TechWave: A Gartner Podcast for IT Leaders

U.S. executive orders (EOs) are directives of the executive branch of government and signed by the president that carry the force of law and cannot be ignored. According to the Federal Register, U.S. President Trump has signed approximately 65 EOs since Inauguration Day on 20 January 2025, and there will likely be more to come.1,2 The scope, scale and velocity of the EOs signed thus far require organizations, including global organizations doing business in the U.S., to prepare by assessing their impact and proactively planning.In this episode of the TechWave Podcast, host Frances Karamouzis is joined by Gartner Senior Director Analyst, Lydia Clougherty Jones, to discuss the impact of the U.S. EOs, with a specific focus on how they affect businesses and global enterprises. Frances and Lydia's conversation not only explores the broad range of topics the EOs cover, but also how organizations can ensure they are:Identifying their action plan and choosing their time wisely to execute.Enabling a fast cycle time to respond at a manageable cost.Implementing effective communications.Facilitating the ability and agility to take opportunities to accelerate value creation.Staying ahead of the curve with trend spotting.The EOs from the new U.S. administration need to be well understood by several layers in your organization. This necessitates that your analysis is aligned with your company's business strategy and operating model, which will require:A “barometer” — A way to take in all available data and information, parse it quickly and provide human-driven teams ways to view and assess it. This entails machine-driven tools and technologies specific to C-suite demands, which the Gartner team has coined as “code in the C-suite.”A “thermostat” — A metadata approach that is continually analyzing and making certain operational adjustments that are driven by both humans and machines.An “execution engine” — An underlying approach to develop action plans using signals and data-driven evidence, including the use of bots within boards of directors (i.e., agentic AI in the form of devices or agents given authority to act on a user's behalf).Disclaimer: Gartner does not provide legal advice or services, and its research should not be construed or used as such. While this podcast involves a discussion on a topic that has many legal issues, Gartner does not provide or apply any legal rules or terms to its clients' or prospects' specific business.Host Frances Karamouzis is joined by expert analyst Lydia Clougherty Jones. Lydia is a senior research director in Gartner's Data and Analytics (D&A) group. She is part of the Analytics & AI team, where she covers D&A and AI strategy, AI value to risk analysis and  among many other topics. Importantly, Jones practiced law for two decades — with a focus on emerging technologies and business transformation — before joining Gartner.1 2025 Donald J. Trump Executive Orders, FederalRegister.gov.2 Presidential Actions, WhiteHouse.gov.

After all the hype of 2023, executives who funded several GenAI initiatives are impatient to see returns on investments, but organizations are struggling to prove and realize value. As the scope, scale and price of initiatives grow, aligning the economics (cost, risk and value) of GenAI is a top priority.Gartner predicts:At least 30% of GenAI projects will be abandoned after proof of concept by the end of 2025, due to poor data quality, inadequate risk controls, escalating costs or unclear business value.In this podcast, expert analysts discuss the “Peculiarly Challenging Business Case for GenAI,” for which the Gartner team focuses on measuring value and quantifying return on investment.About the Guest:Host Frances Karamouzis is joined by expert analyst Nate Suda. Nate covers digital strategy, execution and value creation with a focus on maximizing stakeholder value. Nate is in Gartner's CIO practice on the FEVR team (finance, economics, value and risk team).

Interest in Copilot for Microsoft 365 is surging. However, as more organizations experiment with and evaluate this generative AI offering, many questions are emerging about functionality, integration, cost, return on investment, risks, and approaches to deployment. In this podcast, Gartner experts discuss all of these areas and share current challenges, strategic recommendations and predictions for the future.About the Guest:Host Frances Karamouzis is joined by our expert analyst, Matthew Cain, who focuses on the intersection of technology, job skills and workforce culture. He is part of Gartner's Digital Workplace research team, which advises executive leaders on planning and executing technology strategies that incorporate consumer, workforce and business trends. 

As we think about the continued fervor over AI and generative AI (GenAI), 2024 is shaping up to be very different from 2023 in three specific ways:Urgency and action — First, what we are starting to see among our clients is a sense of urgency, where enterprises are shifting from exploration to action. Last year was all about ideation. This year seems to be a lot more about implementation.Technology stack — The technology stack continues to evolve across multiple layers. At the silicon layer, we are starting to see new AI supercomputing innovations and new technologies from cloud providers. In the application layers, we see application-specific integrated circuits (ASICs). There are also networking innovations as well as shifts at the model layer (from large language models to multimodal models).Emergence of agents — We are seeing the emergence of a new area of agents as well as “agent-to-agent” ecosystems focused on connecting and planning approaches to reasoning for purposes of taking action. All of this is being combined with context and memories integrated with our systems and software.In this podcast, our expert analyst Chirag Dekate shares his insight and recommended actions to help I&O leaders deal with the realities of AI and generative AI in all three of those dimensions.About the Guest:Host Frances Karamouzis is joined by our expert analyst, Chirag Dekate. Chirag's research focuses on providing strategic advice on generative AI systems, engineering AI pilots into production across a hybrid and multicloud context with an emphasis on AI (generative AI) infrastructures, quantum technologies (quantum computing, quantum sensing, quantum networking), high-performance computing, and advanced analytics infrastructures (quantum computing, neuromorphic, GPUs and beyond).

The challenges of a modern, data-driven enterprise demand modern tools capable of dealing with the volume and, more importantly, the diverse uses of personal data. In addition, the pace at which modern privacy regulations are proposed and adopted has continued to accelerate. This has fueled adoption of privacy technology by organizations looking to standardize a global privacy approach for handling personal data. Privacy-driven trust can serve as a key differentiator when customers are looking for a reason to pick one brand over another in a homogeneous market.Strategic Planning AssumptionBy the end of 2024, three-quarters of the world's population will have its personal data covered by modern privacy regulations.Executives seeking a positive balance between the organization's overall success and corporate reputation should recognize that a mature privacy program is the entire organization's responsibility. Privacy and data protection officers may take the lead, but CxOs have their respective responsibilities as well. In this podcast, we explore these issues and more.Host Frances Karamouzis is joined by our expert analyst, Bart Willemsen. Willemsen focuses on privacy-related challenges in an international context, as well as on ethics, digital society, and the intersection with modern technology, including AI.

For 2024 and likely the next decade, business value creation will not happen without the successful blending of data and analytics (D&A) and software engineering at the core. Technology can be a failure point when not handled correctly, but it is often not the biggest roadblock to progress. Digital business acceleration will depend equally, if not more, on how you organize the required roles, skills and culture to drive this transformation.

AI investment continues unabated, often with hundreds of proposed initiatives. Almost all initiatives demand data, which requires that cost, risk and time values are assigned to proposed use cases. In this podcast, we explore business and IT leaders' quest to understand and assess AI-ready data.

Digital Vanguard CxOs are 1.5 to 2 times more likely to achieve their value targets from digital. In this podcast featuring expert analyst Jaime Capella, we explore the characteristics of a Digital Vanguard CxO and, more importantly, what makes them more successful at digital initiative outcomes.

