Your tech team shipped the future. Your people got a login and a thirty-minute training video. Somewhere between the two, the adoption numbers stopped moving. That's where I come in.
Keith Anderson
Everyone nodded in the all-hands. Two months later, the usage dashboard tells a different story. Your best people are still doing things the old way. The champions you appointed are burning out answering the same five questions. This isn't new. I've watched it happen at Google, at Meta, at DoorDash. Same pattern every time.
74%
of organizations fail to scale AI value
BCG AI at Work · 2025
6%
changed how they work, out of the 88% that bought the tools
McKinsey State of AI · 2025
63%
say the hardest part is human, not technical
Prosci · 2024
Fifteen years of being the person who knows the answer. Then a tool shows up that can do it in ten seconds. The resistance you're seeing isn't about the tool. It's about identity. Nobody talks about that part in the rollout plan.
A finance analyst and a customer success rep have nothing in common on a Monday morning. AI 101 gives them the same video. Then everyone wonders why nothing changed.
Right now, that manager has no idea what "good" looks like. Neither does their team. This is the layer every adoption program skips. It's also the layer where adoption actually lives.
The tools aren't the problem.
The people aren't the problem.
The gap between them is the problem.
“The people being asked to change already know what's happening. They're waiting for someone to say it out loud.”
You've tried the obvious things. Here's why they didn't land.
Built for ERP rollouts in the 1990s. Excellent at installing technology. AI adoption isn't an installation. It's asking people to rethink what makes them valuable.
Different problem. Different tools.
Excellent at slide decks for the board. Not set up to sit with a finance analyst on a Tuesday morning and figure out which parts of their work actually get better with AI.
That's a different trade.
Not their fault. They were built for training rollouts, compliance, leadership development. AI adoption showed up and asked them to be behavioral scientists overnight. Usually after the tools already shipped.
I've been inside L&D at five of the biggest tech companies. I know where the gap is.
Free. Technology-centric. Written by the people who built the tools, for the people who will buy more of them.
If they were enough, you wouldn't be reading this.
The gap between the tools and the people is where I work.
The Activation Architecture™
People adopt when they see a reason that matters to them personally. Not because leadership said so, but because someone answered the question they were actually asking: what happens to my value?
People adopt when AI is woven into the workflow, not stacked on top of it. If using the tool means an extra step, an extra login, or an extra decision, they'll skip it by Tuesday.
People adopt when the work itself reminds them to use it. Built into the meeting, the template, the handoff. Not a Slack reminder. Not a training follow-up. The rhythm of the job.
The Activation Architecture is built on decades of behavioral science from BJ Fogg, James Clear, and Daniel Kahneman, adapted for the specific problem of enterprise AI adoption.
Same method. Different depth.
Tier 00 · Free
Free~3 minutes
Take the AuditTier 01 · Diagnose it
From $5,0002–3 week sprint
Let's scope itTier 02 · Build it
On request60–90 days
Request detailsTier 03 · Stay for it
On request6–12 month minimum
Request detailsFortune 500 · Financial Services
Proprietary internal GenAI product rolled out advanced tooling, but no adoption plan until after launch. We sequenced needs by role in one week, then implemented The Activation Architecture. Everything else followed.
Mid-Market · Media · 350+ employees
ChatGPT Enterprise at 19% active use. Tool didn't fit how three key revenue teams worked. Redesigned the work, not just the training. Adoption followed.
Transportation · 2,500+ employees
Used Keith's 2nd Brain Mapping Architecture to gain best of skills from top performers. This increased effectiveness by 34% for on-the-job operators using role-specific AI tools.
When Keith joined, it was the first time my team had our voices heard. That's when things started to shift.Kelly G. Senior Marketing Manager · Capital One
We went from arguing about adoption metrics to watching them move. He made both sides feel heard, then got out of the way.Hoang N. Chief Technology Officer · Travel Weekly
Only consultant I've worked with who took time to really understand the needs from top to bottom.Ray H. Senior Head of Human Resources · BART
I started as a high school English teacher. I say that because it matters. Before I ever touched a Copilot dashboard, I spent years in rooms where you had to earn people's attention every single day, and where nothing you said mattered until the people in the seats believed it would help them.
Then a decade in tech. IC at Google, YouTube, Uber. L&D leadership at Meta, DoorDash, a few startups. VP before I left. At every single one, the same pattern: leadership ships a new technology, puts it on everyone's desk, and waits for behavior to change. It almost never does. Not because the people are resistant. Because nobody translated.
Leaders need someone who will tell them what their workforce is actually thinking. Employees need someone who will tell them what leadership is actually asking for. That translator didn't exist as a job title. So I made it one.
A LinkedIn Live series
Conversations with leaders, practitioners, and people figuring out what AI integration looks like in practice. Not in theory. Not in ten years. Right now, in their role, with real constraints and real decisions.
See the showThree minutes. Seven questions. You'll see where your rollout actually sits and what's most likely blocking it. Report goes to your inbox. No call. No sequence. If I'm the right fit for what comes next, we'll know.