Adoption & Organizational Change
28How organizations adopt AI tools, manage change, and measure impact
Adoption & Organizational Change
The Product Impact Podcast on why AI adoption actually fails — and the behavioral, organizational, and cultural work that makes it stick.
Hint: the problem is rarely the technology.
The Position
The data is consistent and damning. MIT found that 95% of enterprise GenAI investments show zero measurable financial return. Forrester projects 25% of planned 2026 AI budgets will be deferred to 2027. 42% of companies scrapped the majority of their AI initiatives last year. And yet the products work — Copilot, Rovo, Glean, Harvey, Einstein, Claude, ChatGPT all function as advertised when used.
The gap between deployment and value is the behavioral layer — the moment-level decisions employees make about whether to integrate AI into their workflow. That layer is where most adoption strategies fail because most adoption strategies don't even observe it.
The Product Impact Podcast's position on adoption:
- Adoption is a behavioral problem, not a technology problem. Training, licenses, and dashboards don't move adoption numbers. Peer influence, visible success, and workflow redesign do.
- The champions trap is real. Early adopter enthusiasm hides the fact that the rest of the organization never changed. Your pilot metrics are lying to you about production readiness.
- The median pull is the invisible cost. Heavy AI use is converging people's thinking. Teams that look productive may be losing the cognitive diversity that produces breakthroughs.
- Adoption is measurable — but not by utilization. Login rates, feature adoption, and session counts measure exposure, not integration. The real signal is whether anything about how people work has actually changed.
- Cognitive Sovereignty — The ability to remain the author of your own thinking when AI is in the loop. The framework for telling productive adoption from passive consumption.
- The Median Pull — How AI tools cause their users' work to converge. The most underrated risk in any large AI rollout.
- Helen Edwards — Co-founder, Artificiality Institute (S02E05)
- Dave Edwards — Co-founder, Artificiality Institute (S02E05)
"AI was pulling everyone into a median position, into a common position. So there's less exploration that happens when we use AI. People are becoming more like each other. They sound like each other. They sound like the models."
— Helen Edwards, S02E05
- AI Product Strategy — Strategy decisions that determine whether adoption is even possible
- Governance, Risk & Trust — The accountability layer adoption depends on
- Evaluation & Benchmarking — How to measure whether adoption actually delivered value
Articles
28
OpenAI & Anthropic are charging us way more than we need

WTF is an AI-native org anyways? Let's compare Airbnb & Meta's opposing plans.

Playbook for Knowledge Workers to Survive the AI Jobpocalypse

The Browser Is the New Battleground: How AI Is Moving Out of Chat and Into Your Life

Context Models Are the Unlock to Consistent AI Value

What UX Research Looks Like When Context Becomes the Engine

Team Work Is About to Transform and Atlassian Is Leading the Charge

The AI Job Apocalypse Won't Happen. Here's What Will.

Every CEO Will Post a Layoff Notice Like This. Here Is Why.

The Cognitive Shift Every UX Researcher Needs to Make

The UX Researcher's Guide to Claude, Claude Cowork, and Claude Code

Meta Is the Cautionary Tale About AI Every Founder Needs to Remember

The 10% Problem: AI's Value Gap Is Wider Than Anyone Is Admitting

The Free Ride Is Over: AI Economics Is Now Your Most Important Strategy Decision

Stanford's AI Index Proves the US Can't Buy Its Way to an AI Lead

Stanford's 2026 AI Index Just Dropped. Here Are the Numbers Product Leaders Need.

97% of Executives Deployed AI Agents. Only 29% See ROI. The Gap Is the Story of 2026.

What AI Does to Human Thinking: Cognitive Sovereignty, the Median Pull, and Why It Matters for Product Teams

The Agentic Era: What AI Agents Are, How They Change Work, and Why 94% of Organizations Aren't Ready

Enterprise Context Is the AI Moat Nobody Built: Knowledge Graphs, Taxonomies, and Why Models Aren't Enough

Microsoft's Copilot Problem Isn't Adoption. It's Coerced Adoption.

