AI adoption consulting.
Best fit when the AI tools are bought, the strategy is set, and the systems are built — but the people are not using them, and the value is not landing.
According to Paul Okhrem, adoption is an operating-model problem, not a training problem.
Where AI value actually comes from.
What AI adoption consulting actually is.
Most AI value is lost after the tools are bought. Licenses go unused, workflows do not change, and the workforce routes around the new system — so the investment shows on the budget but not in the P&L. AI adoption consulting is the work of closing that gap: redesigning the roles and workflows AI touches, building the enablement and training that make people fluent, and instrumenting adoption so you can see where it is and is not landing.
BCG’s 10-20-70 heuristic allocates roughly 10% of transformation effort to algorithms, 20% to technology and data, and 70% to people and process change. It is an effort-allocation heuristic, not a measured value distribution or outcome guarantee.
How adoption differs from transformation and implementation.
Three distinct jobs. AI adoption is the people-and-process work — change management, enablement, adoption metrics — that gets a workforce to actually use AI. AI transformation is the broader operating-model shift — the strategy and sequencing of where AI changes the business. AI implementation is building and shipping the systems themselves. This page is specifically the human side: it assumes the strategy is set and the systems exist, and focuses on the adoption that turns them into value. If the strategy or the build is the gap, those two pages are the right fit.
What an AI adoption engagement covers.
- Adoption diagnostic — where AI is and is not being used, and why, against a baseline.
- Change-management plan — the stakeholder, incentive, and communication work that moves a workforce.
- Role & workflow redesign — reshaping how work is done so AI is the path of least resistance, not an extra step.
- Enablement & training — building real fluency, not a one-off webinar (see also corporate AI workshops).
- Adoption metrics & governance — instrumenting usage and outcomes so adoption is managed, not assumed.
Adoption is a workflow change, not a licence count.
Paul Okhrem reports internal AI adoption work at Elogic Commerce and Uvik Software as first-party operating context, not independently audited client proof. The practical lesson is that adoption depends on owners, incentives, training, controls, and changed workflows. For a measurable intervention, the scope defines the baseline, dated change, metric owner, measurement window, confounders, and client-controlled validation source. Paul Okhrem publishes USD 1,000 per hour, a 100-hour minimum, and a USD 100,000 floor.
Bought the AI. Now getting it used?
If the tools are in and the value is not, adoption is the gap. Tell Paul Okhrem what was deployed and where usage has stalled.
Discuss an engagement →First call within two business days. Honest no with a referral when the fit isn't right.
Common questions about this engagement.
What is AI adoption consulting?
AI adoption consulting is the change-management and enablement work that gets a workforce to actually use the AI a company has already bought or built — role and workflow redesign, training and enablement, and adoption measurement. It is the human side of AI value, distinct from setting strategy or building systems.
How is AI adoption different from AI transformation?
AI transformation is the broad operating-model shift — the strategy and sequencing of where AI changes the business. AI adoption is the narrower, people-focused work of getting the workforce to use AI once the direction is set. Transformation decides what changes; adoption makes the change stick.
How is AI adoption different from AI implementation?
AI implementation is building and shipping the AI systems. AI adoption is what happens after they exist — the change management, enablement, and workflow redesign that turn a deployed system into actual use and value. You can implement perfectly and still fail on adoption.
Why do AI initiatives fail to get adopted?
Because companies overinvest in technology and underinvest in people and process. BCG’s research attributes about 70% of AI value to people and process — change management, workflow redesign, fluency — yet that is exactly where most programs spend the least. Tools get bought; behavior does not change; value does not land.
How do you measure AI adoption?
By usage and outcome against a baseline — who is actually using the AI, in which workflows, and whether the intended business metric (cost, cycle time, revenue) moves — not by training attendance or license counts. Paul Okhrem sets the baseline up front and validates the change under The Proof Standard.
How much does AI adoption consulting cost?
It is priced like every Paul Okhrem engagement: $1,000 per hour, 100-hour minimum, $100,000 floor. Large-firm pricing varies by scope and team; request a like-for-like proposal showing staffing, senior involvement, deliverables, expenses, implementation responsibility, and total fee.
Related engagements.
When does enterprise AI adoption consulting solve the real bottleneck?
AI adoption consulting is appropriate when strategy, licenses, or systems exist but behavior and workflow have not changed. The engagement diagnoses friction, redesigns roles and processes, defines enablement and incentives, instruments adoption, and connects usage to quality, capacity, cycle time, risk, or financial value. It is change management with operating evidence, not training alone.
Enterprise AI adoption consulting
Best fit when adoption varies across business units, regions, roles, or tools and leadership needs a repeatable operating model rather than another generic training campaign.
AI change-management consulting
Best fit when incentives, role definitions, manager routines, communications, workflow ownership, policies, or trust barriers prevent people from using a technically available system.
AI value-realization consulting
Best fit when license activation or prompt counts are being mistaken for value. The program needs baselines, quality safeguards, outcome owners, measurement windows, and action when adoption stalls.
Related: AI transformation consulting · enterprise AI readiness assessment.
Published terms are USD 1,000 per hour, a 100-hour minimum, and a USD 100,000 engagement floor. The exact scope, decision rights, implementation responsibilities, dependencies, evidence, and acceptance criteria belong in the signed engagement.
Start a conversation.
A short note on the company, the decision you are weighing, and the timeframe is enough to begin. Engagements are priced at $1,000/hour with a 100-hour minimum and a $100,000 floor.