AI is reshaping how companies operate not only in Tech or research, but across every industry. Today, more and more organizations are looking to leverage AI to automate processes, analyze data, and drive innovation. As this momentum accelerates, the role of the AI Consultant is emerging as a highly strategic and in-demand position.
In fact, according to Gartner, more than 80% of companies will have used generative AI APIs or deployed generative AI–powered applications by 2026, up from less than 5% in 2023.
👉 If you are considering a career change or looking to upskill, this role could be an ideal gateway into a rapidly growing field.
The AI Consultant role at a glance
An AI Consultant helps companies define how AI, particularly generative AI, can address their needs: automation, productivity gains, product innovation, data insights, and more. They analyze the business context, identify relevant use cases, design solutions, lead projects, and support teams throughout implementation.
What sets this role apart is its hybrid nature, sitting at the intersection of business, data, Tech, and strategy. As AI adoption continues to accelerate, companies increasingly need professionals who can bridge the gap between strategic ambitions and technological realities.
In simple terms, an AI Consultant is the person who:
translates business challenges into concrete AI solutions
selects or designs the right tools
anticipates risks and challenges (data, governance, adoption)
supports teams through the transition
Key responsibilities of an AI Consultant
The AI Consultant role revolves around three core pillars: analyze, design, and support. The goal is simple: turn AI into real business value, not a gimmick.
1. Auditing the situation and identifying AI opportunities
First and foremost, the consultant analyzes the context: available data, existing processes, business needs, and technical constraints. The challenge is to identify use cases that deliver the highest impact.
According to McKinsey, AI technologies, including generative AI, could technically automate up to 60–70% of current employee activities.
👉 This figure does not reflect what is already automated, but rather the real potential opening up for organizations.
For a consultant, this translates into a critical mission: identifying where AI can truly create value, without overpromising.
2. Designing AI solutions tailored to business needs
Once opportunities are identified, the consultant defines the solution: prototypes or proofs of concept (PoC), model selection, choice of tools (LLMs, APIs, automations), technical scoping, and collaboration with Data or Dev teams.
With the rapid multiplication of models (OpenAI, Claude, Gemini, and others), companies increasingly need professionals who can make smart technology choices rather than building everything in-house.
3. Deploying, training, and supporting teams
Adoption is often the weak point of AI projects. This is where the consultant plays a key role by:
training teams
creating documentation
supporting change management
measuring the real impact of the project
A 2023 MIT study shows that generative AI can increase productivity by 37% in certain tasks when properly integrated.
➡️ This gain is only possible if employees understand the tool and actually use it.
Essential skills to become an AI Consultant
Becoming an AI Consultant means developing a hybrid skill set: technical enough to understand how AI works, strategic enough to address business needs, and human enough to support change.
Here are the skills that truly set apart a strong AI Consultant in 2025.
1. A clear understanding of AI models and how they are integrated
An AI Consultant is not necessarily a Data Scientist, but they master the fundamentals needed to understand:
the different types of models (LLMs, predictive models, embeddings, agents)
their strengths, limitations, and conditions of use
integration logic: APIs, automations, business tools, data flows
What matters most is not deep coding expertise, but the ability to assess a solution, understand how it connects to an existing ecosystem, and communicate effectively with technical teams.
2. Strong skills in prompting, evaluation, and optimization
With generative AI, the consultant becomes a prompt “architect”:
designing robust instructions
structuring interactions
testing, documenting, and optimizing
ensuring the model produces reliable and consistent outputs
This skill has become essential, as it directly impacts the quality of prototypes, automations, and internal copilots that companies aim to deploy.
3. The ability to design an end-to-end AI solution
One of the core aspects of the role is being able to imagine and structure a complete AI solution based on a business need.
This involves:
analyzing a use case
identifying the right model or approach
building a prototype (PoC)
orchestrating a workflow or automation
anticipating risks (data, security, bias)
defining success KPIs
Companies are not only looking for technicians, but for professionals who can turn AI into operational value.
4. The ability to support and guide teams
AI does not impose itself, it needs to be explained, tested, and adopted.
The consultant must:
simplify complex concepts
reassure, guide, and engage teams
help teams understand why and how to use the tool
manage the transition from old workflows to new ones
According to a 2023 MIT study, generative AI can increase productivity by 37% when supported by proper training and onboarding.
This support role is therefore central and clearly distinguishes consultants who can make an AI project succeed from those who merely deliver it.
5. A hands-on, portfolio-driven approach
An AI Consultant must be able to show what they can do:
prototypes, automations, specialized agents, custom copilots, API integrations…
Organizations value candidates who can:
demonstrate real expertise
present concrete use cases
explain their decisions
prove their ability to carry an AI project through from start to finish
The most relevant training programs today are those that emphasize hands-on practice, real projects, use cases, and deployed solutions, as these best reflect what companies expect in 2025.
