AI in business is generalized and represents a risk for competitiveness. Training internal for responsible use is not just a fundamental responsibility but a competitive advantage.
By 2030, 86 % of companies will integrate AI into their operations, revolutionizing uses in all sectors of the economy. This digital transformation, if it promises considerable productivity gains, is accompanied by significant challenges that companies must anticipate.
Hallucinations present a real risk for companies
The Hallucinations of AI – These phenomena where systems generate inaccurate information but presented with confidence – constitute one of the major risks of this technological revolution. An AI assistant can, for example, invent a nonexistent case -law to justify a legal opinion, or generate a computer code with critical security flaws. The consequences can be devastating: commercial decisions based on erroneous data, reproduction of discriminatory stereotypes, or dangerous medical recommendations. Beyond the direct damage, these errors threaten the confidence of users and the reputation of companies.
The use of mainstream AI models in a professional environment amplifies these risks. These models, drawn to generic web data, ignore the technical vocabulars and specific processes specific to each sector of activity. Critical data confidentiality issues, regulatory compliance and the use of unable to specific business applications expose companies not prepared for concrete threats: errors, lack of reliability of results and loss of value. To remedy this, they must move towards specialized AI solutions, adapted to sectoral constraints and professional use cases. “
The training appears as the first bulwark in the face of these challenges. Pioneer companies have already understood the importance of raising awareness among their employees about responsible use of AI. Some have implemented internal certification programs before access to AI tools, others have developed clear use charters, accompanied by regular training.
Secure alternatives exist: Professional versions of AI tools with dedicated APIs, self-hosted or deployed bodies on sovereign Cloud also make it possible to secure data from companies.
Towards a new generation of engineers
One of the major factors of these hallucinations lies in the training data which, created by humans, intrinsically reproduce our cognitive and societal biases. These biases are not simply technical errors, but the amplified reflection of the structural discrimination present in our society. Without prevention action, these technologies are likely to perpetuate and amplify gender -based discrimination, ethnic origin, handicap, sexual orientation or age. The diversity of engineers, but also of employees using AI within companies, therefore appears to be a strategic necessity, beyond a simple ethical posture.
Initiatives exist, such as the “Positive AI” label, already awarded to Orange and Malakoff Humanis, which offers a structuring and progressive framework to allow companies to cross clear steps towards a more responsible AI. Ambitious educational initiatives are also essential to attract varied profiles in AI trades, like the “girls and math” plan recently launched by national education to encourage more young girls to choose the tech professions.
Investing in humans remains the key to a responsible AI
The training and diversity of profiles are no longer options, but strategic imperatives for companies wishing to fully benefit from the potential of AI while limiting its inherent risks. Those who will be able to anticipate these issues will develop a certain competitive advantage in the economy of tomorrow.
Companies that will be content to adopt AI solutions without investing in the training of their employees and the diversity of their teams will not only undergo the consequences of hallucinations and discriminatory biases: they will miss their fundamental responsibility towards their customers, their employees and the company as a whole.
The time is no longer for naive technological fascination, but for thoughtful and responsible adoption. Investing in human skills remains, paradoxically, the best way to master the revolution of artificial intelligence.
