What does AI consulting for a business include?
End-to-end AI consulting covers four stages: assessment (mapping processes and pinpointing pain points), scoping (an impact/feasibility matrix, a prioritized roadmap, governance on confidentiality and human review), building a measurable pilot in a few weeks, then rollout with team training and a dashboard tracking the gains. A typical engagement runs 2 to 6 months depending on scope, with a first measurable result within the first few weeks.
Why bring in an AI consultant?
Generative AI can transform your productivity — provided you pick the right use cases, in the right order, with the right governance. Most AI projects that fail start from the technology instead of the problem. We flip that logic: we start from your business pain points, put a number on the value, then build.
Founded by Nathan Amar, AI engineer and Head of Data & AI with 10+ years of experience, JNS-IA combines technical depth with a real grasp of how businesses run — and one conviction: the best AI is the one your teams actually adopt.
What does AI consulting for a business include?
AI consulting is a complete, four-stage engagement that turns artificial intelligence into measurable results. It starts with an assessment: mapping processes and identifying business pain points. Next comes scoping, with an impact/feasibility matrix, a prioritized roadmap and governance on confidentiality and human review.
The third stage builds a measurable pilot in a few weeks, tested by your teams on a real scope. The last stage rolls out the solution, trains the teams and sets up a dashboard tracking the gains.
At JNS-IA, an engagement typically runs 2 to 6 months depending on scope — with no need for perfect data or an in-house technical team to get started.
| Stage | What we do | What you get |
|---|---|---|
| 1. Understand | Process mapping, interviews with business teams, pain-point identification | A ranked list of value opportunities |
| 2. Scope | Impact/feasibility matrix, trade-offs, confidentiality and human-review framework | A prioritized roadmap and written governance |
| 3. Build | A pilot developed on a real scope, tested by your teams | A measurable pilot in a few weeks |
| 4. Roll out | Gradual extension, team training, KPIs in place | A solution in production and self-sufficient teams |
The mistakes that sink AI projects — and how we avoid them
AI projects that disappoint tend to look alike: they start from the tool instead of the problem, take on too much at once and forget the people who will have to use the result. Serious consulting is precisely about neutralizing these risks before they cost you months.
- Starting from the technology instead of the need: picking a tool and then looking for something to do with it produces demos, not results. The assessment always starts from business pain points and the time actually being lost.
- Aiming too wide from day one: an AI program that tries to transform the whole company in six months gets bogged down. A first project that is narrow, measurable and successful builds momentum for the next ones.
- Neglecting governance: without written rules on confidentiality, human review and approved uses, every department improvises — and one incident ends up freezing every project.
- Leaving the affected teams out: a solution designed without its users ends up in a drawer. We involve them from the assessment, they test the pilot, and their feedback drives the adjustments.
- Measuring nothing: without a metric defined before the project starts (time saved, error rate, turnaround time), there is no way to tell real success from hype. The gains dashboard is part of the deliverable.
- Stopping at the pilot: a successful pilot that never rolls out produces nothing. The fourth stage of the method — extension, training, KPIs — is the one that turns the trial into results.
What the engagement asks of your company
AI consulting has no technical prerequisites: no need for perfectly structured data, a data lake or a dedicated IT team. Three ingredients on your side, however, make the difference between a project that moves and one that stalls.
First, a clearly identified sponsor — a founder, CEO or leadership team member — who settles trade-offs and signals that the topic matters. Second, time from the business teams: a few hours a week for the assessment interviews, then to test the pilot in real conditions. It’s the highest-return investment in the project, because that feedback is what makes the result good. Finally, access to the documents and tools in scope: procedures, examples of past cases, demo accounts on the software involved.
In practice, the workload on your side stays compatible with day-to-day business: assessment interviews fit into short slots, and the build phases are carried by JNS-IA. The whole point of the method is for the transformation to move forward without tying up your teams.
Consulting that fits your size
Small business, SMB, mid-size company or large enterprise: the method adapts. Smaller organizations often see the fastest gains — short decision loops, very concrete use cases. Larger organizations benefit from our experience with multi-team rollouts and change management.
Let’s start simple: a free 30-minute call to understand your context and propose a concrete action plan.
Budget
What does it cost? Quoted per project.
Every engagement is priced after the first conversation, because a two-hour training for six people and an AI agent wired into your ERP have nothing in common. The quote arrives within 24 h, and it is firm.
What moves the number
- Format and durationA two-hour awareness session, a one-day fundamentals course, a role-specific workshop, a programme over several weeks.
- Number of peopleA team of eight and three hundred employees trained in waves are not sized the same way.
- Level of integrationAn agent that answers from your documents costs less than one that writes into your CRM and ERP.
- Security requirementsHosting, access partitioning, logging, human approval on sensitive actions.
- What comes afterHandover to your teams, or ongoing maintenance by us — two different budgets.
Training: delivered by Nathan, through certified training partners.
Request a quote — reply within 24 hFrequently asked questions
How long does an AI consulting engagement take?
A first pilot with measurable results is built in a few weeks. The full engagement usually runs 2 to 6 months depending on scope, with value milestones at every stage.
Do we need clean data or a technical team first?
No. We start with your existing tools and data, on a narrow scope. JNS-IA handles the technical side and progressively hands autonomy over to your teams.
Which use case should we start with?
A task that is repetitive, high-volume, well documented and low-risk: answering recurring questions, meeting summaries, processing inbound emails. The goal of the first project is to prove value fast, not to tackle the hardest problem.
Do you work with companies outside France?
Yes, remotely, in English or French, or on site — JNS-IA is based in Paris. The first call is free and comes with no commitment.
How much time does the engagement require from our teams?
A few hours a week during the key phases: short interviews during the assessment, then testing the pilot in real conditions. The build phases are carried by JNS-IA — the engagement is designed to move forward without tying up your teams.
How do you choose between AI consultants?
Three reliable criteria: does the method start from your business problems rather than a tool to sell, are results measured against metrics defined before the project starts, and is your teams’ autonomy part of the deliverables? Consulting that leaves you dependent on the consultant has missed the point.