The 2024 Gartner CIO and Technology Executive Survey found that 81% of respondents believe that building, developing or customizing digital technologies for the business area should be the responsibility of IT departments (led by CIOs). Only 15% of CIOs believe that this responsibility should be shared equally with business areas, according to the survey.1The ultimate responsibility for building, developing or customizing this software, whether within the CIO organization or in lines of business, falls to software engineering leaders. These leaders are in a key position to enable their organization to become builders of software, because they are at the intersection of business and technical domains, between strategy and implementation. But, to do so, they must build a world-class software engineering organization. In this podcast, we explore the role of software engineers and developers as AI and generative AI are infused into their future. Gartner expert analysts discuss a few of the many layers of this complex topic in the following areas:Reality versus hype — The quest of business and IT leaders separating out what is reality versus hype in order to be pragmatic. More specifically, software engineering leaders must ensure they stay grounded on what is reality so they can prioritize and start piloting and experimenting.Value and measurement — All leaders need to be able to track and measure things so they can determine what they want to put in production, scale and make part of their long-term approach. Above and beyond that, they need to be able to quantify the value. Skills and talent — This involves a deeper understanding of the value of software engineering expertise, performance and productivity.Trends and the future — As always, it is important for leaders to stay abreast of what is coming and how to prepare for it.To address these important focus areas, we discuss several important concepts in the podcast. A few are highlighted below.Reframe the ROI ConversationThe current ROI conversation is focused on cost reduction. Gartner experts are focused on guiding leaders to value generation. It is important to stop thinking of AI as cost-reduction mechanisms or a tool that could help reduce headcount. Instead, it's important to focus on AI and GenAI as force multipliers that enhance developer experience to such an extent that they enable activities that deliver real business value. Amplification FallacyThere is an idea that generative AI will “amplify” people's skills. However, if you carefully think about the concept — “amplifying” something just makes it louder, it doesn't make it better or higher quality. As such, it is important to identify and investigate the differentiated impact across the software development life cycle and specific developer skills. Some initial findings show that GenAI provides a bit more of a productivity boost for junior developers. However, there is also countervailing data that less experienced developers overtrust the outputs of GenAI and are thus more error prone and more likely to introduce security vulnerabilities. For more senior developers, the starting point is that they have the expertise to know what good looks like, as they already have deep knowledge of a problem space, of architectural standards, of best practices and experiential knowledge. Hence, if they are open to using new tools, experimentation and tinkering, they are the ones who can quickly iterate and figure out the best ways to prompt and interact with GenAI coding assistants.Augmentation Versus AgencyOne of the most critical and foundational concepts for the success of AI is trust — engendering trust for both the creators and consumers of the solutions. Software engineers are among the creators of the solutions. The spectrum of increasing trust begins with a low trust level where augmentation rules the day. As trust increases, more tasks are offloaded but not entire roles. Imagine an AI assistant in a craftsman's workshop. As we arrive at a level of trust where we can offload roles, think of the full apprentice or journeyman. With increasing reliability comes increasing trust, and with increasing trust we transition from “tool-based extension” (augmentation) to “social extension” (we recognize AI as having agency).Two of the many predictions Gartner analysts have published on this topic and we explore in the podcast are:By 2028, 75% of enterprise software engineers will use AI coding assistants, up from less than 10% in early 2023.By 2028, systematic adoption of AI coding assistants in 2023 will result in at least 36% compounded developer productivity growth.Evidence1 2024 Gartner CIO and Technology Executive Survey. This survey was conducted online from 2 May through 27 June 2023 to help CIOs determine how to distribute digital leadership across the enterprise and to identify technology adoption and functional performance trends. Ninety-seven percent of respondents led an information technology function. In total, 2,457 CIOs and technology executives participated, with representation from all geographies, revenue bands and industry sectors (public and private).Disclaimer: The results of this survey do not represent global findings or the market as a whole, but reflect the sentiments of the respondents and companies surveyed. Our host Frances Karamouzis is joined by Arun Batchu and Phillip Walsh, who are both expert analysts in Gartner's software engineering leaders team. Batchu is a vice president, and he helps software engineering leaders build their software design, development and people strategies. Walsh is a senior principal analyst who helps software engineering leaders develop and implement strategies to build a world-class software engineering organization.

This TechWave podcast is based on Gartner's research, The Impact of the “U.S. Executive Order on AI.”U.S. President Joe Biden has issued an Executive Order on the Safe, Secure and Trustworthy Development and Use of Artificial Intelligence (the “EO”), which also underscores AI's promise of innovation and competitive advantage. It specifically calls for Americans' privacy and civil liberties' protection, equity and civil rights advancement, and consumers' and workers' support, reinforcing the U.S. Blueprint for an AI Bill of Rights. The EO considers this “the most significant actions ever taken by any government to advance the field of AI safety.” The U.S. is sending a clear signal that AI and GenAI is far more than a disruptive technology; it has far-reaching consequences to impact every aspect of daily life, national and global economies, military matters, and the future of the planet. As such, unlike many other areas of technology or disruptive forces where government organizations have a low reaction time — this is different, and executives will be tested accordingly. One way that our expert analyst, Lydia Clougherty Jones, euphemistically summarizes the message of the EO during the podcast is: “Step Up or Step Aside.” The overall message is that if you are in executive leadership, you have responsibilities with regard to AI. You must proactively take measures to be compliant and prevent harm. As such, “Even if you are not ready for AI, you need to be AI ready.”Executives should adjust leadership priorities, reconcile AI investment with redistributed risk and prepare today for a more regulated tomorrow:The Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence (the “EO”) sends a strong message to the private and public sectors: AI is not a new technology; it's a leadership responsibility. The EO's mandates and directives redistribute the risks of loss associated with responsible AI failures, which will affect current and future AI investments, and the projected corresponding ROI.The EO has major impacts on U.S. federal agencies and those who work with them. It will undoubtedly have a significant impact on the global AI vendor and solutions market, including to address the new standards for the development, functionality, use and output of AI.The EO will have a far and wide impact on AI strategy and the ROI on AI investment. It will alter and redistribute the risk of loss from AI harms considered too costly for AI benefit or value. It will also change corporate and individual behaviors arising from new regulatory frameworks, alongside the industry self-regulation we are already beginning to see take effect. Together, this creates an opportunity for new market solutions, but the oversight of vendors by the government and the commercial sector will be different. In the podcast, several examples are discussed.Note: Gartner does not provide legal advice or services, and its research should not be construed or used as such. While this podcast involves a discussion on a topic that has many legal issues, Gartner does not provide or apply any legal rules or terms to its clients' or prospects' specific business.Our host Frances Karamouzis is joined by our expert analyst Lydia Clougherty Jones, a senior research director in the Data and Analytics group. She covers data and analytics strategy, D&A value, and derisking, among many other topics. Importantly, Jones practiced law for two decades — with a focus on emerging technologies and business transformation — before joining Gartner. Nevertheless, it is crucial to understand that Gartner does not provide legal advice or services, and its research should not be construed or used as such. While this podcast involves a discussion on a topic that has many legal issues, Gartner does not provide or apply any legal rules or terms to its clients' or prospects' specific business.

