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SMEs and VSEs (Very Small Enterprises) can learn several essential lessons from the evolution of artificial intelligence (AI) projects as reported in the article by Grant Gross for the CIO US platform and adapted by Reynald Fléchaux for CIO France.
Today, companies, including SMEs and VSEs, are investing massively in artificial intelligence (AI), often motivated by the fear of missing a strategic opportunity. However, only 25% of projects achieve their objectives, and barely 16% have been deployed company-wide according to an IBM study, highlighting a gap in the preparation and management of AI initiatives. Three years after the debut of ChatGPT, the industry is still struggling to demonstrate a clear return on investment (ROI) for AI projects.
Indeed, many companies venture into AI without identifying a real business need. Many favor experimental projects or “trendy” solutions, like content generation, but forget to address issues essential to their operations and strategy. This often leads to a misallocation of resources.
Another blocking point: the lack of internal preparation. The success of AI projects requires accurate and organized data as well as a well-structured ecosystem. This process demands time, investment, and solid internal skills that many organizations underestimate.
Faced with these failures, companies are adopting a more thoughtful approach: 37% of decision-makers now state they prefer accuracy and slowness over speed and risks. Leaders are relying more on practical and measurable use cases, favoring projects with a direct impact on their business. This more pragmatic strategy shows the importance of mastering the fundamentals before leveraging complex technologies.
For SMEs and VSEs, it is crucial to integrate these lessons:
With an approach centered on business priorities and a well-considered deployment, SMEs and VSEs can leverage AI and avoid costly pitfalls.
