scouting built championship organizations, how reforms like the pitch timer reshaped the pace of play, and how Major League Baseball can reenergize its national appeal. Hosted on Acast. See acast.com/privacy for more information.

The case asks whether the Federal Aviation Administration Authorization Act of 1994 (FAAAA) preempts state negligence claims against freight brokers for carelessly selecting unsafe motor carriers or drivers. The crash happened December 7, 2017, on Interstate 70 in Illinois. Missouri truck driver Shawn Montgomery had pulled his 2015 Mack truck onto the shoulder for mechanical repairs. While standing outside, he was struck from behind by a speeding 1995 Freightliner tractor-trailer driven by Yosniel Varela-Mojena. Montgomery lost his leg and suffered permanent disfigurement.Varela-Mojena worked for Indiana-based Caribe Transport II, which owned the tractor. The trailer was leased from a related Florida company. Freight broker C.H. Robinson arranged the shipment of plastic pots from Ohio to Arkansas and Texas under a contract with Caribe II. Montgomery sued under state law, claiming negligence against the driver, the carriers, and Robinson for negligent hiring. Robinson argued the FAAAA's Section 14501(c)(1) preempts the claims because they relate to a broker's “price, route, or service” in transporting property. The district court said the claims related to broker services but fit the safety exception in Section 14501(c)(2)(A), which preserves state “safety regulatory authority… with respect to motor vehicles.” The 7th Circuit held that negligent-hiring claims against brokers are preempted. Montgomery argues to the Supreme Court that his claims are not preempted. He says the FAAAA targets economic regulations, not safety-based torts. The safety exception protects states' traditional authority over motor vehicles, and requiring brokers to use reasonable care when hiring carriers falls within that power. He warns broad preemption could leave victims without remedies and encourage brokers to choose risky carriers for profit.Robinson and the other respondents reply that state tort claims like negligent hiring are expressly preempted by the statute's plain text. The safety exception applies only to rules with a “direct connection” to motor vehicles. Brokers do not own or operate vehicles, so states lack authority to impose personal injury liability on them. Policy concerns cannot override the law's wording. The U.S. government filed a brief supporting the respondents, arguing the text requires a direct link to vehicles, and a broker's duty to select carriers carefully does not qualify. The government reversed its prior position after new review and court developments.The outcome is hard to predict, especially with the government's shift. Oral argument will likely feature questions about what counts as a “direct connection” to motor vehicles.This program is brought to you by DAT Freight & Analytics. Since 1978, DAT has helped truckers & brokers discover more available loads. Whether you're heading home or looking for your next adventure, DAT is building the most trusted marketplace in freight. New users of DAT can save 10% off for the first 12 months by following the link below. Built on the latest technology, DAT One gives you control over every aspect of moving freight, so that you can run your business with speed & efficiency. This program is also brought to you by our newest sponsor, GenLogs. GenLogs is setting a new standard of care for freight intelligence. Book your demo for GenLogs today at www.genlogs.io today!

How do you bring innovation to life inside an organization whose job is to help other people see risk before it shows up on a balance sheet? In this episode of the Innovation Storytellers Show, I sit down with Jason Lee, Chief Intelligence Officer at Moody's Analytics, for a conversation that lives at the crossroads of national security tradecraft, financial crime investigation, and modern data-driven decision making. Jason has spent decades inside large, complex systems, from federal intelligence work to investment banking to building a security consulting firm, and he shares what he has learned about creating new programs inside environments where bureaucracy, budgets, and skepticism can slow even the best ideas down. We start with Jason's origin story because he makes a compelling point: innovation rarely comes from a formal job description. In his career, it often showed up as a "collateral duty," a leader asking him to solve a pain point, build a new unit, or design a process when the rules had not yet been written. From creating early fraud detection frameworks in banking to uncovering unconventional data sources in government work, Jason frames innovation as a mix of creativity, relationship-building, and a willingness to learn from other industries without copying them. From there, we get into how Moody's is thinking about AI right now, especially the shift from large language models toward large reasoning models. Jason explains why reasoning matters more than hype when the stakes include fraud, terrorism financing, and organized crime. He walks through what it means to use models for scenario analysis, how "tipping and cueing" can help analysts focus on what matters, and why he believes humans have to stay in the loop, especially when errors can have real-world consequences. One of my favorite parts of the conversation is when Jason brings storytelling back into the center of analytics. He explains how workshops with prospects help uncover what clients actually need, even when they cannot fully articulate it yet, and why "data experience" matters when the information is complex and intangible. We also talk candidly about where innovation programs can stall, whether it is budget politics, unrealistic KPIs, mismatched expectations across business verticals, or leaders who want short-term wins when the real value takes years to compound. If you are building inside a big organization, selling complex ideas to busy decision-makers, or trying to make AI useful without losing trust, this episode will give you a lot to think about, so what part of Jason's approach resonates most with how you see innovation playing out right now, and where do you think teams are still getting stuck?  

