We asked Vincent Chauvet, CEO of LGI, for his perspective on the disruption brought about by the so-called “AI revolution” - and what it really means for the consulting sector.
AI is often described as a productivity revolution. Is that really the disruption - or is something much bigger happening?
Vincent Chauvet — Productivity is only part of the story. AI is fundamentally changing our relationship with work across service sectors and industries. It is not only transforming how fast we can perform tasks, but also how value is created, how expertise is used and how organisations structure their work.
For consulting, this means questioning models that have existed for decades. The disruption is not simply “doing the same work faster”. It is about redefining what humans, organisations and AI systems each contribute.
The same transformation is already affecting wider socio-economic systems, including research and innovation.
AI can already analyse documents, generate reports and even propose strategies. So where does a consultant create value today?
VC — The traditional consulting model is being challenged.
We are gradually moving away from selling hours towards delivering outcomes. AI can accelerate analysis and production, but the consultant remains responsible for the quality and reliability of the result.
The distinctive value of a consultant lies in consulting expertise, sector knowledge, judgement and accountability for the final deliverable.
We are therefore seeing the emergence of the “augmented consultant”: someone who uses AI tools and ecosystems of agents to extend their capabilities.
But the expertise still lies with the human - not the machine.
Has AI changed what clients expect from consultants - and what they are willing to pay for?
VC — The shift is already underway. New AI pure players are entering the market and creating a form of disintermediation: some clients may initially think that direct access to AI means they no longer need consultants.
Whether that assumption holds in practice is another question.
AI can produce outputs very quickly, but clients still need reliable results, contextual understanding, critical judgement and accountability.
Consultants will increasingly be valued not for producing information, but for interpreting it, challenging it, and turning it into sound decisions.
Has it changed the way LGI works? What do you now delegate to AI, and what do you keep firmly human?
VC — Transformation is ongoing at LGI. We launched the “LGI Next” programme internally to explore and anticipate new ways of working with AI across operational, support and management functions.
But one principle is non-negotiable: there will never be a complete handover to AI.
We systematically apply the “human-in-the-loop” approach, ensuring human review, quality control and validation throughout our work.
Automation can support human intelligence. It should not replace responsibility, judgement or critical thinking.
There is a lot of talk about “responsible” or “ethical AI”. Beyond the buzzword, what should that actually mean for an organisation using AI? Does that include questioning AI’s environmental and social costs?
VC — Ethical AI is actually only one of 4 pillars of what we call responsible AI.
AI must be ethical - responsibility cannot be delegated to a machine. Humans remain accountable for how AI is used and for the decisions made with it.
But responsible AI should also be:
- Frugal – minimising externalities relating to energy, water and land use,
- Sovereign – limiting strategic and geopolitical dependencies and strengthening European technological sovereignty.
- Compliant - respecting confidentiality, privacy, intellectual property and the applicable legal framework.
Responsible AI therefore requires organisations to look beyond performance alone and consider the wider consequences of the technologies they deploy.
This is the thinking behind Daïmons, LGI’s spinoff initiative dedicated to AI. How are you trying to do things differently?
VC — Daïmons reflects the way we believe AI should be approached: not simply as a technology tool, but as an organisational transformation.
Within LGI, AI is being integrated across our business lines to improve efficiency and create new forms of augmented consultancy.
Through Daïmons, we also support clients in their own AI transformation, with social responsibility and the assessment of externalities built into the approach. The purpose of Daïmons.ai is to help organisations move from scattered AI experimentation to concrete results, driving performance, empowering people and ensuring controlled impact.
In practice, Daïmons provides:
- Tailored AI strategy: maturity assessment, roadmap, ROI, governance & compliance;
- AI agent deployment: automation, business copilots, real-world workflows;
- Transformation & adoption: change management strategy, training, AI literacy, impact analysis.
Our ambition is to provide 360-degree support, from strategy and governance through to building, deployment and monitoring.
Daïmons is not simply about deploying AI. It’s about helping organisations deploy AI in a way that is useful, responsible and aligned with their long-term objectives.
Five years from now, what will separate a great consultant from someone who simply knows how to use AI?
VC — The fundamentals will remain the same. A great “augmented” consultant needs strong consulting skills and deep sector expertise. Those are prerequisites for using AI effectively. Knowing how to use an AI tool will not, on its own, create expertise.
The difference will come from the ability to ask the right questions, challenge the output, understand the context and take responsibility for the result.
AI may amplify expertise - but it cannot replace it.
What is currently your biggest challenge in an AI-powered consulting environment?
VC — One very concrete example is the automated generation of applications for competitive grant programmes, particularly at European level.
We are witnessing a surge in AI propelled applications which put a lot of pressure on the evaluation system, which was designed in a pre-AI era. This creates pressure on institutions and risks reinforcing a kind of “lottery effect”: organisations submit more applications in the hope that one succeeds, while average quality can decline.
Funding institutions are therefore (or should be!) in the process of rethinking how applications are assessed and how quality is recognised.
LGI’s response is to move further up the value chain. Our role is increasingly less about simply supporting grant writing and more about helping clients address the fundamental questions behind successful projects: strategy, governance, consortium building, coordination, impact and long-term value creation.