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Artificial intelligence consulting: what it does
Artificial intelligence consulting is the work of finding where AI solves a real problem for the company, in what order to tackle each process and what each one requires in data, systems and people. The expected result is a plan with priorities and baseline numbers, not a presentation on trends.
The demand has a reason. According to the executive summary of the ICT Enterprises 2025 survey by Cetic.br, released in August 2026, 17% of Brazilian companies with more than ten employees used AI applications in 2025, up from 13% in 2024. Among those that did, 54% hired external vendors to develop or modify AI systems.
At Wama, AI consulting work starts with the AI Assessment, which has an article of its own: the guide to the AI diagnostic for businesses explains what this stage delivers. Here the subject is consulting as a whole: what it does, the contract formats and what to expect in the deliverable.
What does an artificial intelligence consultancy do?
An artificial intelligence consultancy does three things, in this order: it reads the operation as it actually runs, chooses where AI comes in and designs how it comes in. The reading covers flows, exceptions, systems and the place where the necessary data already exists. The choice ranks processes by return and feasibility. The design defines what becomes a fixed rule, what becomes workflow automation and what needs an AI agent.
That separation between rule, automation and agent is the point that saves the most money. Many processes that arrive labeled as AI projects are solved with integration between systems and a well-written rule, and the article on AI process automation shows how to choose the first flow. A serious consultancy says this early, even when the answer shrinks its own scope.
Outside the core are buying licenses for the company, training the team on a generic tool or delivering a market report. These deliverables can come along, but they don't replace the decision about where AI comes in.
The three AI consulting contract formats
The consultancies at the top of the search for this term sell the service in three formats, and they differ in where the commitment ends. The table summarizes what each format delivers and who it's for.
Format | What it delivers | Who it's for |
|---|---|---|
Strategic assessment | Report with opportunities, risks and roadmap, no build | Leadership that needs to defend a decision or guide its own technical team |
Diagnostic with plan | Prioritized processes, baseline and implementation plan | A company that knows it needs AI and doesn't know where to start |
Supported implementation | Use case in production, with follow-up and handoff to the internal team | A company with the first case chosen and an internal owner defined |
The format also changes how it's priced. Assessments and diagnostics usually have price, timeline and deliverable fixed before starting. Implementation depends on the number of processes, the connected systems and the volume. What happens after the plan, stage by stage, is in the guide to AI implementation in companies.
What should come out of an AI consultancy?
Every AI consulting engagement should end with four deliverables the company can use without the consultant in the room:
Prioritized processes, each with the criterion that put it first: volume, available data, risk of error and integration effort.
A baseline, with today's number in time, volume or rework, to measure the after.
A classification of each case: individual work inside the tools the team already uses, or automation that changes the operation and requires integration. Microsoft's AI adoption planning guide, updated in October 2026, uses this split to guide the choice of technology.
A plan with order and estimated cost, that leadership can approve. The math behind it appears in the article on how much it costs to implement AI.
In Wama's AI Assessment, what comes out is the custom Implementation Plan and the baseline for measuring before and after. Without these two items, consulting becomes a nicely formatted opinion.
When is AI consulting not the next step?
AI consulting isn't the next step when a ready-made tool already exists for the problem. The same Cetic.br survey shows that 80% of companies that used AI in 2025 chose off-the-shelf solutions. If the case is a market standard and doesn't depend on internal data, the decision is a purchase, not a consultancy.
It also isn't the next step when the team already uses AI on its own and no one has defined what can go into the tools. In that case, an AI use policy comes first. The same goes for anyone who only wants an assistant that answers based on the company's documents: an AI agent with a knowledge base is usually a direct project, with a clear scope.
In Wama's view, consulting pays off when several processes compete for the same budget and no one can say which comes first. Without that competition, the money goes further going straight to the build.
How Wama organizes AI consulting work
At Wama, the consulting part of AI sits inside the AI Assessment, which brings together what used to be the Strategy service. It's the first stage of a three-part journey: AI Assessment, custom Implementation Plan and execution. There's no boxed solution: each company gets its own plan.
The diagnostic is a small, paid first step that shows where AI fits in the company before any bigger commitment. When the client moves on to the plan, the diagnostic fee is credited against the first installment. This setup leaves the analysis free to recommend less, including saying that a process shouldn't get AI right now.
Wama also uses AI in its own operation, in code and automation, and every output goes through human review before reaching the client. The studio's own AI projects are ManyFeed, a social proof SaaS built with AI, and Auzy, a management platform for creative professionals.
Common mistakes
The mistakes that make AI consulting most expensive happen before the contract is signed:
Starting with the tool. The license arrives before the problem and the consulting becomes a justification for a purchase. Microsoft's guide advises starting with business problems, such as repeated manual effort or slow approvals, before considering AI.
Hiring without a baseline. Without today's number, no result can be held to account later.
Accepting a deliverable only the consultancy understands. The plan needs to be readable by whoever will execute it, inside or outside the company.
Forgetting personal data. Every case involving customers or employees needs a legal basis and a defined data path, following the rules of the LGPD, Brazil's data protection law, for artificial intelligence.
Granting overly broad access. When AI talks to systems, each connection needs minimum permission, the same care required of MCP in companies.
Frequently asked questions
How much does artificial intelligence consulting cost?
It depends on the format. Assessments and diagnostics usually have a fixed price, set by the number of processes and areas analyzed. Implementation varies with the connected systems and the volume of use. Be wary of a price given before any conversation about the operation: without knowing the processes, the number is a guess.
How long does AI consulting last?
The timeline follows the format. Assessments and diagnostics are shorter, because they depend on interviews with the people who run the processes and access to system information. Supported implementation lasts longer, since it includes a pilot, adjustments and handoff to the internal team. A timeline presented without an interview schedule is a loose estimate.
Is AI consulting useful for a small business?
It is when there's more than one candidate process and real doubt about the order. AI use is growing among small companies: in the Cetic.br survey, it went from 10% in 2024 to 15% in 2025. For a single standard case, a well-configured off-the-shelf tool usually does the job without consulting.
What's the difference between AI consulting and an implementation company?
Consulting decides what to do and in what order; implementation builds it and puts it to work. Some vendors do only one part and others do both. At Wama, both are on the same journey, from the AI Assessment to execution, with the plan as the handoff point.
Does the AI consultancy need access to the company's systems?
It needs to understand how data flows, but it doesn't need broad access. In the analysis, interviews, samples and screen walkthroughs are usually enough. When the project reaches integration, each access should be specific, logged and with minimum permission, as in a well-done CRM integration with AI.
If your company has more than one process asking for AI and no criterion for choosing the first, the AI Assessment is the shortest start. Talk to Wama about the processes that take up the most of your team's time today.