This is episode 318 recorded on February 6th, 2026, where John and Jason break down the Power BI January 2026 Feature Update — covering the key report, model, and service changes, what's actually impactful, and how it fits into the broader Microsoft Fabric roadmap. For show notes please visit www.bifocal.show

Unlock the secrets of product-driven growth with software tools and analytics in this insightful episode featuring Kuber Jain, Head of Analytics at Headspace. Discover how the latest software tools shape user engagement and retention in the health tech industry. If you're building or scaling an app, this episode empowers you to leverage analytics as your most valuable asset and avoid the costly pitfalls of intuition-based decisions.Connect with Kuber on LinkedIn and hit listen now to unlock your app's growth potential with smart software tools and analytics!

This week on Bet the Process, the No-Stats All-Star Shane Battier joins to discuss his journey from being a traditional scoring-focused player to embracing analytics in his NBA career, how basketball analytics has evolved over the years, and his transition to business as chief culture advisor for Palmetto Solar.

00:00 Four-Minute Offense 8:00 Great Weekend 23:30 Doug's Big One biggie-sized by Wendy's = The Pressure on Monti 58:20 The Analytics are Wrong! 1:05:12 UofA vs KU 1:16:47 ASU vs Utah 1:26:53 A Show of Class 1:33:40 Vs Vegas 1:42:00 Tony Gemignani

In this episode, host Sandy Vance chats with Hari Bala, the Chief Technology Officer for Health Information Systems at Solventum. Together, they explore how healthcare organizations can build trust and confidence around AI adoption, drawing on insights from Solventum's recent global survey of healthcare professionals. The research highlights a growing demand for AI alongside concerns that innovation could increase pressure on clinicians. Hari shares practical perspectives on how AI can support rather than overshadow providers, improve efficiency without compromising quality, and help organizations introduce new technologies in ways that feel safe and sustainable. Listen to learn how leaders can ensure clinicians feel comfortable incorporating AI into their daily workflows while improving the overall patient experience. In this episode, they talk about: The three key trust factors and why trust is the foundation for AI adoption Why trust is the currency of successful implementation The role of AI in improving patient care and clinician efficiency How speed and quality can improve together rather than compete Key findings from Solventum's healthcare AI adoption survey The cultural and mindset shifts required for successful implementation The impact of AI on the patient experience How leaders can evaluate potential technology partners A Little About Hari: Hari Bala joined Solventum as Chief Technology Officer for Health Information Systems in May 2025. He brings more than 25 years of experience building scalable, distributed systems using generative AI, data science, analytics, and machine learning across healthcare, cloud, and security. Before Solventum, Hari led AI, data, analytics, and cloud transformation initiatives at GE Healthcare and Oracle Cerner. At Oracle, he helped establish the AI Services organization and led development of the Health Data Intelligence and Analytics platform, a near real-time, cloud-based population health solution, while advancing AI and machine learning tools for clinical use. Earlier in his career, Hari spent nearly 19 years at Microsoft in leadership roles across Azure and several core enterprise technologies.

560,296 views Streamed live on Feb 23, 2026 #arestovych #rustle #war#arestovych #rustle #war #zelensky #trump

Matt Harmon of Yahoo Sports and Reception Perception joins Thor to preview and share his knowledge at the NFL Combine, discussing the WR group testing set to happen on Saturday, his info on the prospect group and so much more! Then co-founder and CEO of Reel Analytics joins the show to talk about in-game athleticism score and how it's measured, how to use that to evaluate atheletes, and exude his own knowledge on the crop of players at the combine!See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Mark, Cris & Marisa reunite for a lively discussion about their predictions around AI's impact on the economy over the next year or two. The team talks about their recently released webinar & white paper on the Macroeconomic Consequences of AI and answers several great listener questions in the process. Marisa and Cris try to talk Mark down off the AI-apocalypse ledge, as the once eternally optimistic Zandi has gone down a darker path recently.  Jenna Score: 8.5/10 For a deeper dive on AI and the macroeconomy, see our new paper, The Macroeconomic Consequences of Artificial Intelligence, where we model four potential economic paths over the next decade. We also walk through the scenarios in a companion webinar available now on-demand. Read the paper: https://www.economy.com/getfile?q=2B555C90-1118-4A49-BDAA-5C0A99F83A9E&app=download Watch the webinar: https://bit.ly/3OF6dn9 Read the Citrini Research Scenario on AI here: https://www.citriniresearch.com/p/2028gic Email us for more info about the Moody's '26 Summit in San Diego Hosts: Mark Zandi – Chief Economist, Moody's Analytics, Cris deRitis – Deputy Chief Economist, Moody's Analytics, and Marisa DiNatale – Senior Director - Head of Global Forecasting, Moody's Analytics Follow Mark Zandi on 'X' and BlueSky @MarkZandi, Cris deRitis on LinkedIn, and Marisa DiNatale on LinkedIn Questions or Comments, please email us at helpeconomy@moodys.com. We would love to hear from you. To stay informed and follow the insights of Moody's Analytics economists, visit Economic View. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

BEST OF: Step into the Conspiracy Finals as we dissect the most polarizing NBA rigged theory: magnets in the basketball. We investigate the "impossible" shots and viral "magnet proof" videos, revealing how a decade-old NBA parody commercial became the blueprint for modern basketball conspiracy theories. From Kawhi Leonard's iconic Game 7 bounce to the physics of LeBron James and Kobe Bryant's record-breaking misses, we challenge the narrative that the league is a scripted sports production like the NFL. We also tackle the "magnet toggle" claims surrounding stars like Caitlin Clark and Angel Reese, analyzing if these bizarre rim-hangers are a secret scheme or just the statistical certainty of 200,000 shots per season. Discover the truth behind the magnetized rimmyth and why the internet is obsessed with "glitches in the matrix" on the hardwood.*The is the FREE archive, which includes advertisements. If you want an ad-free experience, you can subscribe below underneath the show description.

