AI strategy & leadership

AI strategy that doesn’t end on a PowerPoint

Most “AI strategy” delivered by big consulting firms is a slide deck left on the CEO’s desk. I build the things those slides promise — because I just finished doing exactly that at my previous employer.

At inFakt I’m leading the full cycle: stakeholder interviews, requirement analysis, AI vision, 12-month roadmap, governance framework, success metrics, change management. Outcome: 6+ initiatives identified with projected 30% efficiency gains.

At IG Group I led a Kraków-based data science team that worked with stakeholders in offices across the UK, US, Japan, Bermuda, and Dubai.

What I deliver

• AI vision & roadmap (4–8 weeks) — discovery with the business, mapping initiatives to ROI/feasibility, quarterly plan with milestones.
• Fractional AI Engineering Manager — 0.5 to 2 days/week, leading an existing team or starting a new one. Hiring, structure, career paths, performance reviews, mentorship.
• Change management — AI deployments require changing the work of 80% of the org, not 20%. I help with internal comms, training, reskilling.
• AI governance — framework, policies, decision logs, model cards, audit trails. Mandatory under EU AI Act and GDPR.

Who this fits

• Scale-ups (50–500 people) with AI chaos (“every team plays with ChatGPT differently”) that need coordination.
• Companies hiring their first ML/AI engineer — I help avoid common hiring mistakes and structure the process.
• Boards that want an honest assessment of “Are we ready for AI?” before approving a budget.

What I don’t do

• I don’t sell “AI transformation” as an 18-month multi-million program. Most orgs need 3–6 months of focus and two good people.
• I don’t pretend that hype like “AI agents will replace 50% of the workforce” is a forecast. I tell clients what’s actually shippable now.

Stack as a manager

Agile · OKR · Jira · Confluence · GitHub · 1:1 frameworks · interview design · capability mapping · ROI modeling