Moving from experimentation to industrialization of AI
Artificial intelligence (AI) is no longer just a technological breakthrough; it has become a major strategic lever for businesses. According to the Superagency in the Workplace report, 92% of companies plan to increase their investments in AI in the next three years, but only 1% consider themselves “mature” in its deployment.
Why this gap? Because most companies still treat AI as an experimental project, without a comprehensive vision or deep integration into their processes. However, tomorrow's winners will be those who can move from experimentation to industrialization to make it a driver of sustainable competitiveness.
The most common mistake is to treat AI as a technological gimmick, unrelated to the overall strategy. To avoid this, you must:
- Identify business priorities where AI can have a major impact: innovation, cost reduction, improving customer experience, etc.
- Define strategic use cases with measurable objectives.
- Make AI a central part of the business model, not just an improvement to existing processes.
Consider the case of a manufacturing company. Rather than using AI solely to optimize the supply chain, it could integrate it right from the R&D phase to accelerate design and prototyping. The result? A gain of several months on the innovation cycle, a decisive advantage over the competition.
The Superagency report highlights a striking paradox: employees are more ready than their leaders think. Yet, 48% of employees say they lack the training and support to use AI effectively.
What should be done ?
- Train all levels of the company, from management to operations.
- Create AI acculturation to allay fears (job replacement, algorithmic bias, etc.).
- Encourage managers to be drivers of adoption, because they are the ones who support change on a daily basis.
A technology company has established a network of "AI Champions," employees trained in AI and tasked with helping their colleagues integrate these tools into their daily work. The result? Adoption tripled in one year.
Many companies invest in Proof of Concept (POC) tests but never manage to scale them up. As a result, they accumulate tests without any real impact.
To avoid this :
- Integrate AI into business processes from the start.
- Establish clear governance with precise KPIs.
- Ensure regular monitoring and adjust projects based on feedback from the field.
A banking company successfully deployed an AI chatbot in less than six months by following these principles, improving customer satisfaction by 20%.
AI offers immense opportunities, but to take full advantage of them, companies must integrate it strategically, train their teams, and quickly move from experimentation to industrialization. Only then will they be able to remain competitive in a constantly changing world.
To learn more: discover how Transform your business processes with AI, how successfully making the transition to AI and why AI is a new form of work.