Artificial intelligence is revolutionizing tender processing, but its use raises legitimate questions. Let's examine the potential risks and how to manage them.

Key Challenges

Analysis Reliability

Analysis reliability represents the first major challenge. Indeed, despite its power, AI can sometimes miss critical information or misinterpret important nuances. In worst-case scenarios, we even speak of hallucinations, where AI invents things disconnected from reality. Special or atypical cases can also pose problems. Experience gained through practice, vigilance, and human validation are essential to guarantee the quality and reliability of construction project analysis.

Regulatory Compliance

Regulatory compliance also raises significant questions. The issue of legal liability in case of error must be clearly established. The protection of sensitive data and compliance with confidentiality rules are also crucial, as is the ability to ensure complete traceability of decisions made with AI assistance.

Technological Dependency

Technological dependency constitutes a third significant challenge. Over-reliance on AI tools could lead to a gradual erosion of human expertise. It is therefore essential to maintain and develop internal skills while ensuring continuous team training.

Best Mitigation Practices

Hybrid Approach: AI Serving Humans

A hybrid approach with AI serving humans emerges as the most relevant solution. This technology should be considered as a support tool and not as an autonomous decision-maker. Systematic validation by experts and maintenance of traditional control processes are paramount.

Ensuring Process Control

How to ensure process control? Security, traceability, and control are the key words. The transparency of AI operation, particularly in displaying sources used for tender analysis, helps ensure system reliability. Regular manual verification of results complements this control system.

Maintaining Skills

Maintaining skills remains vital. Beyond tool usage, teams must maintain their professional expertise and ability to process files manually if necessary. Initially, it's important to only entrust time-consuming and tedious tasks that don't require human intelligence in the strict sense (reflection, decision-making...). This approach contributes to developing a balanced corporate culture.

Practical Recommendations

For optimal use of AI in tender processing, it's essential to clearly define its scope of use. Validation processes must be formalized and rigorously followed. Regular team training in methods and tools coupled with active technological monitoring helps maintain the necessary level of expertise. All while benefiting from extraordinary performance.

Conclusion

AI in tender processes represents a major optimization opportunity but requires a thoughtful and controlled approach. The key to success lies in the balance between automation and human expertise, allowing to make the best use of these new technologies while managing associated risks.