Artificial Intelligence Consulting Firms: Internal Review and Future Recommendation

 

 

TO: Executive Leadership Team
FROM: VP of Strategy
SUBJECT: Post-Engagement Summary – External AI Advisory Collaboration
DATE: [Redacted for circulation]

 

Team,

Following our six-month collaboration with external advisors, I’m submitting this internal review to synthesise outcomes, flag key learnings, and outline next-step considerations. Please treat this as both a debrief and a forward-looking guidance document.

 

1. Engagement Context

When we initiated the engagement, our goals were threefold:

·        Audit the performance of our existing AI infrastructure

·        Identify root causes of our stagnant predictive model performance

·        Evaluate options for strategic AI acceleration over the next 18 months

The scope was intentionally narrow. We didn’t ask for implementation or technical fixes. We asked for hard truths and strategic clarity. And we got them.

 

2. Selection Rationale

Several proposals came in. We deliberately avoided large vendors and instead shortlisted specialist artificial intelligence consulting firms with a proven background in diagnosing systemic misalignment between data operations and strategic outcomes.

The selected firm approached us not as implementers but as auditors of thinking. That distinction mattered.

 

3. Observations Shared by Consultants

Here are the five major insights surfaced in their final summary (with my annotations in brackets):

“The AI team is solving problems the business hasn’t clearly defined.”

 → (This was echoed in 3 cross-functional interviews. Strategy-team alignment is absent.)

“Models are evaluated on internal elegance, not external value.”

 → (We’ve confused sophistication with relevance.)

“Feedback loops exist, but no one owns them.”

 → (We’re gathering data but not translating it into design or policy adjustments.)

“The current architecture is overfitted to a problem definition from two years ago.”

 → (Our infrastructure is optimised for a market reality that no longer exists.)

“No roadmap exists for when automation fails.”

 → (We’ve placed excessive trust in systems without contingency behaviour.)

These weren’t minor process tweaks. They were structural revelations.

 

4. Cultural Impact

As important as the technical guidance was, the deeper shift has been internal. Teams have become noticeably more critical of our AI narrative. Engineers are asking sharper questions. Marketing has stopped using the phrase “intelligent automation” as a default descriptor. The CEO, for the first time, requested a quarterly “unknowns report” to surface model blind spots.

That is a direct consequence of our choice to engage with artificial intelligence consulting firms who prioritise strategic interrogation over technical execution.

 

5. Missed Opportunities (Ours, Not Theirs)

We delayed access to frontline product teams until week 4 of 12. In hindsight, this limited early momentum.

Our internal documentation was inconsistent. Consultants spent time decoding what we should have clarified upfront.

We assigned no dedicated liaison from Strategy. This created unnecessary back-and-forth.

These are learnings we must apply if we re-engage or expand the partnership.

 

6. Final Assessment

Was the engagement worth it? Yes. And not because we got code or tools. We didn’t.

We got confrontation—of our assumptions, our internal biases, and our comfortable narratives. That confrontation has shifted how we talk, prioritise, and design. One Director privately remarked, “It was like being told our smart house had no fire exits.”

I recommend we consider a second engagement with a narrower focus: designing intelligent fallback states for every critical AI function. There are artificial intelligence consulting firms that specialise in failover architecture. We should initiate shortlisting immediately.

 

7. Closing Thought

In an era where every tech team claims to “do AI,” differentiation will come from thinking, not tooling. We don’t need smarter machines. We need smarter understanding of what they’re actually doing.

Let’s continue to work with artificial intelligence consulting firms who challenge us to think beyond automation—and towards responsibility.

Let’s ensure our next steps are shaped not just by urgency, but by intentional, insight-led decisions.