Data Department provides artificial intelligence (AI) strategy consulting and fractional Chief AI Officer advisory for companies that want senior AI leadership without a full-time executive hire. We help you choose which AI projects to fund, review vendors and architectures, set governance rules and build your own team. We have helped a technology group grow a machine learning (ML) function into a 30+ person department that built 20+ models across 7 industries.
What problems does AI strategy solve?
Most companies do not lack AI ideas. They lack a way to choose between them and the senior judgment to tell a sound proposal from an expensive one. The decisions we help with:
- Which use cases to start with, which to postpone and which to stop.
- Whether to build, buy or partner for each use case.
- Whether a vendor proposal or a consultancy's architecture is sound and fairly scoped.
- Whether a pilot is ready for production, or needs more work, or should end.
- Which roles to hire first, and in what order.
- What employees may and may not put into public AI tools.
The method is the same one we use on delivery projects: start from the decision, not the model. A use case earns a place on the roadmap when it changes a specific decision that someone owns, and when the data to support it exists.
Which engagement fits your situation?
| Engagement | Best when | What you get |
|---|---|---|
| Fractional Chief AI Officer | You need ongoing senior AI leadership but not a full-time executive | Regular senior time: roadmap, steering meetings, vendor reviews, hiring support |
| Discovery (2 weeks) | You have candidate use cases and need to pick one | Ranked use cases, data check, go/no-go decision |
| GenAI readiness assessment | You want to use generative AI (GenAI) but are unsure where to start | Review of documents, data, security and skills, with a prioritised list of first steps |
| RAG audit | You have a RAG (retrieval-augmented generation) assistant but no proof it answers well | An evaluation set, a failure analysis and a ranked list of fixes |
| Agent architecture review | You plan to let AI agents act in your systems | Review of permissions, approval points, logging and failure modes |
| Workshops and team training | Leaders or technical teams need a shared, practical understanding | Executive workshops and hands-on training for technical teams |
How we work
Start with a decision inventory. We list the recurring decisions in your business that cost the most when they go wrong: what to stock, what to charge, whom to contact, how to plan. Use cases come from that list, not from a technology catalogue.
Score every use case on four things. Business value, data readiness, ease of adoption by the people who will use it, and risk. Read more on how to choose your first AI project.
Run one pilot at a time, measured. Each pilot has a business metric agreed on day one. Pilots that do not meet it are stopped, and that counts as a useful result.
Build your team as you go. We help write job descriptions, interview candidates and mentor the people you hire, so the capability stays when we step back.
As a fractional Chief AI Officer, we work a fixed number of days per month agreed in advance, join your management meetings where AI is on the agenda, and act as the senior technical voice in vendor and architecture decisions. Read more on what a fractional Chief AI Officer does.
Results from a real engagement
For a technology group, over several years, we mentored a new research and development centre's squads through the full machine learning lifecycle. There were four squads, working in hospitality, energy, tourism and automotive. We also provided group-wide ML and AI training. The function grew into a 30+ person ML and AI department that built 20+ models across 7 industries. Read the ML department case study.
Because we also deliver projects, including generative AI assistants and agents, our advice comes from building and running these systems, not only from planning them. A free 30-minute AI opportunity review is a simple way to see whether this kind of support fits you.
When is AI strategy work NOT the right tool?
- You already have a strong AI leader and team. You likely need delivery capacity, not more strategy.
- The decision is already made. If the goal is a slide deck to justify it, we are the wrong partner.
- There is no executive sponsor. A roadmap nobody owns will not be followed.
- You need one well-defined project. Go straight to a 2-week Discovery for that project.
Frequently asked questions
What does a fractional Chief AI Officer do?
Owns the AI roadmap, chairs steering on AI projects, reviews vendors and architectures, supports hiring and reports to management, for a fixed number of days per month instead of a full-time salary.
Do you also build what you recommend?
Yes. We deliver forecasting, pricing, customer, vision, optimisation and generative AI projects. You can also use our advice with another delivery team or your own.
How do you handle KVKK, GDPR and AI regulation?
We help you set AI usage and data rules that fit KVKK (Türkiye's Personal Data Protection Law), GDPR (General Data Protection Regulation) and, for companies operating in Europe, the EU (European Union) AI Act. For legal sign-off, we work with your legal advisers.
What drives the cost of strategy work?
The number of business units and use cases in scope, how many days per month of senior time you need, and whether training and hiring support are included.