AI Adoption & Enablement · Marketing & Sales
AI is rolled out.
Nobody's using it.
Licenses handed out, training done — and still barely anyone really works with AI. That's not a tool problem, it's an adoption problem. I embed AI into the daily work of your marketing and sales teams — as a way of working, not a seminar.
30 minutes · Free
The problem
Why AI rollouts fizzle
New tools get introduced faster than they get integrated.
Teams move at very different speeds.
Marketing learns faster than the rest of the business.
AI output without operational context produces question marks, not results.
The reframe
AI enablement, not tool training
What teams need isn't a course. It's someone who works through with them what genuinely makes sense in their specific daily work — and what's just distraction.
Adoption ≠ rollout. Adoption means: the right people use the right tools for the right tasks — regularly, without friction, with measurable output.
Enablement means seriously answering four questions:
Who already uses AI — and where does it create real impact?
Which workflows can be scaled with little effort?
Who needs ongoing support — and who needs a concrete project instead?
How does AI stay usable even when the tools change every six months?
Why me
Marketing and sales DNA, not org-chart consulting
I haven't just observed AI tools. I've introduced them in real B2B teams — and seen what works and what fizzles. That's why I don't work with hypothetical roadmaps, but with what's actually on your plate right now.
18 years of B2B marketing leadership across SaaS, tech and agencies.
AI workflows I built myself — not theory, but operationally proven.
No tool recommendations pulled from thin air. Instead: what works in your context.
Independent. No software sales, no hidden agenda.
The first step
Before you pick a format: know where it's stuck
You've introduced AI, but the business impact lags behind expectations. Before you invest time and budget into workshops, sparring or consulting, the AI Adoption Assessment creates clarity: it shows where strategy, usage and processes diverge — with a scorecard across six dimensions, the three to five most important levers and a concrete action plan. Handed over live, not as a self-assessment.
From rolled out to actually used
Status check
First know where it's stuck — the AI Adoption Assessment shows where strategy, usage and processes diverge.
Prioritisation
Which use cases first, where the biggest lever sits — instead of more tool experiments.
Team embedding
Embed AI into real processes — as a workshop, sparring, consulting or fractional engagement, depending on where you stand. Until it's used in daily work.
Impact & refinement
We measure against the goals from the start and refine — impact instead of activity.
How we work on it
Four formats, depending on where you stand
Workshop: From AI chaos to clear workflows
One day in which your teams don't just test AI but turn it into real processes — with concrete use cases, prompt frameworks and a plan for who runs what afterwards.
Request a workshopSparring: AI enablement at leadership level
Regular 1:1 sessions for marketing or revenue leads. The goal: clarity on levers, priorities and progress — without adding management overhead.
Request sparringConsulting: AI strategy for B2B teams
Project-based support for embedding AI into marketing and sales processes: from selecting sensible use cases through prompt architecture to alignment with existing goals.
Request consultingFractional GTM leadership with an AI focus
Interim or fractional leadership for teams that don't just want to test AI but anchor it structurally in daily work — with measurable output, not well-meant recommendations.
Book a discovery callPerspectives
More ways into the topic
Articles from the CEO Guide to AI — for everyone who wants to think along at the strategic level.
Article 1
When teams learn AI at different speeds
→ Whole companies don't learn AI – individual teams do. The tensions that creates for leadership.
Read articleArticle 2
Three things CEOs currently underestimate about AI
→ Speed gaps, fragmented adoption, operational overload – the real mid-market risks.
Read articleArticle 3
Why many companies produce tool chaos instead of clarity
→ How well-meant experiments turn into a parallel shadow-IT system within twelve months.
Read articleArticle 4
Where AI delivers real ROI in the mid-market – and where it doesn't
→ Four fields with clear impact. Three where money is currently being burned.
Read articleFrequently asked questions about AI adoption & enablement
30 minutes of AI clarity for your revenue teams
A first conversation, 30 minutes, free. At the end you'll either have two or three concrete next steps — or the honest feedback that working together isn't the right lever right now.
Book a free discovery call →30 minutes · Free