AI advisory

Company-wide AI transformation consulting

For companies moving from scattered AI experiments to a coordinated way of working. I help leadership connect business priorities with useful pilots, clear ownership, and practical enablement across departments.

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Who this is for

CEOs, founders, executive teams, transformation leaders, and department heads responsible for making AI useful across the company.

When this is useful

  • Each department is trying AI independently, with little shared direction.
  • You need to choose between executive training, team workshops, pilot projects, and a wider transformation program.
  • A hackweek or initial rollout produced ideas, but the company needs a way to carry the useful ones into daily work.

What we work through

Map the opportunity and readiness

Review business priorities, existing workflows, team capability, data constraints, and current experiments with the people who own the work.

Prioritize a manageable portfolio

Select use cases by expected value and feasibility. Clarify ownership, dependencies, review needs, and what evidence would justify further investment.

Connect pilots with enablement

Plan role-specific training for leaders, engineers, and business teams. Use working sessions and hackweeks when they serve a defined purpose.

Build a review rhythm

Agree how to evaluate pilot results, capture feedback, address quality problems, and decide which practices should be extended.

Working outputs

These outputs are a starting point for scoping. We agree the priorities together before the engagement.

  • A working map of opportunities, readiness gaps, and priorities.
  • An initial roadmap connecting use cases, owners, pilots, and team enablement.
  • A review approach for adoption, operational value, quality, and follow-through.

Format and planning

An initial leadership working session, a focused strategy engagement, or ongoing advisory. Training and hackweek design can be included when relevant. The scope, duration, and fee are agreed before work begins.

Before we start

Bring the company’s priorities, participating departments, current experiments, and the main constraints. We can begin with workflow descriptions and anonymized examples.

The experience behind the work

I am VP of Product, AI at Jotform, where I lead the AI Product division. Alongside product and engineering leadership, I contribute to company-wide AI transformation, hackweeks, practical training, and adoption programs. My advisory and training work draws on that operating experience.

My leadership experience

Practical questions

Where should a company start with AI transformation?

Start with a business problem and the people responsible for it. Map a small number of workflows, assess feasibility and constraints, then choose a pilot with an owner and clear measures before expanding across departments.

Should we train everyone before starting a pilot?

Not necessarily. A leadership session can establish direction, while targeted workshops prepare the teams involved in a pilot. Broader training is more useful when connected to relevant workflows and support after the session.

Can this cover non-technical departments?

Yes. Adoption can include operations, marketing, sales, support, and other business teams. The work focuses on their workflows, useful context, review habits, and clear escalation when an AI result needs human judgment.

What happens after an AI hackweek?

The useful next step is to review the experiments, select what to continue, assign owners, and define a limited pilot. The aim is to turn learning into a working practice, with follow-up on adoption and quality.

Discuss the scope for your company

Share your company, the people involved, and the problem you want to address. We can work out the appropriate approach and scope together.

Discuss an engagement