In this episode, Yasmeen Ahmad, Managing Director of Product Management for Data & AI Cloud at Google Cloud, reveals why 80–90% of enterprise data is "dark" and untouched — and how Google Cloud is building the tools to finally unlock it. Yasmeen shares how BigQuery's new Knowledge Engine captures the invisible business context that human analysts have always carried in their heads, and why this semantic layer is the real unlock for enterprise AI in 2026.

Yasmeen breaks down how enterprises are scaling from 50 to 2,000 autonomous AI agents, why continuous evaluation (not unit testing) is the only way to keep agents trustworthy, and what Google learned from seeing 50% of its own code now written by AI. She also explains why 95% of AI pilots produce zero measurable ROI — and why companies that partner with a platform like Google Cloud see dramatically different results. Plus, her contrarian take on governance: it's not the brake, it's what lets you drive 150 mph into the bend with confidence.

Key Topics Covered

• Why 80–90% of enterprise data is "dark" unstructured data that GenAI can finally unlock
• How BigQuery's Knowledge Engine captures the invisible business context analysts carry in their heads
• The semantic layer: why the next big unlock is context, not just more powerful models
• How enterprises are scaling from 50 to 2,000 autonomous AI agents
• Intent-driven agentic AI: giving agents outcomes instead of step-by-step instructions
• Why continuous evaluation is replacing traditional unit testing for AI agents
• Google's internal AI adoption: 50% of code written by AI, 10% engineering efficiency gains
• Why 95% of AI pilots produce zero ROI and what changes that outcome
• AI governance as an accelerator — the "brakes that let you drive 150 mph" framework
• Why culture and founder mentality matter more than technology budget for AI success

Episode Timestamps

00:00 - Introduction and welcome

00:50 - Being Scottish in Silicon Valley and the power of community

03:13 - The career thread: curiosity, pivots, and getting outside your comfort zone

06:20 - What makes data fascinating: the hidden stories inside numbers

07:48 - Why data is the lifeblood of enterprise AI

10:19 - 80–90% of enterprise data is "dark" and untouched

12:59 - What BigQuery actually does (explained simply)

14:50 - The invisible work: knowledge layers and business semantics

17:38 - The agentic AI moment: agents that think, plan, and execute

20:41 - From 50 to 2,000 autonomous agents inside enterprises

22:07 - Why you can't evaluate AI agents like traditional software

25:46 - Signals of AI readiness: Google's 50% AI-written code and Honeywell's 30% efficiency gains

30:21 - Why 95% of AI pilots produce zero ROI

35:37 - Governance as a speed accelerator, not a brake

39:53 - Who's best poised to win: culture over budget

45:59 - Why do you do what you do?

Yasmeen's Socials:

LinkedIn — https://www.linkedin.com/in/yasmeenahmaduk/

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In this episode, we break down the "Agentic Brain" — the architecture behind AI agents that can think, plan, and execute multi-step workflows with minimal human oversight — and why the agentic AI market is about to explode from $7.8 billion to over $52 billion by 2030. We reveal how the smartest enterprises are already deploying autonomous agents that handle everything from customer service to internal operations, and why only 14% of companies have production-ready agentic solutions despite all the hype.

We go deep on what "bounded autonomy" actually means in practice, how multi-agent systems work (inquiries surged 1,445% in just one year), and why Gartner predicts 40% of enterprise apps will embed AI agents by the end of 2026. We also cover the real-world examples of companies using agents to handle 80% of customer service autonomously, the difference between "agentic AI" and a chatbot with extra steps, and what operators and executives need to understand before deploying agents inside their organizations.

Key Topics Covered

• What the "Agentic Brain" is and how it differs from traditional chatbots and copilots
• Why the agentic AI market is projected to grow from $7.8 billion to $52 billion by 2030
• How multi-agent systems work: planning, reasoning, tool use, and memory
• Why only 14% of companies have production-ready agentic solutions despite massive investment
• The concept of "bounded autonomy" and why it matters for enterprise deployments
• How some companies are already using AI agents to handle 80% of customer service autonomously
• Why multi-agent system inquiries surged 1,445% in one year
• Gartner's prediction that 40% of enterprise apps will embed AI agents by end of 2026
• The difference between real agentic AI and hype — how to tell what's actually production-ready
• What executives and operators need to know before deploying AI agents in their organizations

