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:<ul><li>Identifying their action plan and choosing their time wisely to execute.</li><li>Enabling a fast cycle time to respond at a manageable cost.</li><li>Implementing effective communications.</li><li>Facilitating the ability and agility to take opportunities to accelerate value creation.</li><li>Staying ahead of the curve with trend spotting.</li></ul>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:<ul><li>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.”</li><li>A “thermostat” — A metadata approach that is continually analyzing and making certain operational adjustments that are driven by both humans and machines.</li><li>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).</li></ul>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 <a href="https://www.federalregister.gov/presidential-documents/executive-orders/donald-trump/2025">2025 Donald J. Trump Executive Orders</a>, FederalRegister.gov.2 <a href="https://www.whitehouse.gov/presidential-actions/">Presidential Actions</a>, WhiteHouse.gov.

<description>&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;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:&lt;/p&gt;&lt;ul&gt;&lt;li&gt;Identifying their action plan and choosing their time wisely to execute.&lt;/li&gt;&lt;li&gt;Enabling a fast cycle time to respond at a manageable cost.&lt;/li&gt;&lt;li&gt;Implementing effective communications.&lt;/li&gt;&lt;li&gt;Facilitating the ability and agility to take opportunities to accelerate value creation.&lt;/li&gt;&lt;li&gt;Staying ahead of the curve with trend spotting.&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;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:&lt;/p&gt;&lt;ul&gt;&lt;li&gt;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.”&lt;/li&gt;&lt;li&gt;A “thermostat” — A metadata approach that is continually analyzing and making certain operational adjustments that are driven by both humans and machines.&lt;/li&gt;&lt;li&gt;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).&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;&lt;i&gt;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.&lt;/i&gt;&lt;/p&gt;&lt;p&gt;Host Frances Karamouzis is joined by expert analyst Lydia Clougherty Jones. Lydia is a senior research director in Gartner’s Data and Analytics (D&amp;A) group. She is part of the Analytics &amp; AI team, where she covers D&amp;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.&lt;/p&gt;&lt;p&gt;1 &lt;a href="https://www.federalregister.gov/presidential-documents/executive-orders/donald-trump/2025"&gt;2025 Donald J. Trump Executive Orders&lt;/a&gt;, FederalRegister.gov.&lt;/p&gt;&lt;p&gt;2 &lt;/p&gt;&lt;p&gt;&lt;a href="https://www.whitehouse.gov/presidential-actions/"&gt;Presidential Actions&lt;/a&gt;&lt;/p&gt;&lt;p&gt;, WhiteHouse.gov.&lt;/p&gt;
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The scope, scale and velocity of the numerous executive orders signed by the new U.S. president thus far call for organizations to assess their impact and proactively plan. In this podcast, we introduce Gartner’s research coverage for a topic that will be critical to nearly every industry.

Impact of the U.S. Executive Orders

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).

<description>&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Gartner predicts:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;i&gt;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.&lt;/i&gt;&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;About the Guest:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;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).&lt;/p&gt;
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Many generative AI (GenAI) initiatives will be abandoned due to escalating costs or unclear business value. In this podcast, Gartner experts discuss the challenges of developing GenAI business cases and reveal approaches to understanding the quantification of value.

Generative AI Business Case Challenges

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.

<description>&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;About the Guest:&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;&lt;p&gt; &lt;/p&gt;
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Microsoft has set a blistering pace in the enterprise generative AI gold rush, leading to a very large majority of organizations analyzing Copilot for Microsoft 365. In this podcast, Gartner experts provide guidance on establishing a Copilot for Microsoft 365 strategy.

Perils and Promises of Copilot for Microsoft 365

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).

<description>&lt;p&gt;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:&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Urgency and action&lt;/strong&gt; — 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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Technology stack&lt;/strong&gt; — 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).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Emergence of agents&lt;/strong&gt; — 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.&lt;/p&gt;&lt;p&gt;In this podcast, our expert analyst Chirag Dekate shares his insight and recommended actions to help I&amp;O leaders deal with the realities of AI and generative AI in all three of those dimensions.&lt;/p&gt;&lt;p&gt;About the Guest:&lt;/p&gt;&lt;p&gt;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).&lt;/p&gt;
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Infrastructure and operations teams must enable two new areas for delivery in order to be in the mainstream of compute infrastructure: high-performance computing and AI. In this podcast, we explore the realities of the AI and generative AI demands on I&O and recommend actions to take.

Demystifying AI and GenAI Infrastructure & Operations Realities

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.

<description>&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Strategic Planning Assumption&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;i&gt;By the end of 2024, three-quarters of the world’s population will have its personal data covered by modern privacy regulations.&lt;/i&gt;&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;
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Privacy obligations extend beyond the security team. This podcast discusses the challenges and provides actionable advice that enables executive leaders to boost customer trust and create value through broader, deeper client engagement, purpose limitation, data life cycle governance and privacy UX.

Privacy Imperatives in the New Age of Data Wealth

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