Generative AI has revealed applications' potential to operate intelligently, which has created the expectation for intelligent applications. IT leaders must understand the foundational changes affecting applications and decide their strategy to ensure continued alignment to target business outcomes.What are Intelligent Applications?Intelligent applications include intelligence — which we define as learned adaptation to respond appropriately and autonomously — as a capability. This intelligence can be utilized in many use cases to better augment or automate work. As a foundational capability, intelligence comprises a number of AI-based services — especially machine learning, semantic enginesvector stores and connected data. Consequently, intelligent applications deliver experiences that dynamically adapt to user context and intent. Sometimes, user experiences are no longer necessary because applications interoperate with other applications autonomously.Intelligent applications can synthesize their interfaces between other applications (self-integrating applications) — as well as users — in ways that are appropriate to the prevailing circumstances, and they can do so proactively (see Figure 2). For example, an intelligent application can pull functionality (i.e., ordering software from a catalog) into a conversational interface based on user intent and context, or adapt it to external APIs for data exchange.Why Is This Trend Important?The way applications work is changing dramatically. Intelligence — in the form of a suite of AI features and functionalities — is becoming a foundational capability. This is expanding the roles that applications can play across a broad range of employee- and customer-facing business activities, and between applications themselves: increasing their level of agency.Intelligent applications transform the experiences of customers and employees, further impacting product owners, architects, developers and governing roles. As applications play a fundamental and pervasive role throughout our working and social lives, these transformations will have far-reaching consequences (e.g., in terms of the types of jobs available to future generations).AI is surpassing the limits reached and imposed by traditional programming that uses explicit rules, relationships and instructions. AI learns rules implicitly. Combined with access to connected data, AI can model context and intent to operate autonomously. This can improve work through augmentation, or eliminate it through automation.As AI continues to advance, it's causing us to reappraise its capabilities and applications. The progress and speed of such advances — especially in the wake of generative AI applications such as ChatGPT — are providing insight into the nature of intelligence itself. AI can now mimic human behavior so successfully that it can not only help or even replace people at work, but it can also, in some circumstances, fool people into believing it's human. As such, the scope of AI's application to work and automation is shifting from routine and mundane tasks, such as invoice processing, to nonroutine and creative tasks, such as copywriting.Why is this Trending?Business disruption due to talent/skill shortages is one of the biggest external threats to business after economic threats, according to the 2023 Gartner's Board of Directors Survey. Workforce (e.g., retention and hiring) is the second biggest priority for 2023 and 2024. The top priority is digital technology initiatives, with AI/machine learning considered the top breakthrough technology. Intelligent applications have entered the mainstream. Over 50% of respondents to the Gartner AI Use-Case ROI Survey reported that they have a form of intelligent application in their enterprise application portfolios. Yet, a lack of effective automation/tools is the biggest barrier to worker productivity, according to one-third of respondents to the 2023 Gartner Workforce Optimization Survey. Key to AI's advance is content — facts modeled for human comprehension. Content includes text, image, video and audio formats. AI can now identify and extract facts from content and remodel these as data for processing. It can use this data as the source from which to synthesize new content — the generative in generative AI. Most enterprise data is in the form of content, such as documents, and central to all activities that involve people. Content also makes up the interfaces through which users interact with applications, and code is itself content. As such, intelligence extends to adapting applications' form and function through re-composition, re-engineering their parts to optimize performance, extend reach and expand purpose.What are the Business Implications?Intelligence as a capability can apply to all applications. The impact and implications are therefore pervasive across all use cases touched by applications (operational-, employee- and customer-centric use cases). Examples include:Optimization and automation of business processes, such as inventory management. For example, generative AI working with AI-based automated stockout measures can deliver natural language insights to managers — ensuring the right level of inventory to match demand. This improves customer satisfaction and related financial metrics. Example: GA Telesis leveraged an AI-based application using Google's Vertex Generative AI Platform, with its sales processes to synthesize purchase orders for aircraft replacement parts automatically.1 This significantly cut GA Telesis' response times to sales inquiries, thus optimizing and preserving the customer experience.Assistance throughout the digital workplace to help with many tasks, including drafting documents, automating process workflows, answering questions and generating business insights. For example, digital workplace application suite vendors and their intelligent assistants, such as Microsoft Copilot and Google Duet AI. Example: Bank of England created a cognitive search application solution using Squirro to enhance its document search and internal knowledge management capabilities.2 This application used machine learning term extraction workflows, coupled with dashboards, to provide a more unified knowledge search system and streamline data management. Customer relationship management with chat-based interfaces facilitating agent-based and self-service support. For example, generative AI can produce an automated summary of a customer service agent's audio interaction with a customer. The code writes one summary for the customer, indicating what advice was given. The code writes a second summary that summarizes the client's issue and adds to the customer service knowledge base. Example: CallRail partnered with AssemblyAI to provide capabilities, such as automatic transcript highlights, and redaction of personally identifiable information.3 This not only provided customer service agents with essential insights much more quickly, but also improved CallRail's call transcription accuracy by 23%. The opportunities created by intelligent applications should be focused on expected outcomes, such as:Simplification and personalization of experiences for both employees and customers.Optimization of processes combined with a reduction in human error.Simplification of applications, and reduction of their number, to deliver business processes.

The C-suite of many enterprises is increasingly asked by their CEO and boards to provide strategic guidance for GenAI as well as about the appropriate investments their organizations should make in this technology. Most enterprises are struggling with how to identify, vet, prioritize and guide funding decision models for generative AI. Gartner high-level guidance is to segment GenAI investments to look at several factors including value alignment to business goals, benefits, costs and risks.A deeper dive into one of these variables — namely cost — requires enterprises to stratify GenAI initiatives across a spectrum of categories. A full description and graphic depiction of these categories is the focus of the on-demand webinar Generative AI Realities: Proactive Approaches for Quantifiable Business Results. In the webinar and in this podcast, Gartner experts explore the following five categories of cost:Category 1 — Targeted purchase ($10,000 to $50,000)Category 2 — Embedded ($50,000 to $250,000)Category 3 — Horizontal or vertical off-the-shelf solutions ($250,000 to $1 million)Category 4 — Situational build ($1 million to $5 million)Category 5 — Market maker ($5 million to $100 million)In the podcast, Gartner experts discuss these cost categories along with risk and many of the other variables that must be analyzed to proactively plan GenAI investments.Gartner has also published several predictions related to enterprise challenges and the perils of GenAI investments:By 2025, growth in 90% of customized enterprise deployments of GenAI will slow as costs exceed value, resulting in pressure on vendors to introduce innovations and pricing models.By 2028, more than 50% of enterprises that have built their own large language models from scratch will abandon their efforts due to costs, complexity and technical debt in their deployments.Our host Frances Karamouzis is joined by senior director analyst Nate Suda, who covers tech, finance, value and risk in Gartner's CIO group. He focuses on digital value creation, digital strategy and digital execution.

Enterprise architect (EA) leaders are professionals who firstly operate at the enterprise level and act as internal management consultants. The primary goal is to facilitate executives' execution of defining business and IT strategy and goals, developing business and operating models and measurements to deliver the objectives and key results. Gartner has found that the majority of enterprise architects report into the CIO or CTO and, as such, spend a great deal of time on the IT strategy and portfolio. This leads to EAs providing guidance and governance through reference architectures, models, principles and guidelines. Technology innovation (TI) leaders are focused on identifying, informing and keeping track of disruptive innovations and successfully bringing them to the organization. While EAs may be expected to assess trends and identify innovation opportunities, Gartner's finding is that TI leaders are more often aligned to a CTO and primarily tasked with taking advantage of technology innovation. Gartner research has identified four different CTO personas — meaning four different types of CTO roles:The CTO as the digital business leader, who is the main force to accelerate digital transformation and innovation.The CTO as the digital business enabler, who is more focused on optimizing business operations.The CTO as the IT innovator, who is the visionary and main change agent.The CTO as the COO of IT, who is the CIO's right hand and focused on optimizing the IT operations.While all personas exist, nowadays the digital business leader, digital business enabler and IT innovator are most common. EA and TI leaders must:Continuously scan and respond to disruptions by evaluating a variety of trends, beyond just technology, to inform their impact on innovation. Guide their technology strategies by understanding the broad technology trends that will affect the near-term planning horizon. Scout emerging technologies to understand the discrete technologies that are on the horizon to anticipate their impact on the organization. Seek diverse viewpoints and experiences to achieve higher rates of successful business innovation; when people from diverse backgrounds and perspectives come together, their unique thoughts pave a path for innovation.In this podcast, Gartner experts explore the value propositions, challenges and research publications for these two critical roles. 

The world is experiencing a very high level of disruption as a result of geopolitical and social changes. The old patterns of operating are increasingly ineffective due to their lack of speed, agility and proactivity. In this rapidly changing business environment, sourcing, procurement and vendor management (SPVM) leaders have a unique opportunity to determine their transformation and define a new vision for technology acquisitions and vendor relationships. SPVM leaders must balance speed, flexibility and vendor relationship building with managing and mitigating risk. SPVM leaders must prepare for the following trends:Increasing proliferation of unproven vendors and technologies: The pace of innovation is accelerating with an ever-increasing number of new vendors, products, services and solutions staking their claim to market share.Rising number of business technologists: Technology acquisitions are transforming every business unit, function and department within companies.Transitioning toward the product-centric IT organization: IT will continue to contribute significantly to the attainment of key business objectives with the focus on aligning products to capabilities or customer journeys. SPVM leaders will be an integral part of the repositioning of IT. Continuing geopolitical and social uncertainty: The world is changing, the status quo is being challenged and the emergence of a new geopolitical architecture affects all facets of business, including technology.Challenges for SPVM LeadersSPVM leaders must react to the following challenges:Without market intelligence capabilities, SPVM leaders lack the necessary data to drive informed decisions. “Buyers' remorse” is a major issue for enterprises as technology buyers very often regret the purchase they made. The current-state sourcing, procurement and vendor management operating model does not support “autonomous” tech buying and cannot support “business-led” buying effectively. In this product-centric era, contracting is stuck in time, and antiquated contracting vehicles make it hard to manage vendors and expectations effectively. Geopolitical and social volatility have an increased impact on supply chain, risk and talent.Recommended ActionsTo be successful, SPVM leaders must:Move toward a dynamic sourcing approach while developing market intelligence capabilities.Build a flexible SPVM operating model that formalizes business-led technology buying.Create product-centric contract proposals.Develop a vendor and market risk management program to address constant regulatory changes, environmental, social and governance (ESG) considerations, and major geopolitical shifts.The role of IT sourcing, procurement and vendor management is changing. SPVM leaders need to decide if they will elevate their role and become internal commercial advisors, or will remain the leaders of a tactical, low-value group that will continue to be an afterthought.

