Artificial Intelligence (AI) is now establishing itself as a key driver of innovation and competitiveness for small and medium-sized enterprises (SMEs) and mid-market companies. Faced with the complexity and rapid pace of technological change, managers are asking themselves

What are the major challenges surrounding AI for my company?

How can I launch a pragmatic and effective AI initiative?

The major AI challenges for SME/MIB executives

1. Identifying the real drivers of competitiveness

AI offers opportunities for operational optimization, personalized customer experience, and product or service innovation. The main challenge for an SME/MIB is to target the uses with the highest added value, adapted to its resources and sector.

2. Access to skills and resources

Data talent is rare and expensive: it is not always realistic to internalize everything. Several solutions are emerging: ongoing internal training, use of specialized firms, or adoption of “ready-to-use” AI solutions in SaaS mode.

3. Governance and ethics

AI requires careful management of data collection and use, compliance with regulations (GDPR, AI Act), and prevention of algorithmic bias. The trust of customers and partners depends on an ethical and transparent approach.

4. Measuring ROI and steering the transformation

To convince and maintain stakeholder commitment, it is necessary to measure the benefits in concrete terms and steer the transformation in stages, with achievable objectives and a clear vision of the path ahead.

5. Leadership, vision, and change management

AI disrupts habits and can generate fears: leaders must convey the vision, explain the challenges, involve teams, and value the human element in the human-machine partnership.

Practical guide: 5 steps to launch an AI initiative in an SME/mid-market company

1. Define a clear business issue
   Start by identifying a specific pain point or area for improvement in the business (e.g., sales forecasting, automation of time-consuming tasks, customer support, information analysis, writing assistance, etc.).
2. Assess the available data
   Check the quality, quantity, and structure of your internal data: if you don’t have reliable databases, opt for ready-to-use AI or progressive data collection solutions.
3. Surround yourself with the right ecosystem
   Identify technology partners or specialized firms that are suited to the size of your company. Test SaaS AI solutions or join a support program (clusters, competitiveness clusters).
4. Launch a quick POC (Proof of Concept)
   Opt for a short, low-cost experiment on a small scale. Objectively measure the initial results before going any further.
5. Involve and support your teams
   Train and inform your employees from the outset. Communicate objectives, highlight successes, and adapt processes based on feedback from the field.

References to articles and useful resources

• “Artificial intelligence in SMEs: current situation and prospects” — Banque de France, March 2025
• “Practical guide: successfully integrating AI into an SME,” Bpifrance Création, January 2025
• “SMEs and artificial intelligence: obstacles and levers for digital transformation,” La Tribune, February 2025
• “European regulation on AI (AI Act): what are the consequences for businesses?” Les Echos, April 2025
• “The ethics of artificial intelligence in business,” Afnor, June 2025
• “How to launch your first AI initiative: feedback from innovative SMEs,” Maddyness, July 2025

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