I am Rolf Claessen and together with my co-host Ken Suzan I welcome you to Episode 172 of our podcast IP Fridays. Today's interview guests are Co-Founder & CEO of Inception Point AI, Jeanine Whright, and Mark Stignani, who is Partner & Chair of Analytics Practice at Barnes & Thornburg LLP. https://www.linkedin.com/in/jeaninepercivalwright https://www.linkedin.com/in/markstignani Inception Point AI But before the interview I have news for you: The Unified Patent Court (UPC) ruled on Feb 19, 2026, that specialized insurance can cover security for legal costs. This is vital for firms, as it eases litigation financing and lowers financial hurdles for patent lawsuits by removing the need for high liquid assets to enforce rights at the UPC. On Feb 12, 2026, the WIPO Coordination Committee nominated Daren Tang for a second six-year term as Director General. Tang continues modernizing the global IP system, focusing on SMEs, women, and digital transformation. His confirmation in April is considered certain. An AAFA study from Feb 4 reveals 41% of tested fakes (clothing/shoes) failed safety standards. Many contained toxic chemicals like phthalates, BPA, or lead. The study highlights that counterfeiters increasingly use Meta platforms to sell unsafe imitations directly to consumers. China's CNIPA 2026 report announced a crackdown on bad-faith patent and trademark filings. Beyond better examination quality, the agency will sanction shady IP firms and stop strategies violating “good faith” to make China’s IP system more ethical and innovation-friendly. Now, let's hear the interview with Jeanine Whright and Mark Stignani! How AI Is Rewiring Media & Entertainment: Key Takeaways from Ken Suzan's Conversation with Jeanine Wright and Mark Stignani In this IP Fridays interview, Ken Suzan speaks with two repeat guests who look at the same phenomenon from two angles: Jeanine Wright, Co-Founder & CEO of Inception Point AI, as a builder of AI-native entertainment, and Mark Stignani, Partner and Chair of the Analytics Practice at Barnes & Thornburg LLP, as a lawyer advising clients who are trying to use AI without stepping into a legal (or ethical) crater. What emerges is a clear picture: generative AI is not just “another tool.” It is rapidly becoming the default infrastructure for creative work—while the rules around ownership, consent, and accountability lag behind. 1) What “AI-generated personalities” really are (and why that matters) Jeanine's company is not primarily “cloning” real people. Instead, Inception Point AI creates original, fictional personalities—characters with backstories, ambitions, and evolving arcs—then deploys them into the world as podcast hosts and content creators (and eventually actors and musicians). Her key point: the creative work still starts with humans. Writers and creators define the concept, tone, audience, and story engine. What AI changes is speed, cost, and iteration—and therefore what is economically feasible to produce. 2) The “generative content pipeline” isn't a magic button A recurring misconception Ken raises is the idea that someone “pushes a button” and content pops out. Jeanine explains that real production looks more like a hybrid studio: A creative team defines character, voice, format, and storyline. A technical team builds what she calls an “AI orchestration layer” that combines multiple models and tools. The “stack” differs by format: the workflow for a long-form audio drama is different from a short-form beauty clip. This matters because it reframes AI content not as a single output, but as a pipeline decision: which tools, which data sources, which QA, and which governance steps are used—and where human review happens. 3) The biggest legal questions: origin, liability, ownership, and contracts Mark doesn't name a single “top issue.” He describes a cluster of problems that repeatedly show up in client conversations: Training data and “origin story” Clients keep asking: Can I legally use AI output if the tool was trained on copyrighted works? Even if the output looks new, the unease is about whether the tool's capabilities are built on unlicensed inputs. Liability for unintended harm Mark flags risk from AI content that inadvertently infringes, defames, or carries bias. The legal exposure may not match the creator's intent. Ownership and protectability He points to a big gap: many jurisdictions are still reluctant to grant classic IP rights (copyright or patent-style protection) to purely AI-generated material. That creates uncertainty around whether businesses can truly “own” what they produce. Old contracts weren't written for AI A final, practical point: many agreements—talent contracts, author clauses, data licenses—predate generative AI and simply don't address it. That leads to disputes about scope, permissions, and—crucially—indemnities. 4) Are we at a tipping point? The “gold rush” vs. “next creative era” views Jeanine frames AI as “the world's most powerful creative tool”—comparable to previous step-changes like animation, special effects, and CGI. For her, the strategic implication is simple: creators who learn to use AI well will expand what they can build and test, faster than ever. Mark's metaphor is more cautionary: he calls the moment a “gold rush” where technology is sprinting ahead of law. Courts are getting flooded with foundational disputes, while legislation is fragmented—he notes that states may move faster than federal frameworks, and that labor agreements (e.g., union protections) will be a key pressure point. 5) Democratization: more creators, more niche content, more experimentation One of the most concrete themes is access. Jeanine argues AI will: Lower production barriers for independent filmmakers and storytellers. Reduce the need for “hit-making only” economics that dominate Hollywood. Make micro-audience content commercially viable. Her example is intentionally niche: highly localized, specialized content (like a “pollen report” for many markets) that would never have made financial sense before can now exist—and thrive—because the production cost drops and personalization scales. 