AI Transformation Practice

The Challenge

A senior practitioner running an AI transformation advisory came to us at a strange moment in the market. AI was the most-talked-about topic on LinkedIn, which sounds like an advantage but isn't. The noise floor was deafening. Every consultant, ex-Big-4 partner, and former engineer had repositioned as an "AI transformation expert" overnight. Generic LLM explainer posts and recycled McKinsey charts were drowning out anyone with actual implementation scars.

The practitioner had something most of the competition didn't: real deployments inside real enterprises, including the failed ones. They knew where AI initiatives stall, why pilot projects don't make it to production, what change management looks like when half the workforce is anxious about being replaced, and which vendor pitches collapse under operational scrutiny. None of that was visible on their LinkedIn profile.

The brief: turn LinkedIn into a discovery channel for mid-market and enterprise leaders who were ready to move beyond AI hype and needed a practitioner, not a presenter.

Our Approach

We anchored the strategy on a single positioning idea: be the person who has actually done the work. Every post had to pass one test. Would a generic AI thought-leader be able to write this, or does it require real implementation experience? If the answer was "anyone could write this," we cut it.

The content arc ran across four pillars:

• Operator-level takes on enterprise AI adoption — specifically the messy middle between pilot and production
• Behind-the-scenes patterns from change management inside AI rollouts
• Anonymised case observations from advisory engagements
• Selective contrarian positions on industry narratives — especially around AI agents, autonomous workflows, and the gap between vendor demos and operating reality

We also built a deliberate concept the practitioner wanted to own: the idea of being an "Orchestrator of AI" rather than an implementer. This wasn't a tagline. It was a working position about combining operational efficiency with human judgement, and we developed it across multiple posts so it accumulated weight.

Outreach targeted COOs, heads of transformation, CIOs, and digital leaders at mid-market enterprises. 40 to 50 personalised connection requests per week, each one referencing something specific from the recipient's recent activity. Engagement rotated across substantive comment angles on posts from the same target ICP.

What Changed

Across the first 90 days:

• Two of the three enterprise pipeline opportunities progressed to scoped engagements
• Pattern shift in DM quality — from generic vendor pitches and SDR outreach to qualified conversations from operators with real budgets
• The practitioner posted three times a week, not daily — volume wasn't the lever

The lever was that the writing finally carried a recognisable point of view, said specific things that generic AI commentators couldn't say, and showed up consistently in front of the right audience.