Buyer’s guide · UAE / Saudi Arabia / GCC

How to choose an AI advisory firm in the UAE and Saudi Arabia

Ask each shortlisted firm for a named delivery team, a comparable case, an evaluation plan, a data-flow map, full operating costs and a handover plan. Assess that evidence against the same mandate before choosing a firm.

This is a Barry Advisory buyer framework, not an independent ranking or a certification. Firm size does not establish quality; assess the proposed team and scope. These models can overlap.

Delivery models

Choose the delivery model around the mandate.

Large multidisciplinary firm

Consider this model when a programme needs several disciplines, jurisdictions or a broad transformation office. Ask which senior people will actually deliver, how workstreams connect and which activities are subcontracted.

Engineering specialist

Consider this model when the product scope and accountable business owner are clear and the main need is technical delivery. Check whether discovery, governance, integration and post-launch support are included.

Operator-led boutique

Consider this model when direct senior involvement and a connected business-and-technology brief matter. Verify available capacity, specialist partners, cover for key people and the handover into your operation.

Your shortlist

Ask every shortlisted team for the same evidence.

  1. The actual team

    Name the decision owner, delivery lead and specialists. Confirm their availability and responsibilities in writing.

  2. A comparable example

    Ask for the starting problem, the team’s contribution, the measurement period and the limits of the result. Separate employment history from firm-delivered work.

  3. An evaluation plan

    Define representative Arabic and English tasks where relevant, quality thresholds, review needs and the conditions for stopping or scaling.

  4. A data and deployment map

    Specify where data, prompts, outputs and logs go; who can access them; and which model routes and fallbacks are allowed. Have your legal and security owners review the design.

  5. The full operating cost

    Compare discovery, integration, inference, evaluation, human review, maintenance and support. Use the same workload and quality assumptions for each proposal.

  6. An ownership and exit plan

    Agree source-code and documentation handover, operating access, support responsibilities and how your team can change provider or model.

Three reasons to challenge a proposal

Unnamed delivery ownership

Confirm who will do the work and who owns the decision. Do not assume the person presenting the proposal will lead delivery.

Guaranteed ROI or compliance without assessment

Ask for assumptions, testing and review by the client’s legal and security owners. Hosting location alone does not establish that every data flow is appropriate.

An unclear exit

Clarify source-code and documentation rights, export of data and evaluation sets, and operation after changing provider or model.

Our model

Where Barry Advisory fits.

We offer founder-led strategy, AI and digital transformation, growth and delivery. Larger mandates can scale to 35–50 people through specialist and partner teams, depending on scope, budget, timing and agreed mobilisation. That is project delivery capacity, not permanent headcount. Ask us the same questions above.

Explore AI advisory and delivery

Practical questions

Do we need a local office or local operating knowledge?

Decide what the work requires: on-site access, stakeholder availability, language, procurement and support. Check those commitments directly. A regional address by itself does not establish delivery capability.

Should we choose a model provider before an advisor?

Start with the workload, data boundaries, quality needs and operating economics. Ask the advisor to disclose commercial incentives and demonstrate why the proposed model or provider fits those constraints.

What should a useful first phase produce?

A documented baseline, prioritised scope, representative evaluation, cost assumptions and named decision owners. Agree the evidence needed for the next investment rather than relying on a demonstration alone.

Barry Advisory · Updated 6 November 2026

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Define the first decision.

Tell us the workflow, priority or constraint you want to address.

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For a broader voluntary approach to AI risk management, see the NIST framework. The selection checklist above is Barry Advisory’s own editorial framework, not a NIST assessment. NIST AI Risk Management Framework