6) Likeness, consent, and “digital performers”: what happens when AI resembles a real actor? Ken pushes into a sensitive area: what if someone generates a performance that closely resembles a living actor without consent? Mark outlines the current (imperfect) toolbox—because, as he emphasizes, most laws weren't built for this scenario. He points to practical claims that may come into play in the U.S., such as rights of publicity and false endorsement-type theories, and notes that whether something is parody or “too close” can become a major fault line. Jeanine explains her company's operational approach: They focus on original personalities, designed “from scratch.” They build internal checks to avoid misappropriating known names, likenesses, or recognizable identities. If they ever work with real people, the model would be licensing their likeness/voice. A subtle but important business point also appears here: Jeanine expects AI-native characters themselves to become licensable assets—meaning the entertainment economy may expand to include “celebrity rights” for fully synthetic personalities. 7) Ethics: the real line is “deception,” not “AI vs. human” The ethical core of the conversation is not “AI is bad” or “AI is good.” It's how AI is used—especially whether audiences are misled. Mark highlights several ethical risks: Misuse of tools to manipulate faces and content (“AI slop” and political misuse). Displacement of creative workers without adequate transition support. A concern that AI often optimizes toward “statistical averages,” potentially flattening originality. Jeanine agrees ethics must be designed into the system. She describes regular discussions with an ethicist and emphasizes a principle: transparency. Her company discloses when content or personalities are AI-generated. She argues that if people understand what they're engaging with and choose it knowingly, the ethical problem shifts from “AI exists” to “Are we tricking people?” Mark adds a real-world warning: deepfakes are now credible enough to enable serious fraud—he references a case-like scenario where a synthetic video meeting deceived an employee into authorizing a payment. The point is clear: authenticity and verification are no longer optional. 8) The “dead actor” hypothetical: legal permission vs. moral intent Ken raises a provocative scenario: an actor's estate authorizes an AI-generated new performance, but the actor opposed such technology while alive. Neither guest offers a simplistic answer. Jeanine suggests that even if the estate holds legal rights, a company might choose to avoid such content out of respect and because the ethical “overhang” could damage the storytelling outcome. She also notes the harder question: people who died before today's capabilities may never have been able to meaningfully consent to what AI can now do—raising questions about how we interpret legacy intent. Mark underscores the practical contract problem: many rights are drafted “in perpetuity,” but that doesn't automatically settle the ethical question. 9) Five-year forecast: “AI everywhere,” but audiences may stratify Ken closes with a prediction question: in five years, how much entertainment content will significantly involve AI—and will audiences care? Jeanine predicts AI becomes the default creative layer for most content creation. Mark is slightly more conservative on the percentage, but adds an important nuance: the market will likely stratify. Low-cost, high-volume content may become saturated with AI, while premium segments may emphasize “human-made” as a differentiator—especially if disclosure norms become standard. Bottom line for business leaders and creators This interview lands on a pragmatic conclusion: AI will change how content is made at scale, and the competitive edge will go to teams that combine creative taste, operational discipline, and legal/ethical governance. If you're building, commissioning, or distributing content, the questions you can't dodge anymore are: What's the provenance of the tools and data you rely on? Who is responsible when output harms, infringes, or misleads? What rights can you actually claim in AI-assisted work? Do your contracts and disclosures match the new reality? Ken Suzan: Thank you, Rolf. We have two returning guests to the IP Friday’s podcast. Joining me today is Janine Wright and Mark Stignani. Our topic for discussion, how is AI transforming the media and entertainment industries today? We look at the issues from differing perspectives. A bit about our guests, Janine Wright is a seasoned board member, CEO, global COO and CFO. She’s led organizations from startup to a $475 million plus revenue subsidiary of a public company. She excels in growth strategy, adopting innovative technologies, scaling operations and financial management. Janine is a media and entertainment attorney and trial litigator turned technologist and qualified financial expert. She is the co-founder and CEO of Inception Point AI, a growing company that is paving new ground with AI-generated personalities and content through developing technology and story. Mark Stignani is a partner with Barnes & Thornburg LLP and is based in Minneapolis, Minnesota. He is the chair of the data analytics department with a particular emphasis on artificial intelligence, machine learning, cryptocurrency and ESG. Mark combines the power of artificial intelligence and machine learning with his skills as a corporate and IP counsel to deliver unparalleled insights and strategies to his clients. Welcome, Janine and Mark to the IP Friday’s podcast. Jeanine Whright: Thank you. Thank you. Thank you so much for having me and fun to be back. It feels nostalgic to be here. Ken Suzan: That’s right. And you both were on the program. So it’s fantastic that you’re both back again. So our format, I’m going to ask a question to Janine and or Mark and sometimes to both of you. So that’s going to be how we proceed. Let’s jump right in. Janine, your company creates AI-generated actors. For listeners who may not be familiar, can you briefly explain what that means and what’s now possible that wasn’t even two years ago? Jeanine Whright: Sure. Yeah, we are creating AI-generated personalities. So new characters, new personalities from scratch. We design who these personalities are and will be, how they will evolve. So we give them complex backstories. We give them hopes and dreams and aspirations. We every aspect of them, their families, how they’re going to evolve. And in the same way that, say, you know, Disney designs the character for its next animated feature or, you know, an electronic arts designs a character for its next major video game. We are doing that for these personalities and then we are launching them into the world as podcast hosts, content creators on social platforms like YouTube, Instagram and TikTok. And even in the future, you know, actors in feature length films, musicians, etc. Ken Suzan: Very fascinating. Mark, from your practice, what’s the single biggest legal question or dispute