Hyperautomation and intelligent automation investments (inclusive of artificial intelligence) have continued unabated for over five years. The growth has been brisk. While adoption and spending were consistently growing, the trigger of generative AI awareness (spurred by the release of ChatGPT in November 2022) has fueled the growth even more. ChatGPT hit 100 million users in one week and has over 1 billion monthly views on its website. However, only a small percentage of organizations can showcase value or benefits that are identifiable, traceable and quotable on an “earnings call.” This is because few organizations have determined the appropriate or best ways to measure these initiatives, which span myriad technologies such as AI, low code, robotic process automation (RPA) and integration platform as a service (iPaaS). Therefore, Gartner launched a research study called “Gartner's Hyperautomation 100.” The focus is on capturing case studies that feature organizations that have delivered over $100 million in value or triple digit benefits (over 100%) and consistently quantitatively measure those benefits across many different initiatives.In this podcast, we unveil the first of several enterprises that Gartner interviewed. We captured their multiyear journey to not only delivering over $100 million in value but also to measuring it, quantifying it and publicly sharing these achievements because they are traceable and part of an ongoing consistent process of vetting and approving the funding of these initiatives. This podcast features Ericsson, the world leader in the rapidly changing environment of communications technology. It develops, delivers and manages hardware, software and services to enable the full value of connectivity. The official name of the organization is Telefonaktiebolaget LM Ericsson (parent), but it is commonly referred to as Ericsson. Founded in 1876, Ericsson worldwide revenue in 2022 exceeded $26 billion and the company had over 104,000 employees. In 2016, Ericsson started from scratch with no staff and no capabilities in its Enterprise Automation and AI team. At the very beginning, it followed a mantra: “Think big, start small, scale quick.” The terminology it used internally was to set a course for “Radical Transformation Driven by Exponential Technologies.”During the first two years (2016-2017), six initiatives were funded and delivered. Fast forward to mid 2023, when the aggregated number of initiatives has surpassed 300. All the initiatives are funded by the business units as there is no predefined budget. As such, the Enterprise Automation and AI team at Ericsson must prove its value and build confidence with the business unit leaders to get funding for the next project. One of the many ingredients for this success was to measure and quantify the value for each initiative. Internal stakeholder demand (i.e., the amount that business units fund) has increased 22 times since the 2016 launch of the team. It has essentially doubled every year since 2016.

Generative AI refers to artificial intelligence techniques that learn a representation of artifacts from data and use it to generate brand-new, completely original artifacts at scale that preserve a likeness to original data.Generative AI enables computers to generate brand-new, completely original variations of content (including images, video, music, speech and text). It can improve or alter existing content, and it can create new data elements and novel models of real-world objects, such as buildings, parts, drugs and materials.In this podcast, our guest Daryl Plummer takes us through a number of ways to consider the impact of generative AI. We discuss the topic through the lens of a buyer or consumer of the technology, a business leader and a technology service provider.Gartner's high-level messages regarding generative AI include:AI is no longer just a technology or tool. We should no longer treat AI as just a technology. It is no longer just a business tool. AI is now in a place where it is reshaping our society and impacting what it means to be human.Don't say “No,” but ask “How?” We believe advances in AI and the impacts on society cannot be stopped. We must embrace AI and take a “proactionary” approach, which means that we are in favor of advancements that are executed responsibly, through appropriate experimentation.Where there is disruption, there is hope. While we believe that AI should not be hyped, it should never be underestimated. We are at the beginning of many more breakthroughs. And while we acknowledge the fear that surrounds AI, we emphasize the hope. Nothing should be seen as impossible — not even artificial general intelligence.RecommendationsExecutive leaders responsible for innovation and managing disruption should:Understand that AI is advancing rapidly, with an enormous impact on society and business. Address fears of potential job losses incurred from AI technology advances by emphasizing the goal of AI is to augment human capability, not replace it.Collaborate across teams by mixing engineering skills with social sciences. Balance opportunity with risk. Assess and mitigate risk of using new types of AI.While further innovating AI, work on their cutting-edge use cases and governance simultaneously.Frances Karamouzis, distinguished VP analyst, hosted our expert Daryl Plummer, who is also a distinguished VP analyst. Plummer's research focuses on the strategic issues of cloud computing and digital disruption, and the unfolding of the future through predictions, trends and evolving digital business cycles.

Gartner's 2022 Drivers of Secure Behavior Survey reveals that 69% of employees bypassed their organization's cybersecurity guidance in the last 12 months. Further, 74% said that they would be willing to bypass cybersecurity guidance in the future too, if it helped them or their team achieve a business objective (for example, meet an urgent deadline and/or revenue target).1 This willful disregard of security guidance stems from friction that slows down employees and makes it more inconvenient for them to do their work. Moreover, over 90% of survey respondents who admitted behaving unsecurely indicated that they knew their actions would increase cybersecurity risk levels for the organization and, unfortunately, they did them anywayThis cybersecurity-induced friction (hereafter referred to as “friction”), or the “unnecessary” effort exerted by employees to do their work due to the presence of cybersecurity measures, not only drains employee productivity but also pushes them to adopt unsecure practices.It might be convenient and self-serving for cybersecurity teams to think about friction as the “small price” everyone needs to pay to safeguard the organization. But employees often don't share this view and are willing to circumvent cybersecurity controls if these controls hamper them from doing their work. To drive secure behaviors, CISOs need to move away from thinking about friction as a natural and even desirable consequence of cybersecurity measures (a “necessary evil”) and focus instead on identifying and reducing friction that employees experience.In this podcast, we explore Gartner research related to cybersecurity leadership, operational models and shifts in approaches, and delivery of value. Examples include:Evolving role of a CISO from a technical focus to executive leader (whose primary focus is helping business leaders make informed cyber-risk decisions).New cybersecurity teams, functions and processes to address the evolving business environment, such as cybersecurity creating more linkages with the business and working toward shared responsibility.Shifts in cybersecurity policy design and enforcement. There is a shift toward liberalizing the cybersecurity policy toward co-creation with the business as well as making policies less prescriptive and more flexible. This will enable users to have more autonomy for improved execution for security controls. Evidence1 2022 Gartner Drivers of Secure Behavior Survey. This survey was conducted via an online platform from May through June 2022 among 1,310 employees across functions, levels, industries and geographies. The survey examined the extent to which employees behave securely in their day-to-day work, root causes of unsecure behavior, and the types of support and training they received from their organizations to drive desirable secure behaviors. We used descriptive statistics and regression analysis to determine the key factors that drive or impede employees' secure behaviors and their development of cyber judgment.

Gartner forecasts that enterprise IT spending will exceed $4.6 trillion in 2023. That's an increase of 5.2% in constant currency. Of that, business and IT services represents about $1.4 trillion, which is the second largest area of technology spending (second only to telecommunications). Gartner's quarterly update continues to forecast 8.5% growth for the year in constant currency terms (see Forecast: IT Services, Worldwide, 2021-2027, 1Q23 Update).One simple way of talking about the IT services market is to understand some of the players that compete for enterprise spending of business and IT services. Examples include firms such as Accenture, IBM, Capgemini, EPAM, TCS, HCL, Cognizant and Wipro, as well as the more management, strategy or process-driven firms such as McKinsey & Co., EY, PwC and KPMG. Interestingly, the largest firms in the world collectively only account for less than an estimated 25% of the market. In the last 25 years, none of the firms have had more than single-digit share. This results in thousands of midtier and smaller companies — a very large long tail of companies.In this podcast, Gartner VP analyst Sandra Notardonato shares her insights into the market dynamics of the overall sector. The primary reason that this sector is of interest to enterprises is that business and IT services are incurred by over 90% of all enterprises regardless of industry or geography. The strategy, design, deployment, system integration and ongoing management are critical enablers to any cost, growth or innovation-driven business goals.

