Framework Seer Labs IP
A framework derived from 50+ enterprise surveys — MIT, Deloitte, McKinsey, EY, WEF, IDC. Most training programs only address Gap 1. Seer Labs addresses Gaps 2 through 5.
01 The problem
of organizations have AI tools
Multiple (Deloitte, McKinsey)
of workers actually use AI day to day
Multiple
of AI initiatives fail to deliver measurable impact
MIT
The problem isn't a shortage of tools. The problem is that organizations treat AI adoption as a content challenge when it's actually a workflow challenge. They push courses before diagnosing their work environment. The result is awareness without capability.
"Access to training does not automatically translate into capability. Most organizations are not failing to offer AI training — they are failing to design it effectively."
02 The five gaps
From "AI exists" to "I understand what it does"
of data leaders say employees need AI literacy upskilling
Informatica CDO Survey (600 leaders)
What's happening
Most employees know AI exists but can't articulate how it applies to their work. This is the gap generic AI courses target.
How we address it
We don't compete here. Coursera, Udemy, LinkedIn Learning, and vendor webinars all address this gap reasonably well. Start there if you need it.
From "I understand it" to "I can use it in my work"
of employees feel sufficiently trained on AI
EY, 2025
What's happening
Even people who understand AI concepts can't apply them to daily tasks. An accountant needs anomaly detection in spreadsheets; a marketer needs ideation flows; an ops lead needs workflow automation. Generic training misses this entirely.
How we address it
Role-specific, hands-on training built from the audit's workflow map. Every exercise uses the team's real data and tools.
From "I can use it" to "My team works with AI together"
of executives report friction between IT and business units on AI
Deloitte State of AI Enterprise (3,235 leaders)
What's happening
Individual skill doesn't translate to team-level workflow integration. 72% observe AI applications being developed in silos. Without coordination, you get a small number of power users and a large number of bystanders.
How we address it
Cross-functional workshops, manager enablement tracks, and explicit workflow redesign. We teach teams to redesign how work moves — not just to use better tools.
From "It works in a pilot" to "It works at scale"
of companies have AI agents deployed in production
Deloitte State of AI Enterprise 2026
What's happening
Nearly two-thirds of organizations are stuck in the pilot stage. The leap from "it works in a demo" to "it works at scale" requires automation infrastructure, not more training.
How we address it
Automation sprints — we build the automations the team identified during training but can't build themselves. Training ensures they know what's realistic and can maintain what you build.
From "We use AI" to "We trust and govern AI"
of companies are confident in their AI governance
Informatica
What's happening
Blind trust without understanding is dangerous. Employees worry: if AI hallucinates and they relied on it, who gets blamed? If nobody owns the risk, teams default to the old way of working.
How we address it
Governance literacy embedded in every training track. Clear ownership of decisions. EU AI Act literacy for companies with European exposure. The retainer keeps this current as AI evolves.
03 Why most training fails
Teach awareness. One-size-fits-all. 7 in 10 employees ignore them. No measurement. Stops at Gap 1.
$500K+ engagements. Strategy decks, not capability. Addresses Gaps 3-4 at the board level but leaves individual contributors untouched.
Teaches their tool. No workflow integration. No change management. Gap 1 through the lens of one product.
One-time events. No methodology. No measurement. No ongoing enablement. Capability doesn't compound.
Your next step
Start with the Audit. 1 to 2 weeks. $3K to $5K. Fixed scope.
Free · No commitment · No credit card