you’re seeing clients wrestle with when it comes to AI and media creation? Mark Stignani: Well, I think that, you know, it’s not just one thing, it’s like four things. But most of them tend to be kind of the origin story of AI data or AI tools that they use because, you know, but for the use of AI tools trained on copyrighted materials, the tools wouldn’t really exist in their current form. So a lot of my clients are wondering about, you know, can I legally use this output if it’s built upon somebody else’s IP? The second ask, the second flavor of that is really, is there liability being created if I take AI content that inadvertently infringes or defames or biases there? So there’s the whole notion of training bias from the training materials that comes out. The third phase is really, you know, can I really own this? Because much of the world does not really give IP rights into AI-generated inventions, copyrighted materials. It’s still kind of a big razor. Then at the end of the day, you know, if it’s an existing relationship, does my contract even contemplate this? So everything from authors contracts on up to just use of data rights that predate AI. Ken Suzan: And Janine and Mark, a question to both of you. How would you describe where we are right now in the AI revolution in media and entertainment? Are we approaching a tipping point? And if so, what are the things we need to watch for? Jeanine Whright: Yeah, I definitely think that we’re at a phase where people are starting to come to the realization that AI is the world’s most powerful creative tool. But that, you know, storytelling and point of view is what creates demand and audiences. And AI doesn’t threaten or change that. But it does mean that as people evolve in this medium, they’re very likely going to need to adopt, utilize and figure out how to hone their craft with these AI-generated content and these AI-generated toolings. So this is, you know, something that people have done certainly in the past in all sorts of ways in using new tools. And we’ve seen that make a significant change in the industry. So you look at, you know, the dawn of animation as a medium. You look at use of special effects, computer-generated imagery in the likes of Pixar. And this is certainly the next phase of that evolution. But because of the power of the tool and what will become the ubiquity of the tool, I think that it’s pretty revolutionary and all the more necessary for people to figure out how to embrace this as part of their creative process. Ken Suzan: Thank you, Janine. Mark, your thoughts? Mark Stignani: Yeah, I mean, I liken this to historically to like the California gold rush right now, because, you know, the technology is so far outpaced in any of the legal frameworks that are available. And so we’re just trying to shoehorn things in left and right here. So, I mean, the courts are beginning to start to engage with the foundational questions. I don’t think they’re quite there yet. I just noticed Anthropic got sued again by another group of people, big music group, because of the downloaded works they’ve done. I mean, so the courts are, you know, the courts are certainly inundated with, you know, too many of these foundational questions. Legislatively, hard to tell. I mean, federal law, the federal government is not moving uniformly on this other than to let the gold rush continue without much check and balance to it. Whereas states are now probably moving a lot faster. Colorado, Illinois, even Minnesota is attempting to craft legislation and limitations on what you can do with content and where to go with it. So, I mean, the things we need to watch for any of the fair use decisions coming out here, you know, some of the SAG-AFTRA contract clauses. And, you know, again, the federal government, I just, you know, I got a big shrug going as to what they’re actually going to come up with here in the next 90 to 100 days. So, but, you know, I think they’ll be forced into doing something sooner than later. Ken Suzan: Okay, let’s jump into the topic of the rise of generative content pipelines. My first question to Janine. Studios and production companies are now building what some call generative content pipelines. This is where AI systems produce everything from scripts to visual effects to voice performances. What efficiencies and creative possibilities does this unlock for the industry? Jeanine Whright: Yeah, so this is quite a bit of what we do. And if I could help pull the curtain back and explain a little bit. Ken Suzan: That’d be great. Jeanine Whright: Yeah, there’s this assumption that, you know, somebody is just sitting behind a machine pushing a button and an out pops, you know, what it is that we’re producing. There’s actually quite a bit of humans still in the loop in the process. You know, we have my team as creators. The other half of my team is the technologists. And those creators are working largely at what we describe as the the tip of the sphere. So they’re, of course, coming up with the concepts of who are these personalities? What are these personalities, characters, backgrounds going to be a lot of like rich personality development? And then they’re creating like what are the formats? What are the kind of story arcs? What is the kinds of content that this this character wants to tell? And what are the audiences they’re desiring to reach and what’s most going to resonate with them? And then what we built internally is what we refer to as an AI orchestration layer. So that allows us to pull from basically all of the different models and then all of these different really cool AI tools. And put those together in such a way and combine those in such a way that we can have the kind of output that our creative team envisions for what they want it to be. And at the end of the day, what you what the stack looks like for, say, a long form audio drama, like the combination of LLMs that we’re going to use in different parts of scripting and production and, you know, ideating and all of that. And the kinds of tooling that we use to actually make it and get it to sound good and have the kinds of personality characteristics that we want to be in an authentic voice for a podcast is going to be different than the tech stack and the tool stack that we might use for a short form Instagram beauty tip reel. And so there’s a lot of art in being able to pull all of these tools together to get them to do exactly what you want them to do. But I think the second part of your question is just as interesting as the first. I mean, what is what possibilities