Insight On

Shadow AI Agent Risk: It's Not Just the CISO's Problem | EP28

Shadow AI agent risk has moved from information risk to operational risk in less than six months — and that shift means accountability no longer sits with the CISO alone. Vivek Menon, CISO and Head of Enterprise Data at Digital Turbine, explains why the COO, CMO, and CFO are now on the hook when an agent acts without human review. In this conversation, you'll learn how shadow agent risk differs from shadow AI and shadow IT, why Vivek builds governance to the EU AI Act as his North Star even for US operations, and what "survivable, auditable, explainable" actually looks like when an incident reaches auditors at a public company. If you're still getting up to speed on what agents actually are, the AI Agent Cheat Sheet breaks it down: https://www.insight.com/en_US/content-and-resources/guide/the-ai-agent-cheat-sheet.html [https://www.insight.com/en_US/content-and-resources/guide/the-ai-agent-cheat-sheet.html] Vivek also shares the one hiring metric that tells you whether AI adoption is working — and why zero friction in AI tools is a red flag, not a feature. For more on the questions executives are asking behind closed doors about agents, check out our companion episode: https://www.insight.com/en_US/content-and-resources/insight-on/what-executives-are-too-embarrassed-to-ask-about-ai-agents-answered.html [https://www.insight.com/en_US/content-and-resources/insight-on/what-executives-are-too-embarrassed-to-ask-about-ai-agents-answered.html] This episode wraps our series on the agent economy. If you're building an AI transformation playbook, see how one organization approached it: https://www.insight.com/en_US/content-and-resources/case-studies/case-study-the-ai-playbook-ai-transformation.html [https://www.insight.com/en_US/content-and-resources/case-studies/case-study-the-ai-playbook-ai-transformation.html] — and learn more about Insight's full AI services and capabilities here: https://www.insight.com/en_US/what-we-do/expertise/data-and-ai.html [https://www.insight.com/en_US/what-we-do/expertise/data-and-ai.html] Book a Radius strategy workshop because you'll get a structured path to AI governance and agent readiness tailored to your environment: https://www.insight.com/en_US/what-we-do/methodology/radius-business-strategy-workshops-and-planning.html [https://www.insight.com/en_US/what-we-do/methodology/radius-business-strategy-workshops-and-planning.html] Chapters (5–12) * 00:00 — Welcome and introduction * 01:35 — What Digital Turbine does * 02:18 — What CISOs admit to each other behind closed doors * 03:01 — Shadow IT to shadow AI to shadow agent risk * 04:33 — Why AI agent risk is now an operational risk * 05:32 — What a survivable AI incident looks like * 07:03 — Pressure on CISOs to not be the department of no * 08:45 — Red flags when new AI capabilities launch * 10:04 — How a dual mandate in security and data helps * 12:35 — How business units get green-lit to build agents * 15:38 — Managing AI governance across 10 regulators * 17:36 — Biggest productivity gain from AI so far * 20:53 — How to detect shadow agent activity in your team #AIAgents #ShadowAI #CISO #EnterpriseAI #AIGovernance

AI Agent Governance at Scale: Stagwell's Marketplace Model | EP27

AI agent sprawl is one of the fastest-growing governance challenges for any organization with multiple teams building agents — and Stagwell solved it by building an internal marketplace. In this episode, Merrill Raman, Global CTO of Stagwell, explains how the company's network of 70+ marketing and advertising agencies build, publish, share, and license AI agents through a centralized Agent Cloud — with real financial incentives for the teams that create them. Merrill explains how Stagwell applies the 80/20 rule to technology standardization, why agent discoverability is the antidote to agent sprawl, and what the emotional journey of AI adoption actually looks like for leaders and their teams. He also shares why you should redesign your workflow before applying AI — not after. Download our AI terminology cheat sheet: [AI Terminology Cheat Sheet link] Talk to an Insight AI specialist because you'll get a direct conversation about how to govern and scale AI agents inside your organization: https://www.insight.com/en_US/what-we-do/expertise/data-and-ai/generative-ai.html [https://www.insight.com/en_US/what-we-do/expertise/data-and-ai/generative-ai.html] Subscribe to Insight On for more conversations on the agent economy. Chapters (5–12) * 00:00 — Welcome and introduction to Stagwell's agent story * 01:12 — How Stagwell started building AI agents * 02:09 — Why 70 agencies need a shared agent foundation * 04:03 — What the Agent Cloud is and how it works * 06:22 — How agencies publish and discover agents * 07:46 — The internal licensing marketplace model * 09:01 — Turning agents into SaaS revenue streams * 11:30 — Agent examples: AI moderator for market research * 13:13 — Keeping humans in the loop at agent scale * 14:00 — AI-driven content personalization workflows * 15:20 — Biggest lessons from the agent development journey * 16:44 — The emotional arc of AI adoption for leaders #AIAgents #AgentGovernance #GenerativeAI #InsightOn