Artificial intelligence (AI) research and deployment company OpenAI recently announced the official launch of ChatGPT, a new model for conversational AI. According to OpenAI, the dialogue provided by this platform makes it possible for ChatGPT to “answer follow-up questions, admit its mistakes, challenge incorrect premises and reject inappropriate requests.”Since its launch, social media has been abuzz with discussions around the possibilities — and dangers — of this new innovation, ranging from its ability to debug code to its potential to write essays for college students. In this podcast, we sit down for a conversation with Bern Elliot, VP Analyst at Gartner, to discuss the broader implications of this innovation and the steps that organizations should take regarding the use of these tools. Gartner has published a number of research pieces regarding ChatGPT (see recommended reading below). Here are a few of the common questions that set the stage for our interactive dialogue on the podcast.Q. What is ChatGPT and how does it work? Chat Generative Pretrained Transformer, or ChatGPT, is a chatbot and generative language tool launched by OpenAI in November 2022.1 The ChatGPT models compute the most probable set of letters or words when given an initial starting phrase, or “prompt.” ChatGPT is built on top of OpenAI's GPT-3 family of large language models and enables interaction with a model via a conversational user interface. ChatGPT was trained using 300 billion words taken from books, online texts, Wikipedia articles and code libraries, then fine-tuned with human feedback.On 16 January 2023, Microsoft announced the introduction of Azure OpenAI Service, which includes ChatGPT along with language models and added enterprise services..2 It is important for enterprise planners to distinguish between the OpenAI ChatGPT and the Azure OpenAI Service. The Azure version promises significant enterprise operational features, but is still emerging at the time of writing.Q. What role will ChatGPT play in the enterprise? ChatGPT, and foundation models like it, will be used as a tool alongside many other hyperautomation and AI innovations. It will form part of architected solutions that automate/augment humans or machines, and autonomously execute business and IT processes. As generative AI takes its place alongside existing approaches to work, ChatGPT or other competitors will be used to replace, recalibrate and redefine some activities and tasks that form part of many job roles.Q. How much does ChatGPT cost? The current research preview version of ChatGPT, which is the only version users could access up to the end of January 2023, is free of charge. However, there is no guarantee that this free service will persist, and it could be withdrawn at any time. OpenAI recently announced the launch of a pilot subscription plan for ChatGPT Plus for $20 a month.3ChatGPT will also come to the Microsoft Azure OpenAI Service soon, but the pricing for that is currently being rolled out.4 It is possible that significant elements will be bundled with different Microsoft 365 software subscriptions.Q. Should I provide ChatGPT-powered experiences directly to my customers? No — this is too high a risk at present for most use cases, except in rare cases, possibly related to gaming or entertainment, where the correctness or impartiality of the content may have less scrutiny. Gartner expects the ChatGPT service to change rapidly over 2023 and to be complemented by other offerings. It is important for enterprise planners to distinguish between the OpenAI ChatGPT and the Azure OpenAI Service.  Gartner also expects several competitors will enter this market alongside ChatGPT. In particular, Gartner expects organizations like Baidu, IBM and Google to come to market early in 2023, along with a crop of smaller players. For example, on 6 February 2023, Google announced the introduction of its own offering, Bard.Footnotes:1 Introducing ChatGPT, OpenAI.2 Azure OpenAI Service, Microsoft.3 Introducing ChatGPT Plus, OpenAI.4 General Availability of Azure OpenAI Service Expands Access to Large, Advanced AI Models With Added Enterprise Benefits, Microsoft. Host Frances Karamouzis is joined by our expert analyst, Bern Elliot. Elliot is a Gartner vice president and distinguished analyst. His research focus is artificial intelligence generally, with an added focus on natural language processing (NLP), machine translation, and customer engagement and service.

Organizations are in the midst of transformational change that is reshaping our world and expanding our reach into worlds we create and those we have yet to explore. This degree of change will force shifts in how people, and businesses, relate to each other. Old challenges remain, new challenges unfold and endless opportunities abound. Executive leaders should promote the use of technological, political, economical, social/cultural, trust/ethics, regulatory/legal and environmental (TPESTRE) — which Gartner refers to as a “Tapestry” — as a planning tool for uncertainty. Gartner's Tapestry should be used as a starting point for an ongoing trendspotting initiative (see The Gartner Trendspotting Framework: Driving Operations, Innovation and Strategy). To succeed in a disruptive future, enterprises must continually scan and respond to disruptions. These disruptions threaten corporate positions in the marketplace and jeopardize the digital transformation wins that companies have worked so hard to achieve (see Inventing the Future With Continuous Foresight). Executive leaders must evaluate a variety of trends, beyond just technology, and their impact on strategic planning. Gartner's Tapestry research is a 360-degree perspective of potentially game-changing technological, political, economical, social/cultural, trust/ethics, regulatory/legal and environmental trends that will assist leaders in their strategic planning efforts. In this podcast, our expert analyst Marty Resnick joins us to explore how you can utilize Tapestry for strategic planning. Host Frances Karamouzis is joined by our expert analyst Marty Resnick. He is one of the leaders of Gartner's Futures Lab, our home for unconventional, speculative and futuristic research. The mission of the Gartner Futures Lab is to prepare leaders for uncertainty by exploring new ways of imagining the future. By starting with the question “What if …,” we help you determine your uncharted next mission-critical priorities.

Our host Frances Karamouzis is joined by Tad Travis, chief of research for our applications leaders team. Travis shares how Gartner expert analysts are delivering research for all of these important areas.

Business-driven hyperautomation is a disciplined approach that organizations use to rapidly identify, vet and automate as many business and IT processes as possible. Hyperautomation involves the orchestrated use of multiple technologies, tools or platforms. Its ubiquity is both a strength and a weakness. It's a strength as it is applied to myriad business and IT processes in every business and IT function in the organization. Its weakness is that it requires disciplined and orchestrated strategic planning to architect, design and implement and, most of all, rigorous adaptive governance to sustain. Spending on hyperautomation initiatives is projected to be brisk and somewhat recession proof. By 2026, the market for software that enables hyperautomation will reach nearly $1.04 trillion from the 2021 totals that hovered at $591 billion. This represents a compound annual growth rate of 11.9% (see Forecast Analysis: Hyperautomation Enablement Software, Worldwide). Gartner also estimates that for every dollar of software spend, there is $4 to $12 that are spent on IT services. Examples of IT services include strategy, consulting, implementation and systems integration. Moreover, a large amount of this spend on software and services is siloed across an array of business functions. In that regard, Gartner has predicted that by 2024 a diffused (siloed) approach to hyperautomation initiatives will drive up initiative-specific total cost of ownership by fortyfold, making adaptive governance a differentiating factor in financial performance.One of the many reasons for these large numbers and continued growth is that hyperautomation initiatives often have a broad spectrum of business outcomes and a very large and fragmented set of technology markets. In this podcast, our Gartner expert analysts share some trends and predictions regarding hyperautomation. Examples include:API-first world — There is a stealth and clear trajectory to an API-first approach as evidenced by RPA vendors increasingly investing in improving their API connectivity capabilities. Application portfolios are changing with more SaaS being adopted in portfolios, many of which have documented APIs. APIs are easier to secure and more stable to interact with than screen scraping techniques.Reduction in core need for screen scraping — The simplification, abundance and increased functionality of API access will reduce the core need for RPA screen scraping and task automation that initially thrust these product categories to the forefront.RPA vendor evolution — An overwhelming majority of RPA vendors offer automation via both API and UI integration. This means that organizations will scale their automation beyond screen scraping and complement offerings with APIs, robust workflows and process insights to achieve enterprise scale automation. This will set the stage for either convergence or consolidation of existing markets or some newly formed categories.For additional insights and an early glimpse of Gartner's hyperautomation predictions for 2023 — listen to our podcast.In this podcast, our host Frances Karamouzis is joined by two Gartner expert analysts — Keith Guttridge and Saikat Ray. Both Guttridge and Ray are part of Gartner's software engineering leaders research teams and speak to many clients working on hyperautomation initiatives. Both analysts are part of the authoring team for Magic Quadrants for Integration Platform as a Service and Robotic Process Automation, among several other publications.