is this unlocking? So of course you’re finding efficiencies in the creative production process. You can move faster. You can do things were less expensive, perhaps, and you were able to do it before. But on the creator side, I think one thing that hasn’t been talked about enough is how it is really like blown wide the aperture of what creators can do and can envision. Traditionally, you know, Hollywood podcasting, many of these businesses that become big businesses have become hit making businesses where they need to focus on a very narrow of wide gen pop content that they think is going to get tens of millions, hundreds of millions in, you know, fans and dollars in revenue for every piece of content that they make. So the problem with that is, is that it really narrows the kinds of things that ultimately get made, which is why you see things happening in Hollywood, like the Blacklist, which is, you know, this famous list of really exceptional content that remains unpredited, unproduced, or why you see things like, you know, 70 to 80% of the top 100 movies being based on pre-existing IP, right? Because these are such huge bets that you need to feel very confident that you’re going to be able to get big, big audiences and big, big dollars from it. But with AI, and really lowering the barrier to entry, lowering the costs of production and marketing, the experimentation that you can do is really, really phenomenal. So, you know, my creative team, if they have an idea, they make it, you know, they don’t have to wring their hands through like a green lighting process of, you know, should we, shouldn’t we, like we, we can make an experiment with lots of different things, we can do various different versions of something. We can see what would this look like if I placed it in the 1800s, or what if I gave this character an Australian accent, and it’s just the power of being able to have this creative partner that can ideate with you and experiment with you at rocket speed. With the creators that are embracing it, you can see how it is really fun for them to be able to have this wide of a range of possibility. Ken Suzan: Mark, when you hear about these generative pipelines, what are the immediate red flags or concerns that come to mind from a legal standpoint? How about ethics underlying all of this? Well, Mark Stignani: that was not, that’s the number one red flag because I mean, we are seeing not just that in the entertainment industry, but it literally at political levels, and the kind of the phrase, to turn the phrase AI slop being generated, we’re seeing, you know, people’s facial expressions altered. In some cases, we’re seeing AI tools being misused to exploit various groups of individuals and genders and age groups. So I mean, there’s a whole lot of things ethically that people are using AI for that just don’t quite cover it. Especially in the entertainment industry, I mean, we’re looking at a fair amount of displacement of human workers without adequate transition support, devaluation of the creative labor. I mean, the thing though that I’m always from a technical standpoint is AI is simply a statistical average of most everything. So it kind of devalues the benefit of having a human creator, a human contribution to it. That’s the ethical side. But on the legal side, I see chain of title issues. I mean, because these are built on very questionable IP ownership stages, I mean, in most of these tools, there has been some large copying, training and taking of copyrighted materials. Is it transformational? Maybe. But there’s certainly not a chain of title, nor is there permission granted for that training. I mentioned SAG-AFTRA earlier, I think there’s a potential set of union contract aspects to this that if you know many of these agreements and use sub-licenses for authors and actor agreements, they weren’t written with AI in mind. So that’s another red flag. And also I just think in indemnification. So if we ultimately get to a point where groups are liable for using content without previous license, then who’s liable? Is the tool maker the liable group or the actual end user? So those are probably my top four red flags. But I think ethics is probably my biggest place because just because we can do something from an ethical standpoint doesn’t mean we should. Jeanine Wright: Yeah, if I can respond to both of those points. I mean, one from a legal perspective, just to be very clear, I mean, we are always pulling from multiple different models and always pulling from multiple different sources. And we even have data sources that we license or use for single source of truth on certain pieces of information. So we’re always pulling things together from multiple different sources. We also have built into our process, you know, internal QAing and checking to make sure that we’re not misappropriating the name or likeness of any existing known personality or character. We are creating original personalities there. We design their voice from scratch. We design their look from scratch. So we’re not on our personality side, we’re not pulling or even taking inspiration from existing intellectual property that’s already out there in creating these personalities. On the ethical side, I agree. I mean, when we came out of stealth, we came out of stealth in September. There was certainly quite a bit of backlash from folks in my—I previously co-founded a company in the audio space. I mean, there’s been many rounds of layoffs in audio and in many other parts of the entertainment industry. So I’m very sensitive to the feedback around, like, is this job displacement? I mean, I do think that the CEO of NVIDIA said it right when he said, you’re likely not going to lose your job to AI, but you will lose your job to somebody who knows how to use AI. I think these tools are transforming the way that content is made and that the faster that people can embrace this tooling, the more likely they’re going to be having the kinds of roles that they want in, you know, in content creation and storytelling in the future. And we are hiring. I’m hiring AI video creators, AI audio creators. I’m hiring AI developers. So people who are looking for those roles, I mean, please reach out to me, we would love to work with you and we’d love to grow with you. We also take the ethics very seriously. For the last few months or so, I’ve met regularly with an ethicist, we talk about all sorts of issues around, you know, is designing AI-generated people, you know, good for humanity? And what about authenticity and transparency and deception, and