HSBC's Chief AI Officer Starts This Week. So Do 46 Others. Most Will Quit Before 2028.

Chief AI Officer Hirings Hit Record in Q1 as Enterprise AI Budgets Tighten

How to Measure AI Product Impact: The Bullseye Framework for Power, Speed, Impact, and Joy

$650 Billion in Capex, $14 Billion in Losses: What Q1 2026 Means for AI Builders

20 AI Product Podcasts Worth Your Time If You're Scaling LLM Capabilities

Four Enterprise Agentic AI Failures Disclosed in Q1 as Gartner Warns 40% Cancellation Rate
Episodes: Adoption & Organizational Change
208. The Most Important Data Points in AI Right Now
18:157: $490 Billion in AI Spend Is Delivering Nothing — Orchestration Is the Fix
29:216. Robert Brunner Was the Secret to Beats' & Apple's Success — Now He's Redefining AI for the Physical World
44:415. The Human Impact of AI We Need to Measure [Helen & Dave Edwards]
57:244. The AI Agent Era Will Change How We Work
46:563. Win The AI Context Wars — Unlock The Value of Data [Juan Sequeda ]
52:011. Why Your AI Metrics Are Lying to You - Framework for improving AI product performance
35:00Why Design of AI is becoming the Product Impact Podcast
16:0652. Clawd Bot & Moltbook: When Demos Hijack Reality [Jim Love]
43:0151. Agents Will Disrupt Search & Shopping [Devi Parikh, CEO Yutori, ex Meta
42:5950. Designing AI for 2026: Trust, Cost, Orchestration [Yaddy Arroyo]
44:3249. AI Was Supposed to Help Humans. What Happened? [Ovetta Sampson]
48:1446. The AI Commercialization Playbook: Stop Selling Tech, Start Delivering Value [Jessica Randazza Pade, Neurable]
44:3045. Agentics: Rebuilding How We Think, Work, and Create with AI [Kwame Nyanning, Author of Agentic]
44:5543. Play Unlocks the Next Billion‑Dollar AI Market [Michelle Lee, IDEO]
41:4742. HubSpot’s Head of AI on How AI Rewrites Customer Acquisition & Marketing
45:4538. Co-Designing the Future of AI Products [Savannah Kunovsky, IDEO]
33:5230. Take Control of AI’s Predictive Power [Tyler Hochman, FORE]
49:3927. Implementing AI in Creative Teams: Why Adoption Will Surge [Jan Emmanuele, Superside]
58:2025. Faster, Cheaper, Better: AI’s Transformation of Insights & Strategy [David Boyle, author of PROMPT]
53:14Featured People
Arpy Dragffy
Arpy Dragffy is the founder of PH1 Research, a 14-year-old product strategy and AI value consultancy, and co-host of the Product Impact Podcast. His work focuses on the gap between AI deployment and AI-driven outcomes — measuring it, closing it, and helping product teams ship AI that compounds rather than decays.
Juan Sequeda
Principal scientist at ServiceNow and co-founder of data.world (acquired by ServiceNow). Leading researcher in knowledge graphs, semantic data management, and enterprise context infrastructure for AI. Juan's research demonstrated that LLM accuracy increases dramatically when knowledge graphs provide structured business context, a finding that catalyzed the industry's focus on context over capability.
Organizations
Gartner
Technology research and advisory firm. Gartner predicted that over 40% of enterprise agentic AI projects will be canceled by end of 2027 and that traditional search engine volume would drop 25% by 2026 due to AI chatbots.
Microsoft
Global technology company and developer of Microsoft 365 Copilot, the most widely deployed enterprise AI assistant with 15 million paid seats. Microsoft's March 2026 Copilot reorganization under Jacob Andreou signals a shift toward specialized AI products.
