Artificial intelligence

Artificial intelligence (AI) is reshaping market structures, value chains, and economic power dynamics.
It is redistributing positions among market participants, deepening technological dependencies, and placing control over data, models, and infrastructure at the core of competition.

For businesses, AI is not merely an optimization tool: it is a strategic positioning lever. In this context, the law becomes an instrument for structuring markets and creating competitive advantage.
De Gaulle Fleurance advises clients in structuring, securing, and managing AI-driven transformations across all dimensions.

AI and governance: controlling risk and structuring market position

The AI Act introduces a risk-based framework that now conditions market access. Classifying AI use cases, models, and underlying data, structuring compliance, and documenting governance mechanisms are no longer optional.

Beyond compliance, this framework reshapes competition: regulatory requirements create barriers to entry and widen gaps between market participants. Well-prepared companies turn compliance into a strategic advantage, while others face increased exposure to risk.

In this environment, AI governance becomes a strategic management tool, supporting asset protection, particularly with respect to data, and reinforcing market positioning.

AI, competition and commercial relationships: securing positioning in a redefined competitive landscape

AI is not only transforming competition, it is redefining its rules.

The ability to access, process, and integrate large-scale data into high-performing systems is becoming a key driver of market power.

These developments foster market concentration, reinforce technological lock-in effects, and exacerbate information asymmetries. They also reshape value chains, with certain players capturing an increasing share of value through control of data, models, or infrastructure.

Companies must integrate these dynamics upstream to deploy robust, legally sound commercial and technological strategies.

AI, investments and M&A: positioning AI as a strategic asset in growth transactions

AI has become a core asset in external growth strategies. Many M&A transactions now revolve around technologies, datasets, models, or specialized expertise that directly impact valuation and long-term viability.

These transactions require a tailored approach: understanding AI assets, anticipating regulatory constraints (AI Act, GDPR), securing rights over data and models, retaining key talent, and integrating AI into post-acquisition governance.

AI and disputes: anticipating, proving, and defending in an algorithmic environment

The integration of AI into decision-making and contractual processes is generating new categories of disputes: challenges to automated decisions, algorithmic errors, and breaches of transparency or fairness obligations.

Effective dispute management requires contractual foresight, clear allocation of responsibilities, and the ability to combine legal analysis with a technical understanding of the algorithms and data underlying contested decisions, particularly in litigation and arbitration contexts.

AI agents: framing delegated decision-making

The emergence of AI agents marks a paradigm shift: beyond decision-support tools, these systems can act, negotiate, and execute autonomously.

This evolution entails increasing delegation of operational, commercial, and decision-making functions to systems driven by models and data whose internal logic may remain partially opaque.

It challenges traditional concepts of liability and decision traceability, while transforming contractual relationships, particularly through automated interactions.

AI and intellectual property: securing and leveraging intangible AI assets

AI is disrupting traditional intellectual property frameworks. Training and operating AI systems rely on large-scale use of data, databases, software, and protected content, raising critical issues regarding lawful use and control of rights.

Companies must secure access to and use of input data while protecting their own intangible assets: models, algorithms, databases, and know-how. At the same time, AI-generated or AI-assisted outputs raise complex questions regarding ownership, protection, and exploitation in a still-evolving legal landscape.

Beyond protection, control over data is a key driver of economic power and market differentiation.

AI and employment law: supporting workforce transformation

AI is profoundly transforming job functions, task allocation between humans and technology, required skills, and collaboration models. These changes impact work organization, employment conditions, and career paths, requiring structured legal and HR support.

HR functions are also evolving through the use of AI-powered decision-support tools in recruitment, evaluation, workforce organization, and career management. These developments must be carefully framed in light of non-discrimination rules, data protection requirements, transparency obligations, and, where applicable, employee representative consultation requirements.

Making law a strategic lever in the AI economy

In the AI economy, control over data, models, and use cases directly determines value creation and market positioning.

Law is no longer peripheral: it is a central tool for shaping strategy, managing risk, and structuring power dynamics among market participants.

De Gaulle Fleurance supports clients in this transformation by combining legal expertise, technological insight, and strategic market understanding, turning AI not only into a driver of innovation, but into a true instrument of economic power.