Turn AI opinions into an AI plan.
The hard part of AI strategy is deciding where to start and who leads it. We tell you plainly where you stand, give you a short list of what’s worth doing, and put senior people alongside your team until the work is done.
A 30-minute conversation with a partner, with no commitment.
Sound familiar?
The tools are licensed. A few teams are moving fast, most are waiting for permission, and some are using tools nobody approved. Your board asks for the AI strategy, and what you have is a list of pilots. Finance asks what all of it is returning, and nobody can say.
You need a plan that shows where the returns are, what each idea risks, and who leads it.
Most AI strategies stall after the offsite
Between the offsite and the operating plan, priorities go without owners, business cases go without numbers, and budgets fund pilots but not the rollout after them. We weigh every bet on return and risk, then set up the decisions that move the best ones forward.
Three offerings, one question each
AI Maturity Diagnostic
Where do we stand, and what should we do first?
A structured baseline of your people, processes, data, and governance, scored across the organization. We turn it into a roadmap ranked by expected return, effort, and risk.
Start here if leadership is debating priorities without shared facts.
AI Offering and Revenue Strategy
How does AI change what we sell, and how we charge for it?
For professional services firms. We find where AI changes your services, pricing, and talent model, estimate which new offerings will pay back fastest, and help you win that revenue before a competitor does.
Start here if clients are asking why they still pay for hours AI now does in minutes.
AI Strategy Office
Who owns our AI strategy week to week?
Senior strategy leaders join your leadership team for a fixed term and a set number of hours each week. Between board meetings they run the roadmap, track returns, and move investment toward what’s working. You set the priorities, and a midpoint review rebalances the work.
Start here if AI strategy belongs to someone who already has a full-time job.
The work between the plan and the results
What happens after the plan is written.
Start from evidence.
We measure how your people use AI today, so priorities are set from data instead of by whoever argues hardest.
Put a number on it.
Before you invest, every priority gets a value case your CFO will sign: costs, expected returns, and the measures that prove them.
Weigh return against risk.
For each bet we show the possible return, what could go wrong, and which risks fall within your guardrails, so priorities get through review.
Name an owner for every priority.
Each initiative gets a named person, a date, and a budget line.
Connect strategy to delivery.
Priorities go straight to our own enablement and engineering teams to deliver.
Prove the return.
A re-score of the Diagnostic, read against the value measures set at the start, shows leadership what changed and what it was worth.
We package the roadmap, value cases, decision frameworks, and board materials so your team can run them without us.
Strategy in practice
We started with a firm-wide AI training session and four weekly coaching sessions on the firm’s own tools. Then we met firm leadership to recap what we heard in those sessions and scope the next phase.
A short AI maturity self-assessment that gave IT leadership a de-identified baseline and set the depth of training for each person.
An executive program that began with a private 1:1 with every leader, so the strategy was built on what each of them needed.
Ongoing AI coaching for one office twice a month, in person and virtual, with a monthly report on adoption, the use cases found, and the champions who have emerged.
Frequently asked questions
Where are you with AI?
Pick the closest one. We’ll start from there.
Make your next AI decisions with us.
A 30-minute briefing is enough to talk through where you stand and where your biggest returns are likely to be.
You’ll talk with a partner, and there’s no commitment.