how are we in building in this space going to avoid some of the problems that we’ve seen with things like social media and other forms of technology? So we keep that very top of mind and we try to build on our own internal values-based system and, you know, continue to elevate and include the humanity as part of the conversation. Ken Suzan: Thank you, Janine. Janine, some argue that AI content pipelines will level the field for filmmaking, giving independent creators access to tools that were once available only to major studios. Is that the future you envision? Jeanine Wright: I do think that with AI you will see an incredible democratization of access to technology and access to these capabilities. So I do think, you know, rise of independent filmmakers, you won’t have as many people who are sitting on a brilliant idea for the next fantastic script or movie that just cannot get it made because they will be able to with these tools, get something made and out there, at least to get the attention of somebody who could then decide that they want to invest in it at a studio kind of level in the future. The other thing that I think is really interesting is that I think, you know, AI will empower more niche content and more creators who can thrive in micro-communities. So it used to be because of this hit generation business model, everything needed to be made for the masses and a lot of content for niche audiences and micro-communities was neglected because there was just no way to make that content commercially viable. But now, if you can leverage AI—we make a pollen report podcast in 300 markets, you know, nobody would have ever made that before, but it is very valuable information, a very valuable piece of content for people who really care about the pollen in their local community. So there’s all sorts of ways that being able to leverage AI is making it more accessible both to the creator and to the audience that is looking for content that truly resonates with them. Ken Suzan: Mark, let’s talk about the legal landscape right now. If someone creates an AI-generated performance that closely resembles a living actor without their consent, what legal recourse does that actor have? Mark Stignani: Well, I mean, I think we can go back to the OpenAI Scarlett Johansson thing where, you know, if it’s simply—well, the “walks like a duck, quacks like a duck” type of aspect there. You know, I think it’s pretty straightforward that they need to walk it back. I mean, the US doesn’t have moral rights, really, but there’s a public visage right, if you will. And so, one of the things that I find predominantly useful here is that these actors likely have rights of publicity there, we probably have a Lanham Act false endorsement claim, and you know, again, if the performance is not parody, and it’s so close to the original performance, we probably have a copyright discussion. But again, all of these laws predate the use of AI, so we’re going to probably see new sets of law. I mean, we’re probably going to see “resurrection” frameworks, we’ll probably have frameworks for synthetic actors and likenesses, but the rules just aren’t there yet. So, unfortunately, your question is largely predictive versus well-settled at this point. Ken Suzan: Janine, your company works with AI actors. How do you navigate the questions of consent and likeness compensation when creating digital performers? Jeanine Wright: I mean, if we—so first of all, if we were to work with a person who is an existing real-life person or was an existing real-life person, then we would work with them to license their name and likeness or their voice or whatever aspects of it we were going to use in creating content in partnership with them. Not typically our business model; we are, as I said, designing all of our personalities from scratch and making all of our content originally. So, we’ve not had to do that historically. Now, you know, the flip side is: can I license my characters as if they’re similar to living characters? Like will I be able to license the name and likeness and voice of my AI-generated personalities? I think the answer is yes and we’re already starting to do that. Ken Suzan: Let’s just switch gears into ethics and AI because I find this to be a really fascinating issue. I want to look at a hypothetical. And this is to both of you, Janine and Mark: an AI system creates a new performance by a beloved actor who passed away decades ago, and the actor’s estate authorizes it, but the actor was known to have expressed opposition to such technology during their lifetime. Is this ethical? Jeanine Wright: This feels like a Gifts, Wills, and Trusts exam question. Ken Suzan: It sounds like it, that’s right. Jeanine Wright: Throwing me back to my law school days. Exactly. What are your thoughts? It’d be interesting to see like who has the rights there. I mean, I think if you have the legal rights, the question is around, you know, is it ethical to go against what you knew was somebody’s wishes at the time? I guess the honest answer is I don’t know. It would depend a lot on the circumstances of the case. I mean, if we were faced with a situation like that where there was a discrepancy, we would probably move away from doing that content out of respect for the deceased and out of a feeling that, you know, if this person felt strongly against it, then it would be less likely that you could make that storytelling exceptional in some way—it would color it in a way that you wouldn’t want in the outcome. And I feel like there’s—I mean, certainly going forward and it’s already happening—there are plenty of people I think who have name, likeness, and voice rights that they are ready to license that wouldn’t have this overhang. Ken Suzan: Mark, your thoughts? Mark Stignani: Yeah, I mean, again, I have to kind of go back to our property law—the Rule Against Perpetuities. You know, from a property standpoint to AI rights and likenesses—since most of the digital replica contracts that I’ve reviewed generally do talk about things in perpetuity. But if it’s not written down for that actor and the estate is doing this—is it ethical? You know, that is the debate. Jeanine Wright: Well, gold star to you, Mark, for bringing up the Rule Against Perpetuities. There’s another one that I haven’t heard for many years. This is really taking me back to my law school days. Ken Suzan: It’s a throwback. Jeanine Wright: The other thing that’s really interesting is that this technology is really so revolutionary and new that it’s hard to even contemplate now what it is