Episode Timestamps

00:00 - Introduction and meet the Agentic Brain team

00:39 - Today's agenda: three practical AI agents

01:09 - Agent 1: Personalized learning agent

03:05 - How the learning agent works

09:25 - Live demo: testing the learning agent

16:50 - Future of personalized learning with AI

24:51 - Agent 2: Sales analysis agent

28:31 - Demo: Sales performance dashboard

32:41 - Call quality and feedback analysis

46:18 - Real-world impact: proactive team management

49:26 - Agent 3: Customer service agent

50:52 - Multi-agent systems and scaling

78:55 - Closing remarks and thanks

Partner Links

Work with Agentic Brain — https://cal.com/forms/44f75adf-4741-4c5e-88d5-3249592ada99

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This week on AI News in 5: OpenAI kills Sora just six months after launch — blindsiding Disney and losing a billion-dollar deal. Amazon drops $50 billion on OpenAI, putting Microsoft on the warpath. Apple dumps OpenAI and partners with Google to rebuild Siri. OpenClaw becomes the fastest-growing open-source project in history. And a hacker infects a popular AI tool downloaded 3.4 million times a day.

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About The AI Why with Liam Lawson:

The AI Why breaks down what's actually happening in AI — who's building it, how it's being implemented at scale, and why the people building it do what they do. New episodes every Tuesday (AI News in 5) and Thursday (founder and exec interviews).

In this episode, Brian Alvey, CTO of WordPress VIP (Automattic's enterprise platform), reveals how the platform powering NASA, CBS, NBCUniversal, Rolling Stone, Samsung, and the White House is integrating AI into enterprise publishing at massive scale. Brian shares how he's built over 24 content management platforms throughout his career — and why the current AI moment is the most transformative shift he's ever seen in publishing technology.

Brian breaks down how WordPress VIP is embedding AI into tools like Parse.ly to give editors conversational content insights, how their AI-powered "editorial recipes" turn hours of manual headline testing and cross-linking into minutes, and how a new tool called Tollbit lets publishers actually charge AI crawlers for accessing their content. He also shares his philosophy on keeping humans in the loop at enterprise scale, how 200-person newsrooms and 11,000-contributor content teams are navigating AI adoption, and why the open web matters more than ever when everyone's fighting for attention in an AI-first world.

Key Topics Covered

• How WordPress VIP powers mission-critical content for NASA, CBS, the White House, and hundreds of enterprise brands
• Brian's journey building 24+ content management platforms and what he's learned about great CMS architecture
• How WordPress VIP takes open-source WordPress and locks it down with enterprise governance for massive newsrooms
• The AI tools WordPress VIP is building: conversational analytics, headline testing, engagement optimization, and automated cross-linking
• How Tollbit lets publishers charge AI companies for crawling their content — a new revenue stream for media
• What "human in the loop" actually means when you're managing 11,000 contributors
• The Agentforce integration with Salesforce: bringing AI-powered chat and lead generation directly into WordPress sites
• Why the open web still matters in the age of AI and how publishers are fighting back
• How enterprise publishing teams are adopting AI without sacrificing editorial quality
• Brian's honest take on where AI helps editors vs. where it still falls short

Episode Timestamps

00:00 - Introduction and welcome

00:35 - Brian's career building publishing platforms before Google existed

03:22 - AI as an equalizing paradigm shift

07:20 - Generalist superpower: bridging art and science

09:46 - Human skills vs AI: lessons from The Founder

13:36 - Career advice for his kids in the AI era

16:01 - WordPress VIP and enterprise publishing at scale

18:28 - Core mission: speed and stability without breaking things

23:06 - AI content intelligence tools and MCP adapters

28:39 - Media business fundamentals: attention and monetization

35:27 - Customer segments and AI crawler strategies

40:12 - Trust and credibility in the AI-generated content era

44:25 - From competing against WordPress to leading it

48:15 - Obsession with automation and future of work

51:51 - Building products in days with AI tools like Claude

56:47 - What truly drives him

58:40 - Closing and where to find Brian

Brian's Socials:

LinkedIn — https://www.linkedin.com/in/brianalvey/

Website — https://brianalvey.com

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Apple confirms Google Gemini will power the new Siri — dropping OpenAI as the default on a billion devices. GPT-5.4 Thinking becomes the first AI to beat the human baseline at navigating a computer. Yann LeCun raises $1.03B in the largest seed round in European history to build a new kind of AI. Robotics companies pull in $1.2B in a single week. And the U.S. Department of Energy puts $293M behind AI for national challenges.

