Foundational Program

AI Integration Blueprint

Strategy and planning for where to start with AI

A focused, milestone-paced planning engagement that answers four questions at once: what our rules are, where our team actually is with AI, why we're doing this, and which three to five opportunities to fund first.

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What You Walk Away With

Four deliverables, each one usable on its own the day the engagement ends.

An AI Governance Framework Your Organization Owns

Anchored to the NIST AI Risk Management Framework and written as your internal policy, not our deliverable: approved tools, a four-tier data classification model with permissible-use rules for each tier, a request-and-escalation path for new tools, and an oversight committee with incident reporting and a review cadence. It arrives on a plain document your team adopts under its own letterhead.

An Honest Read on Where Your Team Actually Is

An anonymous 10–15 minute survey across the whole organization: comfort level, which tools people really use at work versus at home, what they use AI for, their biggest time-sinks, what's holding them back, and their appetite for more. Segmented by function, so you can see which teams are ready now and which need something else first.

One Shared "Why" — At the Leadership Level and at the Desk

Every leader answers the same prompt privately before the group meets, so the synthesis starts from the team's real range of views instead of the loudest voice in the room. We work those inputs into a single "why," stated two ways: the organizational case, and the version an individual contributor actually feels.

A Board-Ready Roadmap

Three to five validated opportunities, prioritized and sequenced. Each is written as a fundable pilot: the business metric it moves and its time-to-value, success criteria and how you'll measure them, what it takes to build and run, its governance review, its adoption plan, and its dependencies. Enough to make a funding decision on.

Our Approach

Three milestones, paced to your leadership's availability. Milestone-driven, not calendar-driven — we're after a set of outcomes, not a finish date.

1

Orient & Align

A kickoff working session sets objectives and the metrics that most need to move. Each leader then submits independent, private input on the "why" and where the leverage sits, which we synthesize into one shared answer. Running in parallel: the org-wide survey, a usage baseline pulled from your actual AI tooling, and a scan of your current governance and tool posture.

2

Find the Leverage

We map your priority metrics down to the processes that drive them, then run working walkthroughs with process owners and frontline contributors and review the data behind those metrics. Every candidate is ranked by frequency, effort, and impact, and classified as automation (repetition is the constraint) or enablement (fluency is the constraint) — with an honest read on where teams actually have capacity.

3

Synthesize & Decide

We design each validated opportunity against a specific bottleneck, sequence them against your capacity read, and finalize the governance framework. It ends in a live leadership session where you decide what gets funded and what goes first.

What You Get

The Blueprint document, your AI governance framework, the survey instrument and its results, and the ranked workflow inventory behind every recommendation.

Best For

Organizations that want a board-ready picture of where to start, what it's worth, and how to do it responsibly — before committing budget to a build or a training rollout.

What We Need From You

Executive sponsorship and a named internal coordinator. Your leadership team for the kickoff, the independent input, and the final decision session; process owners and a few frontline contributors for the operational deep-dives; 10–15 minutes from the broader organization for the survey; and access to the data behind your priority metrics. No prior fluency required—the Blueprint establishes the baseline everything after it builds on.

What is an AI Integration Blueprint?

A strategy and planning exercise that gets your organization to a rigorously built plan for using AI responsibly: the rules you'll work within, an honest read on where your people are today, leadership agreement on why it matters, and three to five opportunities in priority order, each specified well enough to fund.

Most AI programs stall because building starts before anyone has agreed on the rules, the reason, or the return. The Blueprint closes those three gaps first, then hands you a sequenced list of what to build. It plans the work; it doesn't perform it — the building and the training happen in the programs that follow.

Will people answer the survey honestly?

Only when anonymity is real and felt. The survey runs inside your own environment, with name recording turned off, and it asks the "about you" questions last — after every substantive answer is already given, so nobody can be triangulated from their responses. We state a minimum reporting group size to respondents in writing, and we commit to sharing the results back with them.

That design is what produces candid write-in answers rather than a performance. It also separates two very different problems that look identical from the executive floor: people who are held back because the rules are unclear, and people who genuinely don't want to use AI. The first is an enablement problem you can solve in weeks. The second isn't.

What makes the roadmap board-ready?

The unit of the roadmap is a fundable pilot, not an idea. Each opportunity carries:

  • The business metric it moves, and its time-to-value
  • Success criteria and how you'll measure them, including a minimum viable threshold
  • What it takes to build and run — tools, systems, access, and people
  • A governance and risk review against the framework you just adopted
  • An adoption and change plan
  • Its dependencies and prerequisites

Getting there means ranking candidates honestly. Every workflow we surface is scored on frequency, effort, and impact, then classified: automation, where repetition is the constraint, or enablement, where fluency is. The two need different investments, and conflating them is the most common way an AI budget gets spent without moving a number.

How long does it take, and what does it ask of your team?

Three to six weeks, paced to milestones rather than the calendar. The variable is leadership availability, not our capacity — the sessions that produce alignment can't be rushed or delegated.

What we need: your leadership team for the kickoff, the independent input, and the final decision session; process owners and a few frontline contributors for the operational deep-dives; 10–15 minutes from the broader organization for the survey; and access to the data behind your priority metrics.

What happens after the Blueprint?

The Blueprint is the on-ramp, and it produces the business cases that fund what comes next. Depending on what the Blueprint finds, that's usually one of three paths — or a combination:

Key Takeaways

  • The Blueprint answers four questions before you spend build budget: what the rules are, where your team actually is, why you're doing this, and what to fund first.
  • The governance framework is written for you to adopt as your own internal policy, anchored to the NIST AI Risk Management Framework.
  • Leaders give their input independently before the group meets, so alignment is built from the real range of views rather than the first voice in the room.
  • Every recommendation on the roadmap is specified as a fundable pilot — metric, measurement, resourcing, governance, adoption, and dependencies.

Client Success

Organizations building this capability alongside us.

Get a board-ready picture of where to start.

Let's find out together. We'll help you choose the program that fits where you are today.

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