going to be in a decade, much less for people who have passed away to have contemplated what the potential for it could be today. So you could have somebody who is, perhaps, a deceased musician who expressed concerns about digital representations of themselves or digital music while they were alive. But now, the possibility is that you could recreate—certainly I could use my technology to recreate—that musician from scratch in a very detailed way, trained on tons of different available data. Not just like a digital twin or a moving image of them, but to really rebuild their personality from scratch, so that they and their music could be reintroduced to totally new generations in a very respectful and authentic way to them. It’s hard to know, with the understanding that that is possible, whether or not somebody who is deceased today would or would not agree to something like that. I mean, many of them might want, under those circumstances, for their music to live on. These deceased actors and musicians could live forever with the power of AI technology. Mark Stignani: Yeah, I really just kind of go to the whole—is deep-faking a famous actor the best way to preserve them or keep them live? Again, that’s a bit more of an ethical question because the deep fakes are getting good enough right now to create huge problems. Even zoom meetings in Hong Kong where a CFO was on a call with five synthetic actors who all looked like his coworkers and they sent a big check out based upon that. So again, the technology is getting good enough to fool people. Jeanine Wright: I think that’s right, Mark, but I guess I would just highlight the same way that it always has been: the ethical line isn’t AI versus human, the ethical line is about deception. Like, are you deceiving people? And if people know what it is that they’re getting and they’re choosing to engage with it, then I think it isn’t about the power of the technology. In our business, we have elected—not everybody has—but we have elected to be AI transparent. So we tell people when they listen to our show, we include it in our show notes, we include it on our socials. Even when we’re designing our characters to be very photo-realistic, we make an extra point to make sure that people know that this is AI-generated content or an AI personality. Like, our intention is not to deceive and to be candid. From a business model perspective, we don’t need to. I mean, there’s already people who know and understand that it is AI, and AI is different than people. Because it is AI, there’s all sorts of things that you can do with it that you would not be able to do with a real person. You know, we get people who ask us on the podcast side, we get all sorts of crazy funny requests. You know, people who say, “Can I text with this personality? Can I talk to them on the phone? Can they help me cook in the kitchen? Can they sing me Happy Birthday? Can they show up at my Zoom meeting today because I think my boss would love it?” You know, all sorts of different ways that people are wanting to engage with these characters. And now we’re in the process of rolling out real-time personalities so people will be able to engage with our personalities live. It is a totally different way that people are able to engage with content, and people can, as they choose, decide what kind of content they want to engage with. Ken Suzan: Jeanine and Mark, we’re coming to the end of this podcast. I would love to keep talking for hours but we have to stay to our timetable here. Last question: five years from now, what percentage of entertainment content do you predict will involve significant AI generation, and will audiences care about that percentage? Jeanine? Jeanine Wright: I mean, I would say 99.9%. I mean, already you’re seeing—I think YouTube did a survey—that it was like 90% of its top creators said that they’re using AI as material components of their content creation process. So, I think this will be the default way that content is created. And content that is not made with AI, you know, there’ll be special film festivals for non-AI generated content, and that will be a special separate thing than the thing that everybody is doing now. Ken Suzan: Mark, your thoughts? Mark Stignani: Yeah, I go a little lower. I mean, I think Jeanine is right that we’re seeing, especially in the low-quality content creation and like the YouTube shorts and things like that, you know, there’s so much AI being pushed forward that the FTC even acquired an “AI slop” title to it. I do think that disclosure will become normalized, that the industries will be pushed to say when something is AI and what is not. And I think it’s very much like, you know, do you care about quality or not? If you value the human input or the human factor in this, there will be an upper tier where it’s “AI-free” or low AI assistant. I think that it’s going to stratify because the stuff coming through the social media platforms right now—I can’t be on it right now just because there’s so much nonsense. Even my children, who are without much AI training at all, find it just too unbelievable for them. So, I think it will become normalized, but I think that we’re going to see a bunch of tiers. Ken Suzan: Well, Jeanine and Mark, this has been a fantastic discussion of an ever-evolving field in IP law. Thank you to both of you for spending time with us today on the IP Friday’s podcast. Jeanine Wright: Thank you so much for having me. Mark Stignani: Appreciate your time. Thank you again.

Our latest guest brings a voice – and I do mean a voice – that you don't often hear in the data world. He's bold, he's sharp, and he's not afraid to call out the fluff that can cloud today's analytics conversations. Scott Taylor, also known as The Data Whisperer, is a global advocate for strategic data management, the author of Telling Your Data Story, and one of the most honest, and most likeable, truth-tellers in the data space. Whether he's breaking down metadata metaphors or championing the case for master data as the foundation of all things analytics, Scott's mission is crystal clear: No matter how fancy your AI is, it's worthless without the right data underneath. Scott is a keynote speaker at the upcoming 2026 INFORMS Analytics+ Conference, where he'll be shaking things up with his signature style. 

Ben Criddle talks BYU sports every weekday from 2 to 6 pm.Today's Co-Hosts: Ben Criddle (@criddlebenjamin)Subscribe to the Cougar Sports with Ben Criddle podcast:Apple Podcasts: https://itunes.apple.com/us/podcast/cougar-sports-with-ben-criddle/id99676