AI Agents Explained: What You Might Be Getting Wrong | EP26

AI agents are in every pitch deck and boardroom conversation — but the definition shifts depending on who's talking. In this episode, Miles Ward, CTO of AI at Insight, draws a hard line between chatbots and agents, explains what agent orchestration actually looks like in production, and gives you the three things you're "out of your mind" not doing right now. You'll learn the two-word test for whether something is actually an agent (persist and act), why headless agents cut cost and latency by eliminating the tokens you don't need, and how Mattel uses agent orchestration to move from quality control signals to supplier corrective action without human handoffs. Download the AI Agent Vocabulary Cheat Sheet: https://www.insight.com/en_US/content-and-resources/guide/the-ai-agent-cheat-sheet.html Explore Insight's Data and AI solutions because you'll see exactly how enterprises are building, governing, and scaling agentic AI in production: https://www.insight.com/en_US/what-we-do/expertise/data-and-ai.html Subscribe to Insight On for weekly conversations with the leaders building what's next. Chapters (5–12) 00:00 — Welcome and episode overview 00:57 — What is an AI agent vs a chatbot 04:33 — Where the line between chat and agent actually falls 05:34 — AI agent orchestration explained 08:12 — Mattel's agent orchestration in production 10:41 — What is an AI harness 13:07 — Headless agents and why they matter 15:31 — Which terms executives need to know now 18:10 — The question clients are too embarrassed to ask 18:30 — Three things every leader must do with AI right now 21:50 — The single most important thing to go do today #AIAgents #GenerativeAI #EnterpriseAI #InsightOn

Lessons from GTT: Essential Moves to Learn Before Scaling Your AI Infrastructure | EP25

Most enterprise AI factory deployments fail before they produce a single result — not because of the technology, but because of what companies skip before they build. James Karimi, CIO and CISO at GTT, shares the governance-first playbook that helped GTT stand up three AI factories across the US, EU, and UK in two months. The results? A two-week finance close reduced to one hour. Recruiters reclaimed 60% of their time in a given week. And that was just the beginning. Karimi breaks down the deliberate six-month pause GTT took after procuring infrastructure — before installing anything — and why that decision is the reason their AI operators are delivering real results today. He also gets into the combined CIO-CISO role, how GTT handled employee fear around AI job displacement with radical transparency, and what edge GPU deployment will look like in 2026 for enterprise network services. If you're evaluating AI factory infrastructure, trying to prioritize use cases, or figuring out how to get your organization to actually adopt AI — this conversation has the specifics. Take the IT Infrastructure Readiness Assessment to see where your organization stands before you build: https://www.insight.com/en_US/what-we-do/expertise/modern-infrastructure/it-infrastructure-readiness-assessment.html [https://www.insight.com/en_US/what-we-do/expertise/modern-infrastructure/it-infrastructure-readiness-assessment.html] Explore Insight's modern infrastructure expertise: https://www.insight.com/en_US/what-we-do/expertise/modern-infrastructure.html [https://www.insight.com/en_US/what-we-do/expertise/modern-infrastructure.html] Subscribe to Insight On for new episodes every week. Jump to… * 00:00 — Introduction and the combined CIO-CISO role * 02:09 — What GTT does and its global network scale * 02:58 — How generative AI disrupted GTT's business * 03:48 — What an AI factory actually is * 05:44 — Early wins from three AI factory deployments * 07:24 — The six-month data governance pause * 09:58 — How GTT prioritizes AI use cases

Stop Replacing Humans With Agents. It Doesn't Work That Way | EP24

Most companies are asking the wrong question about AI — and a Stanford researcher's field work shows exactly where the returns break down. Melissa Valentine, professor at Stanford University, senior fellow at the Stanford Institute for Human-Centered AI, and co-author of Flash Teams, makes the case that AI workflow integration — not better prompting — is what separates real ROI from endless experimentation. In this conversation, Valentine shares findings from her research on why high-impact AI users think like product managers, why the org chart isn't dying but needs to be understood differently in an AI-powered organization, and why the efficiency narrative around AI may be leading organizations straight into the Turing Trap. Subscribe to Insight On for conversations with researchers, practitioners, and business leaders on the technology decisions that shape outcomes. 📖 Read Melissa's research: To Drive AI Adoption, Build Your Team's Product Management Skills: https://hbr.org/2026/02/to-drive-ai-adoption-build-your-teams-product-management-skills [https://hbr.org/2026/02/to-drive-ai-adoption-build-your-teams-product-management-skills] How to Make Enterprise Gen AI Work: https://hbr.org/2025/09/how-to-make-enterprise-gen-ai-work [https://hbr.org/2025/09/how-to-make-enterprise-gen-ai-work] Flash Teams (book): https://www.amazon.com/Flash-Teams-Leading-AI-Enhanced-Demand/dp/0262049848 [https://www.amazon.com/Flash-Teams-Leading-AI-Enhanced-Demand/dp/0262049848] Jump to… 00:00 — Welcome and guest introduction 03:54 — The real reason companies aren't seeing AI ROI 05:18 — The copy-paste trap and integrated workflow problem 09:12 — The product manager mindset for AI adoption 14:18 — Overcoming resistance to workflow change 18:08 — Levels of AI maturity across organizations 25:29 — Is the org chart dying or just changing? 28:29 — Why one-to-one agent replacement is the wrong model 32:11 — What a working agentic system actually looks like 33:36 — Cognitive load and the hidden cost of AI-accelerated work 35:38 — How to bring a CFO along on AI transformation