Digital business will not happen without a digital platform with data and analytics (D&A) at the core. Technology can be a failure point when not handled correctly, but it is often not the biggest roadblock to progress. Digital business acceleration will depend equally, if not more, on how you organize D&A and the required roles, skills and culture to drive this transformation.CEOs cite data and analytics as the top capability for enabling growth over the next two years.1 They also believe that artificial intelligence (AI) will be the technology most significantly impacting their industry over the next three years.1 As such, the role of the CDAO is growing in influence as organizations must transform data into business value. CDAO refers to the business leadership role that has the primary enterprise accountability for value creation by means of the organization's D&A assets and ecosystem. Equivalent titles for portions of this responsibility are chief data officer, chief analytics officer, and chief/head of data and analytics, to name a few.Gartner has been an early pioneer in this area. We are the only research firm around the world that recognized the role and its importance over eight years ago and launched the first comprehensive CDAO survey. We now boast the largest body of contiguous data about CDAOs and how they are growing, evolving and, most of all, adding value. If you are a CDAO and would like to participate in the study, here is the link: CDAO Survey.Common Characteristics of CDAOs Gartner's depth and breadth in the area of D&A and, more specifically, the large number of client inquiries and interactions with CDAOs have revealed that CDAOs have the following common characteristics: Often new in their position. Most have been in their role for less than two years.Lack C-level experience and leadership skills,​ as they came from targeted D&A competency.Often appointed to a role without any specific or clearly defined measures for success. CDAOs struggle to showcase or articulate the value delivered. Need guidance and measurement of effectiveness. They struggle to self-assess how effective they are in their role or determine team efficacy or efficiency.Gartner CDAO Survey Insights The 2022 CDAO study shows that the most effective data and analytics leaders focus on creating business value, nurturing data and analytics talent, and changing culture. CDAOs must deliver tangible business outcomes for their organization and stakeholders as their life span in the role is highly correlated to these results. Leaders need to prove how D&A can improve business processes, lead to better decisions and support digital transformation.Based on past survey results and Gartner's interaction with clients, nearly 500 CDAOs highlighted the following roadblocks as inhibitors to their success:Skills and staff shortagesCultural challenges to accept changeLack of resources and funding to support the programsLack of trust in data or data sources (internal and external)Lack of business stakeholder involvement and supportPoor data literacyStarting Point and ApproachGartner research reveals that D&A leaders that are most successful tend to excel in four key areas: LeadershipSkills and cultureOperational excellence Demonstrating business outcomes1 The 2022 Gartner CEO and Senior Business Executive Survey was conducted to examine CEO and senior business executive views on current business issues, as well as some areas of technology agenda impact. The survey was conducted from July 2021 through December 2021, with questions about the period from 2021 through 2023. The research was collected via 382 online surveys and 28 telephone interviews. Survey results are published in 2022 CEO Survey — The Year Perspectives Changed.Results of this survey do not represent global findings or the market as a whole, but reflect the sentiments of the respondents and companies surveyed.In this podcast, our host Frances Karamouzis is joined by Carlie Idoine, chief of research for our data and analytics team, to share how Gartner expert analysts are delivering research for all of these important areas. Her experience includes design, implementation and communication of an enterprise analytics strategy and comprehensive analytics programs.

Cybersecurity permeates every single organization in the world, as a breach can impact your operations, delivery of your product or service, and your brand. As a result, CISOs and their teams are under pressure from many directions, requiring them to take a broader perspective than they did in the past. CISOs need both technical and business skills.Cybersecurity importance and impact are so significant that it has become a common discussion topic for boards of directors (BoDs) across all industries. This is not surprising, as 88% of respondents to the 2022 Gartner View from the Board of Directors Survey1 now regard cybersecurity as a business risk, and not a technology problem. As a result of this trend, cybersecurity leaders, including chief information security officers, are increasingly being asked to present on a wide range of cybersecurity topics. These include:Daily cybersecurity needs — Providing an overview of the latest trends, threats or incidents that are prominent in the media or being discussed on other boards — for example, ransomware.Staying current — Every CISO must stay current on fast-changing cybersecurity news, manage effective incident response, adapt cybersecurity approaches to rapid changes, and influence and drive secure behaviors.Demonstrating value and proactively managing investments — A CISO must summarize how the cybersecurity team's investments are delivering value to the organization. This requires defining cybersecurity metrics, securing a defensible budget, effectively partnering across the business, and improving individual and team effectiveness. Additionally, the CISO may need to raise the level of cybersecurity literacy for the board of directors and other leaders in the organization.Building and optimizing their cybersecurity program — This includes things such as defining their cybersecurity strategy, defining their cybersecurity architecture, building and maintaining teams. and managing risk. One staple of any cybersecurity program involves the assurance that the organization meets its compliance obligations.1 The 2022 Gartner View From the Board of Directors Survey was conducted online from May through June 2021 among 273 respondents from the U.S., Europe and Asia/Pacific. Companies were screened to be midsize, large or global enterprises. Respondents were required to be a board director or a member of a corporate BoD. If respondents serve on multiple boards, they answered for the largest company, defined by its annual revenue, for which they are a board member. Disclaimer: Results of this survey do not represent global findings or the market as a whole, but reflect the sentiments of the respondents and companies surveyed.In this podcast, our host Frances Karamouzis is joined by Mary Ruddy, chief of research for our security and risk management team, to share how Gartner expert analysts are delivering research for all of these important areas. Her primary research areas are security and identity architecture, and access management including customer IAM. Ruddy's thought leadership includes recent contributions to Top Trends in Cybersecurity, Top Strategic Technology Trends, Cybersecurity Mesh Architecture, Identity Fabric, and Identity Threat Detection and Response.

According to Gartner's 2022 CEO study, the workforce has become the third most important priority for CEOs in 2022 and 2023,1 making this a top issue for the highest-level executives of the enterprise. A number of these workforce issues are the great resignation, hybrid work and burnout. All of these are at the forefront of the VP of HR agenda. Gartner has extensive research addressing these topics (see recommended reading below). However, the shift from the human capital function to CEO and boardroom conversations often has additional dimensions. Beyond attracting, acquiring, retaining and training talent, the collective delivery execution of remote, globally distributed personnel, workflows, processes, and enabling tools and technologies add to the complexity. This translates to productivity and utilization of personnel in pursuit of team-based synergistic collaboration. The collective impact on time (cycle time, elapsed time, reaction time), quality and risk is the boardroom conversation of “labor volatility.” The biggest market implication is business disruption; specifically, the inability to:Launch a new product or serviceDeliver an existing product or serviceAvoid significant delays that have a “material” financial impact The term “material” is an accounting term that means significant financial consequence that must be explained on financial disclosures. This podcast features a case study of global talent resilience to showcase the art of the possible for addressing labor volatility. The case study is about EPAM, which started in the U.S. in 1993 as a software engineering services company. The focus was to deliver application development and engineering services from Eastern Europe. Now, EPAM is a service provider that is a consulting firm, system integrator or managed services firm.PAM had been consistently growing at a strong pace from its foray into the public market (2012 IPO). At the time, financial and industry analysts had identified one of its areas of vulnerability as its unusually high concentration (85%) of personnel in Belarus, Russia and Ukraine. Thus, EPAM's leadership developed and began executing a multiyear plan to derisk by shifting talent across 50 countries around the world. The plan was moving forward with investments in highly distributed collaboration tools, client engagement and people platforms, and new agile development approaches targeted to multicultural and time-zone-agnostic work techniques. Starting in 2014, a series of disruptive events occurred. There were significant geopolitical issues in Belarus, Crimea and other areas of importance to EPAM operations. This forced EPAM to accelerate its plan. Then, we were all impacted by the pandemic. Similar to many other companies, EPAM was navigating the complexities of the pandemic-mandated, almost instantaneous shift to fully remote operations.hen EPAM entered the public markets in 2012, it had 8,000 employees, with 82% concentrated in Central Eastern Europe (CEE). By 2015, it lowered its concentration in CEE to 71%, having grown to 18,000 employees. There was continued progress over the years. In the second quarter of 2022, EPAM had 60,000 employees, with a concentration of 31% in Central Eastern Europe. In this podcast, EPAM's CEO Arkadiy Dobkin recounts how his team made the incredible shift of people and resources out of Belarus, Russia and Ukraine to more than 12 other countries. From August 2020 through May 2022, EPAM shifted close to 10,000 employees from Belarus, Russia and Ukraine to countries such as Poland, Georgia, Turkey, Lithuania and many others. In summary, EPAM went from 85% of its people in Belarus, Russia and Ukraine in 2012, to 69% in 2015, to 31% in 2022. By any standard, this kind of people pivot is amazing and is a demonstrated example of global talent resiliency.About the GuestOur host Frances Karamouzis is joined by Arkadiy Dobkin. Dobkin is the CEO, president and chairman of the board at EPAM Systems, a leading digital transformation services and product engineering company. Under his leadership, EPAM has grown from a New-Jersey-based startup with Eastern European roots to the foremost global digital transformation services provider — leading the industry in digital and physical product development and digital platform engineering services. Today, EPAM is a global enterprise and part of the S&P 500 Index.

