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Engagement · 6 weeks · First findings in week 4

AI Adoption Reality Check

An independent read on why your AI isn't paying off, and a plan to fix it in the next 90 days.

Before you spend more on AI, or stop spending, it's worth knowing what's actually going on. I find out from your own people in confidential conversations, then work through what they tell me. You get a clear account of what I find, with a plan specific enough to act on.

Format
6-week diagnostic, led by Phil
For
CEO, COO or de facto AI lead
Delivery
Interviews · working session · report
Outcome
The real constraint and a 90-day plan
Start with a conversation

01The situation

You've invested in AI. Licences are out, pilots have run, maybe there's a programme with a name and a steering group. The value isn't showing up the way it was meant to, and the question of why is landing on your desk.

Costs are rising, unapproved tools or AI-built software are spreading, or poor AI output is creating more checking and rework. You need a handle on what's happening, where the risks sit and what needs to change.

02Who it's for

  • The person AI responsibility has landed with, whatever your title. You might be the CEO, COO or the de facto AI lead alongside your day job.
  • An organisation that has bought tools or run pilots but can't see the benefits it expected
  • An AI rollout with pockets of resistance, managers who aren't backing it or teams pulling in different directions
  • Someone facing rising costs, unapproved AI use or unreliable output who wants an independent read before committing to more spend

03What it isn't

  • An implementation team, or someone to run the programme for you
  • A data audit, security review or model-stack recommendation
  • A tool or vendor selection exercise
  • A fractional AI chief or an ongoing advisory relationship
  • An off-the-shelf maturity score — every finding is specific to you

For ongoing support, see Ongoing AI Strategy Advisory.

If the blocker is technical, I'll tell you and point you to the right specialist. You won't be left trying to fix an organisational problem with another tool, or a technical problem with another workshop.

04What you walk away with

You'll leave with clear priorities and practical changes you can act on right away, so you can start turning the AI effort around.

01

The real issues, with a clear priority. What's holding back results, why it's happening and what to tackle first.

02

A report written for busy executives. Clear findings and practical recommendations, without the fluff.

03

A 30/90-day plan — what to stop, what to change and what to do next, specific enough to act on right away.

04

Two follow-up sessions over 90 days, so you act on the report rather than file it.

Independent by design

I'll tell you plainly what I find and what to do about it. I have no platform to sell or implementation contract to steer you towards.

05How it works

  1. Week 1

    Intake and scoping

    A 90-minute session to frame the problem, agree the questions that matter and map who to talk to.

  2. Week 2

    Stakeholder interviews

    Six to eight confidential conversations with the people closest to the problem. This is where the real picture comes out.

  3. Week 3

    Diagnosis

    I assess your situation across ten dimensions to find what's holding back results.

  4. Week 4

    Executive working session

    A half-day with your leadership team to test the findings, pressure-check the constraint and agree what changes.

    First resultFindings

  5. Weeks 5–6

    The report

    A clear account of where the problems lie, what to stop and what to change, with a 30/90-day plan you can start acting on right away.

+90 days

Follow-through. Two advisory sessions across the 90 days after delivery, to keep the plan on track and adjust it when reality pushes back.

My promise

In six weeks, you'll have a clear diagnosis of what's holding back your transformation, and a concrete 90-day plan that tells you what needs work, what to focus on and where to start.

06What the report gives you

The report sets out:

  1. The honest baseline — where adoption really stands
  2. The binding constraint, named and evidenced
  3. What's working, and worth protecting
  4. What to stop — the spend that isn't paying off
  5. A 30/90-day plan: what to do first, who needs to act and what follows
  6. A short executive summary of the findings and decisions needed

07Why work with Phil

Before starting this practice, I held a senior global digital-delivery role across the infrastructure practices of an engineering consultancy, where I saw first-hand that simply giving people access to AI is a long way from adoption.

My own practice is AI-native, end to end. I've built AI into how every piece of work gets done.

From people I've worked with on similar challenges

“What sets Phil apart is the rare combination of deep technical fluency and genuine business acumen. … I watched him repeatedly bridge the gap between engineering teams and business leadership, translating complex technical trade-offs into decisions leaders could act on with confidence.”

John FormosoFormer senior colleague at Hatch

“One of Phil's greatest strengths is his ability to engage effectively across all levels of an organization. I have seen him hold his own in executive discussions about operating models, strategic direction, and organizational change while also connecting effortlessly with practitioners, engineers, and project teams.”

Andy HaresFormer colleague at Hatch

08The ten dimensions

I assess ten dimensions of adoption to find what’s holding back your AI transformation. Select a dimension to see the question behind it.

  1. Transformative belief

    Do leaders believe AI should change how the organisation operates, and are they prepared to act on that belief?

  2. Strategic clarity and ambition

    Is there a specific direction that guides decisions, or just a general intention to use more AI?

  3. Mandate and permission to transform

    Are people backed to redesign workflows and challenge established processes, or only permitted to use AI within their existing responsibilities?

  4. Leadership courage

    Will leaders back difficult changes when they disrupt established roles, priorities or interests?

  5. Leadership behaviour

    Are leaders visibly using AI and sharing what they learn, or asking everyone else to change while carrying on as before?

  6. Manager practice

    Are managers making time for experimentation, feedback and shared learning, or leaving adoption to individual enthusiasm?

  7. Governance and trust

    Can people quickly establish what is permitted, how to handle data and who can resolve uncertainty?

  8. Capability and confidence

    Can people use AI with sufficient skill and judgement to produce useful results, or have they only completed the training?

  9. Culture and sharing

    Does useful learning become shared practice, or stay with a handful of capable individuals?

  10. Communications clarity

    Are people hearing an honest, relevant account of what will change for them, including the uncertainty — or simply another announcement about AI’s potential?

How I think about AI in organisations

Let's get your AI effort moving.

Tell me what's happening. We'll talk through the problem and whether a Reality Check would help.

Start with a conversation

Fixed fee, quoted on enquiry