Naully Nicolas
Digital philosopher, AI strategy consultant, and author of Guérill-iA
Naully Nicolas is a digital philosopher, AI strategy consultant, and speaker. He supports SMEs, public organizations, and leaders who want to adopt artificial intelligence with method, clarity, and strategic sense. His approach connects critical thinking, history, governance, and concrete action. He helps organizations move beyond the noise surrounding AI to ask the right questions, frame useful applications, train teams, and build realistic trajectories. He is also the author of Guérill-iA, a book dedicated to the adoption of artificial intelligence in SMEs, designed as a clear, practical, and strategic manual.
Prices
- Conference : 6000 €
- Animation : 9000 €
Localization
Languages
His conferences
AI and Defense: The Machine Accelerates, the Human Decides
Explore what artificial intelligence changes in defense, security, and high-pressure decision-making environments. In the defense and security sectors, AI promises to accelerate analysis, detection, coordination, and decision support. However, it does not replace human judgment, responsibility, or the legitimacy of action. This conference offers a strategic reading of the contributions and limitations of AI in environments where time is of the essence, uncertainty is high, and error is costly. An intervention to think about technology seriously, without fascination or rejection. What the audience takes away: - What AI truly improves in defense environments - Why speed does not mean accuracy - The limits of automation in the face of uncertainty - The irreplaceable role of human judgment - The ethical and strategic questions that must not be overlooked
After the copilots, what remains for humans?
Understanding how AI transforms roles, skills, and collective work. AI does not just change tools. It changes the place of humans in the organization. When certain tasks are automated, it is judgment, arbitration, responsibility, and cooperation that become central. This conference explores the future of work in the era of copilots and intelligent agents. It enables leaders, managers, HR, and teams to better understand what is truly transforming in professions, and how to prepare for this transition with clarity. What the audience retains - What AI really automates, and what it does not replace - Why work is shifting from tasks to judgment - The skills that gain value in the age of AI - The concrete impacts for managers and teams - How to avoid an adoption that destabilizes more than it helps
Adopting AI Without Losing Control
How to reconcile innovation, governance, security, and trust in artificial intelligence projects. Adopting AI is not just about choosing a tool. It is also about knowing where the data goes, who maintains control, how to mitigate risks, and how to create an acceptable framework of trust for teams, clients, and partners. This conference offers a clear approach to AI governance, at the intersection of strategy, digital sovereignty, compliance, and cybersecurity. It helps organizations move forward methodically, without naivety or paralysis. What the audience will take away - Why any AI strategy is also a governance issue - Key points of vigilance regarding data, tools, and usage - How to balance speed, control, and trust - The foundations of a simple and credible AI framework - The reflexes to adopt before scaling up
From Gadget AI to Useful AI
Artificial intelligence generates as much enthusiasm as it does confusion. Between spectacular promises, multiplying tools, and poorly framed uses, many organizations move forward without a clear direction. This conference offers a simple and strategic reading of AI adoption. It shows how to start from real business needs, identify useful use cases, reduce risks, and create value without losing control. An intervention designed for leaders, managers, and teams who want to move from talk to action. What the audience takes away - The difference between “impressive” AI and truly useful AI - The 3 criteria for a good AI use case - The most common mistakes in AI projects - A simple method to move from testing to sustainable use - The first questions to ask before investing