The democratization of digital delivery means putting the responsibility, tools and accountability for building digital capabilities in the hands of not only IT departments but also other business units. The COVID-19 pandemic has given this trend renewed urgency as organizations have had to accelerate the digitalization of how they work and serve their customers remotely. Digitalization opportunities have seen dramatic growth, together with lower barriers to entry (for example, low-code development tools and artificial-intelligence-assisted development). These have enabled technology work that was once primarily the responsibility of dedicated IT teams to become “democratized.”Gartner's research reveals that business technologists (i.e., personnel reporting outside of IT) outstrip IT headcount by a factor of four to one. The increased number of business technologists highlights a significant shift in how enterprises manage their information technology estate.CIOs and IT leaders must seize the moment to reimagine a technology operating model on an enterprise level (not just for the IT organization) to help the enterprise gain maximum advantage from its technology investments and its growing population of business technologists. Many of these business technologists are bringing new ways of working and being successful as part of the fusion teams that deliver in more agile ways.To provide some context of these new ways of working, we highlight the definitions of fusion teams and business technologists:A fusion team is a multidisciplinary team that blends technology or analytics and business domain expertise, and shares accountability for business and technology outcomes. Instead of organizing work by functions or technologies, fusion teams are typically organized by the cross-cutting business capabilities, business outcomes or customer outcomes they support. A business technologist is an employee who reports outside of the IT department (centralized or business unit IT) and creates technology or analytics capabilities for internal or external business use. Business technologists can be individuals whose primary job entails technology work (such as Python developers hired in marketing, data scientists hired in finance, and accounting teams or software engineers hired in R&D). They can also be citizen technologists whose primary job is done through technology work (such as pricing managers building algorithms, customer service representatives building chatbots or doctors writing pandemic apps).Host Frances Karamouzis is joined by Gartner expert analyst Jaime M. Capella. Capella is a Distinguished VP, Research, serving CIOs and other senior executives. His recent research collaborations look at the evolution of technology operating, funding and governance models to adopt Agile, incorporate product management principles and democratize digital delivery. 

The business value of artificial intelligence (AI) will reach $5.1 billion by 2025. Furthermore, 80% of executives think that automation can be applied to any decision. These impactful findings are among the many reasons that Gartner invests considerable resources to conduct an annual Artificial Intelligence Survey. Gartner's annual survey is designed to understand the keys to successful AI implementations and the barriers to the operationalization of AI. The research was conducted online from October through December 2021 among 699 respondents from organizations in the U.S., Germany and the U.K. The results of the survey cut across four key themes:The Value of AIOperationalizing AITalentPrivacy, Security and RiskFor the first theme — the Value of AI — the data shows that organizations continue to increase their focus on measuring the value of their AI efforts. This zeal for value is driven by the fact that 40% of organizations have thousands or hundreds of thousands of AI models deployed. Furthermore, leading organizations expect to double the number of artificial intelligence projects in place. As such, there is a continued quest to more accurately measure value and showcase the benefits to leadership.This leads us to the other themes. The survey data reveals that operationalization progress is slow; only 54% of AI models are fully deployed. Yet, the barriers are not talent-driven. Over 70% of organizations indicate AI talent is not a primary concern for staffing AI initiatives. Organizations report that they are able to retrain or upskill existing talent or acquire new talent to meet the need.In this podcast, Gartner expert analyst Svetlana Sicular explores the first three themes, providing insights, examples and more data-driven findings from Gartner's annual Artificial Intelligence Survey.Our host Whit Andrews is joined by expert analyst, Svetlana Sicular. Sicular's research interests center on artificial intelligence (AI) and machine learning (ML); data-centric AI; and responsible AI and augmented intelligence.

Gartner defines business technologists as employees who report outside of IT departments (centralized or business unit IT) that create technology or analytics capabilities for internal or external business use. In the 2021 Gartner Reimagining Technology Work Survey, respondents indicated that, on average, business technologists make up 41% of their organization's workforce. About 80% of these users are citizen technologists who create technology output as part of (or in addition to) their full-time roles. Business technologists and other citizen personas play a key role in automation, application development, data science and many other roles. These personas are often referred to as citizen developers, citizen designers, citizen integrators, citizen data scientists and many other roles with the prefix “citizen.” When these non-IT users have access to intuitive, self-service tools, they are empowered to independently build solutions for their business unit.As low-code development technologies proliferate, more organizations are recognizing the value of empowering citizen technologists. These non-IT personas can independently use low-code and no-code technologies to improve business efficiency, efficacy and agility. Citizen technologists use a wide range of tools, and they need intuitive, flexible platforms to develop, automate and integrate their data, forms and workflows. In fact, citizen automation and development platforms (CADPs) have emerged as a new class of solutions that specifically target the needs of citizen technologists with an emphasis toward no-code builder experiences.Our host Dixie John is joined by our expert analyst, Jason Wong. Wong is a distinguished VP analyst on the Software Design and Development team helping CIOs, and IT, application and software engineering leaders. Wong's research focuses on enterprise strategies for “total experience,” low-code platforms, citizen development, mobile apps, progressive web apps and multiexperience development.

Worldwide, public cloud services are forecast to grow by 20.4% (22.0% in constant currency) in 2022. Organizations continue to accelerate cloud adoption, which is driving a five-year compound annual growth rate of 19.6% (19.4% in constant currency). The continued growth of cloud quite naturally leads to a discussion about some of the primary providers, often referred to in the market as the hyperscale vendors. Examples of hyperscale vendors include Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP) and Alibaba's Alicloud. Others may also be considering services from Facebook or Apple.A hyperscale vendor is a very large-scale cloud provider with global reach and impact. The potential for a hyperscale cloud provider's failure is a classic high-impact/low-frequency risk. More specifically, “concentration” risk focuses on the level of dependency (reliance) an organization's business, processes and data may lie with a specific vendor's offerings and services. Understanding the scope and scale of cloud service provider failure is critical in order to take steps to manage risk.Cloud services democratize access to resilience and redundancy capabilities previously only cost-effectively available to the largest enterprises. However, it is your responsibility to take advantage of these capabilities through resilient design that places the emphasis upon avoiding disasters rather than recovering from disasters. As organizations embrace cloud capabilities, the most effective teams strive to avoid service interruptions by creating systems that are highly available. This allows them to sidestep failures in underlying systems and continue operating with minimal impact to users, rather than recovering from an outage.Traditional disaster recovery (DR) thinking is rooted in the failure of physical data centers. However, in public cloud infrastructure and platform as a service (IaaS and PaaS), the failures with broad customer impact are rarely rooted in the data center issues. Rather, they are the result of software bugs that cause one or more cloud services to fail.IT leaders should rethink traditional disaster recovery architectures in favor of more effective resiliency patterns — not only when deploying new applications in public cloud IaaS or PaaS, but also when migrating existing applications to public cloud environments.

Every year, Gartner shares the personal side of expert analysts in the form of their recommended reads (see Gartner's 7 Must-Read Business Books for 2022). Each book on the list comes with a note from the expert highlighting its value to you as a leader and an individual. This month's podcast features the book The Delusions of Crowds: Why People Go Mad in Groups by William J. Bernstein. The book was recommended by one of our data and analytics experts, Andrew White. The primary reason White recommended this book is that it goes totally against the popular image of the wisdom of crowds and explores counter arguments referred to as the delusions of crowds. Most importantly, the ideas are framed on the key challenges of executives and IT leaders for strategic decision making.Gartner research highlights that decision making is a core capability for every organization, and it is becoming more complex. Decisions are becoming more connected, more contextual and more continuous. IT leaders must prepare to reengineer decision making and ultimately make business decision making a competitive differentiator. 