👉 And this is exactly what helps candidates stand out when applying for AI consulting roles or missions.
Salary and career outlook for AI Consultants in France
The salary of an AI Consultant in France varies significantly depending on experience, location, type of employer (startup, Tech company, consulting firm, freelance), and area of specialization. Below is a realistic overview of potential salary ranges, updated for 2025–2026.
Indicative salary ranges
Entry-level / junior
An AI Consultant at the start of their career can typically earn between €35,000 and €45,000 gross per year.Mid-level / experienced consultant
With a few years of experience, salaries generally rise to a range of €60,000 to €80,000 gross per year.Senior consultant or expert
In top-tier organizations or on high-value projects, it is not uncommon to reach €85,000 to €100,000 gross per year, or even more depending on responsibilities, bonuses, and the type of assignments.
⚠️ These figures can vary based on region, company size, industry (Tech, industrial, finance), and skill set (generative AI, data, automation, consulting, project management).
Why the outlook is strong
Demand for hybrid profiles who can combine technical expertise, strategy, and change management is exploding. Companies are looking for consultants who can turn AI opportunities into concrete, sustainable projects.
As generative AI, APIs, and automation tools become more widespread, the need for interpreters between business and Tech continues to grow. AI Consultants are becoming key enablers.
With experience, strong skills, and a solid project portfolio, an AI Consultant can move into high-impact roles, often with bonuses, performance incentives, or freelance and external consulting opportunities, significantly increasing earning potential.
For profiles trained today at the intersection of AI, project management, and digital transformation, this is an ideal time to enter the field. The market is dynamic, expectations are high, and salaries are attractive.
How to become an AI Consultant
There is no single, linear path to becoming an AI Consultant. On the contrary, career journeys are often diverse and sometimes unexpected. What successful profiles share is a common ambition: understanding how AI can transform a role, a service, or an organization and being able to demonstrate it.
Understanding AI, but above all, understanding what it can be used for
The starting point is not necessarily technical. It is about clarifying how AI works, how an LLM processes information, or how automation can streamline a process without overhauling an entire infrastructure.
Gradually, the perspective shifts. AI is no longer seen as “just a tool,” but as a lever, a productivity engine, a decision accelerator. This is where business thinking becomes essential.
The real breakthrough: thinking like an architect
An AI Consultant does not simply apply models.
They build a vision.
A need → a use case → a solution → an impact.
This ability to structure a project, explain it clearly, and adapt it based on real-world feedback is often what separates effective consultants from purely technical profiles.
It is also what enables speed: focusing on what matters, avoiding unnecessary complexity, and prototyping just enough to convince.
Then comes practice. Real practice.
It is by building an AI agent, connecting an API, or orchestrating a workflow that you truly understand what AI can change.
This is not theoretical knowledge.
It is hands-on expertise acquired through testing, building, and iterating.
These projects then become tangible proof points:
a portfolio that shows not only what you can do, but how you think.
Do not overlook the most underestimated dimension of the role: the human factor
AI adoption rarely depends on technology alone.
It depends on people.
An AI Consultant must be able to bridge the gap between tools and the people who use them: demystifying AI, addressing concerns, demonstrating concrete value, and supporting teams through adoption.
This balance between Tech, strategy, and pedagogy is precisely what makes the role both unique and highly attractive.
Over time, everyone finds their area of expertise
Generative AI applied to marketing
Business process automation
Internal copilots
Specialized agents
Large-scale AI strategy
The field is vast and constantly evolving, while companies are accelerating rapidly. This creates an exceptional window of opportunity for profiles capable of aligning AI with real business needs.
👉 If you are considering a career transition or upskilling, the timing is excellent: skills are scarce, expectations are high, and opportunities are real.
FAQ
Does an AI Consultant need to know how to code?
Not necessarily. Understanding the logic behind models, APIs, and workflows is often enough to work effectively with technical teams. AI Consultants are primarily expected to focus on understanding needs, designing solutions, and supporting adoption.
What is the difference between an AI Consultant and a Data Scientist?
A Data Scientist builds and trains models.
An AI Consultant identifies use cases, designs solutions, orchestrates integration, and supports teams throughout deployment.
The two roles collaborate closely, but they address different needs.
Is this role accessible through a career change?
Yes, provided you invest in solid training on AI fundamentals and practice on real-world projects. It is a hybrid role where understanding business challenges is just as important as technical knowledge.
What types of tools does an AI Consultant use?
Mainly generative AI models, automation platforms, APIs, analytics tools, and no-code or low-code environments. The key is not to master everything, but to know how to choose the tools that best serve a specific project.
Will AI replace the role of the consultant?
No. Companies need experts who can frame problems, explain solutions, secure AI usage, and support adoption. AI automates, but the consultant provides meaning, structure, and direction.
