Trustworthy AI : De-risk business adoption of AI

Description: Creating AI Trust is a very complex and hard problem. It is not clear what it is and how it can be operationalized. We will demystify what is Trustworthy AI, efficient adoption and leveraging it for reducing risks in AI programs. McKinsey reports indicates companies seeing the biggest bottom-line returns from AI—those that attribute at least 20 percent of EBIT or profitability to their use of AI—are more likely than others to follow Trustworthy AI best practices, including explainability. Further, organizations that establish digital trust among consumers through responsible practices such as making AI explainable are more likely to see their annual revenue and profitability grow at rates of 10 percent or more.

Trustworthy AI : De-risk business adoption of AI is a business podcast hosted by Pamela Gupta, with 52 episodes on record and a Required Pod Score of 80.

Pamela Gupta hosts Trustworthy AI : De-risk business adoption of AI, a business show with 52 episodes published.

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  Episode #7

  De-Risking AI Adoption: Book Launch

  Sep 16, 202613 minS3

  De-Risking AI Adoption: The AI Trust Layer, An AI Governance Playbook is out now. AI has moved from prediction, to generation, to action. Governance has not moved with it. In this short launch episode I explain why I wrote De-Risking AI Adoption, and why the argument is bigger than approval processes or compliance. Traditional AI still decides who gets credit and which transactions look fraudulent. Generative AI writes software and analysis at enormous scale. Agentic systems now call APIs, access data and execute workflows with decreasing human involvement. Each step creates more enterprise value. Each step also widens what happens when something goes wrong. When AI could only generate an answer, the risk was largely the answer. When AI can take action, the risk becomes the consequence, and that consequence runs across financial, operational, security, reputational and increasingly physical impact. That is why AI governance has to become more than a review gate. It has to become an operating system for trusted AI adoption. In this episode: 1:10 Why I wrote this 1:32 Turning AI governance into defensible decisions 2:26 Every wave added risk, and none of it retired the last 5:00 Frameworks are essential, decisions still need an operating model 7:56 The AI approval gap 9:16 AI TIPS, eight dimensions of trust 10:23 As AI moves from output to action, the stakes change 11:17 Three questions before approving AI De-Risking AI Adoption: The AI Trust Layer, An AI Governance Playbook is available now in hardback, paperback and ebook. Forewords by Jim Reavis of the Cloud Security Alliance, Dr Paul Dongha, and Khwaja Shaik of IBM. Get the book: https://www.amazon.com/dp/B0HJN3XMHK Watch the video: https://www.youtube.com/watch?v=0jCFaoOTmyY Trusted AI: https://www.trustedai.ai LinkedIn: https://www.linkedin.com/in/buildingtrustedaiholistically/ For team and bulk copies, get in touch directly. Can Trustworthy AI help De-Risk adoption of AI? ‘Can Trustworthy AI can be instrumental in helping organizations gain a competitive edge and promote better business outcomes, including accelerated innovation with AI’.? With extensive experience in global industry leadership in areas of Business Strategy, Technology, and Cybersecurity, Pamela helps clients in creating a strategic approach to achieving business value with AI by adopting a holistic risk based approach to AI Trust. She defined 8 essential pillars of trustworthy AI. Read more details at Trustedai.ai website . Her insights have shaped the way we look at the impact of Cyberwarfare on Business, strategies for efficient digital transformation, and governance views on Algorithmic failures. Join Pamela as she delves into her signature framework, AI TIPS , standing for Artificial Intelligence Trust, Integrity, Pillars and Sustainability. This podcast is all about operationalizing governance and building Trustworthy AI systems from the ground up. For questions or comments on this podcast reach out to me .

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  Episode #5

  The missing layer in AI governance: capital before commitment.