There is a great deal of hype and confusion about the creation and value of platforms. Since 2004, Google searches on the word “platforms” have increased about 300% to a peak last August. And in the last couple of years, the word has appeared in 5% to 10% of the questions clients ask or the notes of the advice we give when we answer those questions. Based on the high interest in the topic of platforms, in this podcast Gartner explores value drivers for successful platforms.A few factors that are explored regarding platforms include:The definition of a platform is less important than the proposed product's value proposition.The platform is a product. It is a product that must be developed in alignment with the customer-centric use cases that drive compelling value that is sustainable and effective.Platform is not the same thing as the network effect. Network effect occurs in business models where something gets better with the addition of every customer.SaaS is not the same thing as platform. Structurally, a SaaS model allows for multitenancy of one or more assets — the user interface, software, data, hosting approach and many other technology elements. SaaS has robust partitions and compartmentalizes participants. A sample of interesting Gartner predictions across the extensive coverage of platforms includes:By 2025, 80% of IT spending will be subscription- and/or consumption-based, driven by a shift to product and platform business models.By 2025, four of the top ERP vendors will rebrand themselves as business platform providers

Digital workplace leaders who readied their organizations for remote work were able to meet the challenges of the pandemic swiftly and successfully. Right now, leaders across the organization — most notably, human resources, corporate real estate and the C-suite — are having discussions about the return to the office as well as the alternative flexible hybrid work options. Workers want to choose when and where they work. Every organization, team and department will execute this differently. The good news is that you likely have the main applications you need to support these work patterns. You've been deploying cloud-based productivity capabilities (e.g., collaboration, calendaring and meetings) to support remote work. In this TechWave podcast, a Gartner analyst provides his perspective on the gaps in functionality where new, interesting vendors will emerge to enhance the digital workplace.

In this podcast, Gartner analysts discuss some very interesting predictions that are among Gartner's top predictions for 2022: By 2024, 40% of consumers will trick behavior tracking metrics to intentionally devalue the personal data collected about them, making it difficult to monetize. Analysis is by Rachel Steinhardt.By 2025, synthetic data will reduce personal customer data collection, avoiding 70% of privacy violation sanctions. Analysis is by Svetlana Sicular, Jim Hare and Anthony Mullen.By 2027, a quarter of the Fortune 20 companies will be supplanted by companies that “neuromine” and influence subconscious behavior at scale. Analysis is by Jackie Fenn.

Data privacy law became relevant in the early 1970s alongside the advent of computer retail sales. Today, more than 140 countries with data privacy laws are attempting to control personal data collection and use while mitigating the risk of downstream data misuse. However, most are ill-equipped to accomplish either. This leaves data and analytics leaders incapable of applying much-needed data and analytics across their organization, let alone globally, while also protecting individuals from data misuse. In short, data privacy law is a mess, creating inefficiency and undermining goodwill. In this podcast, Gartner expert analysts share a “maverick” approach on how business and IT leaders driving business and consumer value should use the seven-point framework: Positivity, Rally, Inquire, Validate, Abandon, Comply, Yield (P.R.I.V.A.C.Y.). This framework takes the maverick approach of proactively strategizing on how to concurrently scale data while protecting individuals worldwide from data misuse.

This podcast discusses a very interesting prediction that was selected as one of Gartner's top predictions for 2021. The prediction is:By 2025, customers will be the first humans to touch more than 20% of all products and produce. The hope of long-term business impact for any hyperautomation initiative is a fully automated process that results in a product advancing through the assembly line, onward through the supply chain and distribution channels to arrive at the end customer, whereby the first human to touch and interact with the product is the consumer. Machines and computers are increasingly performing more types of tasks independently. So much so that Gartner anticipates that, by 2025, there will be a critical mass of commercial examples of products or produce that have fully automated end-to-end processes.

Gartner analyst Penny Gillespie recently introduced new research on rogue thinking, an approach for idea generation to drive revenue and ignite transformation. Rogue thinking goes against conventional, mature business wisdom by connecting what may appear to be disparate elements in ways that redefine category norms and expectations that produce business value.Rogue thinking facilitates idea execution through the common barriers of benefit recognition, measurement, risk assessment, funding, delivery and communications. In essence, it is a recipe for identifying business opportunities.Host Whit Andrews speaks with Penny Gillespie, vice president and Gartner fellow in Gartner's Customer Experience/Digital Commerce team, which resides in the larger Applications and Software Engineer Leaders Group. Gillespie is responsible for conducting research and developing publications aimed at helping IT leaders recognize digital opportunities, develop a competitive strategy for digital commerce as well as improve digital commerce performance.

Kevin Roose's book, “Futureproof,” presumes a future in which automation has reconfigured the natures of employment and social life. Roose provides nine rules for how to survive this era. In this podcast, we discuss the rules as they apply to IT leaders and what steps such leaders can take in their lives to thrive. Roose shares stories about how previous generations of automation can teach us how to react to this one. Host Whit Andrews talks with Kevin Roose, an award-winning technology columnist for The New York Times and New York Times bestselling author, about his new book “Futureproof.” Roose is the host of “Rabbit Hole,” a New York Times-produced podcast about internet culture, and a regular guest on “The Daily,” as well as other leading TV and radio shows. He writes and speaks regularly on many topics, including automation and artificial intelligence, social media, disinformation and cybersecurity, and digital wellness.

Changes in how organizations mature their data and analytics strategies will define how organizations accomplish their future directions. Host Whit Andrews met with three Predicts authors at the Data and Analytics Virtual Summit to discuss data and analytics predictions.Erick Brethenoux specializes in machine learning, artificial intelligence and applied cognitive computing. He guides organizations on the strategic, organizational and technology aspects of using advanced analytics as a driving force of their growth. Mark Beyer covers broad data architecture solutions including data management and its intersection with use cases and data governance issues. His recent areas of client issues and research include adapting best practices for data management to remove false distinctions between cloud, on-premises and hybrid fallacies. Frank Buytendijk is a Distinguished VP and Gartner Fellow in Gartner's Data and Analytics Group. His work often takes a futurist approach, researching the edges of what he covers. Buytendijk pioneers the topics of the future, digital ethics and digital society, helping organizations do the “right thing” with technology.

Host Whit Andrews engages leading Gartner analysts in this podcast to explore the future of digital control. They discuss rewards, penalties and virtual imprisonment through digital tools, and what listeners may need to do to make their enterprise ready in various scenarios. As an example, leaving your house without your phone is increasingly an unimaginable action for many people who live rich digital lives. The control that governments can exert on the phone in some countries gives them the ability to influence people without needing to affect their physical selves. Such impacts will be available to commercial entities as the sophistication of user behavior monitoring grows in intensity.Two Gartner analysts who have authored Maverick publications are joined by one of the leaders of our Maverick program, Frank Buytendijk.

Gartner research suggests that, by 2026, 80% of organizations will abandon pursuing a 360-degree view of the customer. This is for several reasons, including that it doesn't adhere to privacy regulations and obliterates customer trust.Host Whit Andrews discusses the future of pursuing the 360-degree view of the customer with Marty Resnick, VP analyst and co-lead of the Maverick program; Lizzy Foo Kune, VP analyst in Gartner's Marketing practice; and Benjamin Bloom, VP analyst in Gartner's marketing practice. 

Farhan Choudhary joins Whit to talk about ideas for vendors the world needs. Farhan is a part of Gartner's Artificial Intelligence team, under Data and Analytics at Gartner, focusing on Artificial Intelligence along with Data Science, Machine Learning and Deep Learning. He co-led the Gartner Use Case Prism Framework and with that guides organizations on the strategic, organizational and technology aspects of using advanced analytics as a driving force of their growth.

Finding IT workers and making their offices convenient to them is a key factor in discovering access to new skills and making strategic decisions about organizational locations. 2020 intensified the potential for new locations and disrupted natural assumptions about what nation and what location to pursue. Learn from TalentNeuron about how to aid executives in partnering for IT talent success.

Compute resources directly embedded in the body and available to the brain are the natural outcome of making technology smaller and more portable. The evolutions of prior generations of technologies lead Gartner Maverick research to imagine how technology will reframe ideas of being, working, and interacting as features and functions migrate to the least latency possible -- being part of the human brain.

Four predictions about the impacts of cloud computing frame a future that IT leaders can react to and prepare for. A world where transportation and retail are refigured through cloud means that organizations must respond now with organizational and strategy changes.