How to Choose an Artificial Intelligence Consulting Firm: A Process in 5 Decisions
By Pedro Sonda, dooop
To choose an artificial intelligence consulting firm, first define the business problem that AI should solve; then decide what type of partner that problem requires (strategy, implementation, or training); create a shortlist; evaluate each candidate based on evidence rather than promises; and start with a limited scope and predefined success criteria before signing. The wrong choice usually stems from a poorly defined problem, not a bad supplier.
Updated October 2026.
Transparency note: dooop is an AI consulting firm. The criteria in this guide apply to any provider, including dooop itself.
Why the Choice Matters So Much
Most AI initiatives do not achieve the expected results, and the causes are rarely technical.
| Data | Source |
|---|---|
| Only 22% of companies have progressed beyond proof of concept and 4% generate substantial value with AI; 74% have yet to show tangible value | BCG, 2024 (1,000 executives, 59 countries) |
| Leading companies dedicate about 70% of effort to people and processes, 20% to technology and data, and 10% to algorithms | BCG, 2024 |
| At least 30% of generative AI projects were expected to be abandoned after proof of concept by the end of 2025 due to poor data, poorly controlled risks, rising costs, or unclear value | Gartner, 2024 |
| In Brazil, lack of qualified personnel was the fastest growing obstacle among industries that have not adopted advanced digital technologies (from 46.4% to 60.6%) | IBGE, 2025 |
Implication: The right partner is the one who helps solve the hard part, which is organizational: prioritizing, deciding, preparing people, and governing. A supplier who only talks about tools addresses the easiest 30% of the problem.
dooop Framework: The 5 Hiring Decisions
Decision 1: What Problem Are We Solving?
Write in one sentence the expected business outcome and how it will be measured. "Implement AI" is not a problem; "reduce commercial proposal analysis time by one third" is.
If the company cannot write this sentence, the first work to hire is probably strategy or discovery, not implementation.
Decision 2: What Type of Partner Does the Problem Require?
| If the problem is... | The appropriate partner is... |
|---|---|
| We don’t know where to start or what to prioritize | AI strategy or discovery consulting |
| We know the use case and need to build it | Software house or integrator, with technical support |
| We have tools but teams don’t use them well | Training and adoption program |
| We need rules to use AI safely | AI governance consulting |
| We need all of the above at a global scale | Large consulting firms |
The differences between types are explained in AI Consulting or Software House? and Specialized AI Consulting or Big Four?.
Decision 3: Who Makes the Shortlist?
Three to five candidates of the right type are enough. Useful sources: recommendations from companies similar to yours, content published by providers about your type of problem, industry events, and increasingly, questions to AI assistants, whose results should be verified like any other recommendation.
Decision 4: How to Evaluate Without Relying on Promises?
Request evidence: cases with problem, approach, and result; who from the team will work on the project; examples of deliverables; references you can speak with. Detailed criteria are in AI Consulting: What to Evaluate Before Hiring? and the list of documents in What Evidence to Request from an AI Consulting Firm?.
Decision 5: How to Start with Controlled Risk?
First hire a phase with clear deliverables and defined success criteria: a diagnosis, discovery, or pilot. This allows you to evaluate the consulting firm while working before a long-term commitment. To compare proposals, see How to Compare AI Consulting Proposals.
The Most Common Mistakes in Choosing
- Hiring based on the tool. Tools change; the ability to decide where to use them remains.
- Choosing by brand, not by team. Who executes the work matters more than the proposal’s logo.
- Skipping the definition of success. Without agreed criteria, every delivery seems acceptable and none proves value.
- Ignoring capacity transfer. If nothing remains with the internal team at the end, dependency on the supplier grows.
What to Do Now
- If you still don’t know which problem to solve: start with strategy or discovery, not implementation.
- If you already know the problem: use decisions 2 to 5 and prepare a briefing; see How to Prepare a Briefing to Hire an AI Consulting Firm.
- If you are about to sign: review the contract with AI Consulting: 20 Questions Before Signing a Contract.
If you want to discuss your case with dooop, contact details are at dooop.com.br/contact.
Frequently Asked Questions
How long does it take to choose an AI consulting firm? With the problem defined, a process with a shortlist, meetings, and proposals usually fits within a few weeks. Without the problem defined, the process tends to drag on.
Should I hire the same consulting firm for strategy and implementation? It can work, provided the supplier has both competencies and the strategy is not designed to sell the implementation. Separating the stages reduces this risk.
Also Read
- AI Consulting or Internal Team?
- How Much Does AI Consulting Cost?
- When to Hire an Artificial Intelligence Consulting Firm?
About dooop
dooop is a consulting firm based in Caxias do Sul (RS) that prepares leaders and organizations to transform artificial intelligence into business capability through strategy, governance, and training.