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About The AI Why:

The AI Why breaks down what's actually happening in AI — who's building it, how it's being deployed, and why the people building it do what they do. New episodes every Tuesday (AI News in 5) and Thursday (founder and exec interviews).

In this episode, Michael J. Domanic, VP and Head of AI at UserTesting, reveals how he drove 70%+ weekly AI adoption across the entire company — turning UserTesting into one of the most AI-mature enterprises in the market. Michael shares why most enterprise AI rollouts fail, and the exact playbook he used to get hundreds of employees building custom GPTs and integrating AI into their daily workflows.Michael breaks down how UserTesting moved from Phase 1 (culture change and grassroots adoption) to Phase 2 (agent orchestration and scaled automation), how he built the governance frameworks that let teams experiment safely without creating chaos, and why the companies that treat AI adoption as a culture problem — not a technology problem — are the ones winning. He also shares his honest take on why AI projects consistently miss expectations and what leaders need to do differently in 2026.Key Topics Covered- How UserTesting achieved 70%+ weekly AI adoption across the entire organization- Why most enterprise AI projects fail to meet expectations — and the root causes leaders miss- How employees built hundreds of custom GPTs for internal workflows without a top-down mandate- The Phase 1 to Phase 2 transition: from culture change to agent orchestration- Building AI governance frameworks that enable experimentation without creating risk- Why treating AI adoption as a culture problem (not a tech problem) is the key to success- How to get executive buy-in for enterprise-wide AI transformation- What "AI maturity" actually looks like inside a real company- Michael's predictions for how agentic AI will reshape enterprise operations- The skills leaders need to drive AI adoption in their organizations*Episode Timestamps*00:00 - Introduction and welcome01:31 - Michael's career background and life journey08:08 - Why AI transformation is about creativity, not technology10:43 - Hiring the right AI transformation leaders14:07 - Building Centers of Excellence for AI17:36 - What UserTesting does and Michael's role32:55 - Achieving 70%+ AI adoption across the company35:41 - How employees built hundreds of custom GPTs39:16 - OKR methodology and governance frameworks43:50 - Creativity as the fundamental skill for future work48:39 - Phase 2: Agent orchestration and advanced AI56:46 - Outlook: Optimism about AI's future impact59:27 - Closing: How honest conversations drive progressMichael's Socials:LinkedIn — https://www.linkedin.com/in/michaeldomanic/Partner LinksBook Enterprise Training — https://www.upscaile.com/Subscribe to our free newsletter — https://newsletter.theaireport.ai/subscribe

This week: OpenAI's Pentagon deal sparked the #QuitGPT movement with 2.5 million supporters, Anthropic got labeled a supply-chain risk by the DOD, AI-driven layoffs hit Oracle and Block hard, NVIDIA teased its biggest GTC yet, and Apple revealed a $599 AI laptop.

Key Topics Covered

• OpenAI's classified Pentagon deal sparks #QuitGPT revolt with 2.5M supporters and 295% surge in ChatGPT uninstalls
• Pentagon labels Anthropic a supply-chain risk; OpenAI and Google employees rally behind Anthropic in court
• Oracle eyes 30,000 layoffs and Block cuts 40% of workforce as AI replaces jobs at scale
• NVIDIA GTC 2026 preview: $26B open-source investment, new inference chip, and enterprise AI platform expected
• Apple announces rebuilt Siri with Google Gemini and the $599 MacBook Neo AI laptop

Episode Timestamps

00:00 — OpenAI's Pentagon Deal and the #QuitGPT Revolt

01:00 — Pentagon vs. Anthropic: The Supply-Chain Risk Showdown

02:00 — AI Layoffs Hit Oracle, Block, and Atlassian

03:00 — NVIDIA GTC 2026: The Super Bowl of AI

04:00 — Apple's Mass-Market AI Play

About The AI Why

The AI Why with Liam Lawson covers enterprise AI — how it's being implemented at scale, and why the people building it do what they do. New episodes every Tuesday (weekly news in 5 minutes) and Thursday (hour-long interviews with founders and C-suite execs).

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