  Jul 1, 202635 minS3

  Most AI risk conversations begin after capital has already moved. This one begins before. In this episode of the Trustworthy AI Podcast, I sit down with Ernest Nicholson, CEO of SKEET Global Services and Managing Principal of Zephyr IDP, to examine a question most boards and capital allocators are not yet asking: how do you de-risk an AI infrastructure deal before capital commits? Ernest brings three decades of watching capital move into infrastructure at the wrong moment, as a Presidential Appointee in the Clinton Administration, a Senior Executive at Halliburton KBR, and a platform builder at SKEET Global. His work with the AI Ethics Council, co-chaired by Sam Altman and John Hope Bryant, sharpened his conviction that AI governance has to start earlier and reach further, with the communities most exposed to poorly governed infrastructure treated as co-architects rather than stakeholders to be managed. We get into: • The core thesis that risk is set before capital is deployed, not after, and what real de-risking looks like at that stage • The six pillars of Zephyr IDP: Demand, Power and Entitlement, Counterparty, Technology, Capital Stack, and Community and Governance, and where most deals quietly fail • Why Community and Governance, anchored in Agency and Ownership, belongs in the same room as Capital Stack and Counterparty risk • The April 2026 submission of Zephyr IDP to the Basel Committee on Banking Supervision as a practitioner reference framework for AI Infrastructure Specialized Lending Governance, and why Basel risk weights change the math on the cost of debt • Whether a board-reportable governance score can credibly function as a risk weight input for institutional lending, and where that bridge holds or breaks • The four governance layers now forming in the public AI conversation, and the one question every board director should ask before approving a major AI infrastructure investment A substantive, unscripted conversation about de-risking AI infrastructure at the point where capital moves. Can Trustworthy AI help De-Risk adoption of AI? ‘Can Trustworthy AI can be instrumental in helping organizations gain a competitive edge and promote better business outcomes, including accelerated innovation with AI’.? With extensive experience in global industry leadership in areas of Business Strategy, Technology, and Cybersecurity, Pamela helps clients in creating a strategic approach to achieving business value with AI by adopting a holistic risk based approach to AI Trust. She defined 8 essential pillars of trustworthy AI. Read more details at Trustedai.ai website . Her insights have shaped the way we look at the impact of Cyberwarfare on Business, strategies for efficient digital transformation, and governance views on Algorithmic failures. Join Pamela as she delves into her signature framework, AI TIPS , standing for Artificial Intelligence Trust, Integrity, Pillars and Sustainability. This podcast is all about operationalizing governance and building Trustworthy AI systems from the ground up. For questions or comments on this podcast reach out to me .

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  Episode #4

  Mythos & Board Readiness: De-Risking AI Adoption (with Diana Wu David)

  May 18, 202629 minS3

  <p>AI risk is moving faster than traditional governance, monitoring, and board oversight cycles can absorb. The frameworks most enterprises have in place were not built for the velocity of generative and agentic AI, and the gap between adoption and oversight is widening every quarter.</p><p>In this episode of the Trustworthy AI Podcast, host Pamela Gupta sits down with Diana Wu David, Director at ServiceNow Futures and the world's #1 ranked global futurist, to dig into what real board readiness for AI looks like in 2026.</p><p>The conversation covers:</p><p>• Why traditional risk and audit cycles can no...

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  Episode #3

  When AI Runs Your Supply Chain: Governance at the Speed of Commerce

  Mar 11, 202638 minS3

  <p><b>What happens when AI makes thousands of real-time decisions about inventory, fulfillment, and pricing across a $300M+ operation — and one of them goes wrong?</b></p><p><b>In this episode of Trustworthy AI, host Pamela Gupta sits down with Nirmal Jingar, Sr. Technology Leader, AI Platforms & Modernization at Wayfair, to explore what AI governance actually looks like when it has to work in production — not just read well in a policy document.</b></p><p><b>Nirmal isn't advising on AI governance from the outside — he's building and shipping AI systems inside a major e-commerce operation with direct...

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  Episode #2

  AI Governance Isn't Optional Anymore —What ISO 42001 Auditors Look For

  Feb 25, 202636 minS3

  <p>Trustworthy AI: De-risk Adoption of Business AI — with Pamela Gupta</p><p>Most organizations have AI policies. Few have AI governance that holds up under audit. There's a difference — and that difference is where legal exposure, regulatory risk, and operational failure live.</p><p>In this episode, I sit down with Dallas Bishoff, the newly appointed U.S. Vice-Chair of ISO Steering Committee 27 (Information Security, Cybersecurity & Privacy) and one of the first ISO 42001 Lead Auditors in the world. Dallas is both writing the rules and auditing against them — a rare perspective that every AI governance leader needs to hear.</p><p>W...

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