In the frenetic race towards integrating artificial intelligence, many companies miss the essential point: it is not just about automating existing processes. The real challenge lies in using AI to completely rethink how we work.
This is not a mere incremental improvement; it is a fundamental transformation. This approach, which could be termed AI-driven process reengineering, is revolutionising industries and potentially offering unprecedented gains in efficiency, productivity, and innovation.
As Thomas H. Davenport, professor at MIT, aptly puts it, “AI doesn’t just automate existing processes; it allows us to reimagine how companies function. It’s not about doing the same things faster, but about doing fundamentally new things.”
From automation to reinvention: the forgotten paradigm
Imagine if, instead of inventing the assembly line, Henry Ford had merely refined artisanal methods of car production. This is exactly what some companies are doing today when they only automate existing processes without rethinking them entirely. True innovation arises from the audacity to challenge the status quo.
Take the example of a major European bank that did not just automate its customer service – it completely reinvented it. By implementing AI-powered chatbots and intelligent routing systems, the bank reduced call volumes by 40% while increasing sales by 15%. This is not merely replacing humans with robots but deploying new solutions to serve customers more effectively.
As Vikram Pandit, former CEO of Citigroup, rightly points out: “AI in banking is not just about chatbots or automated processes. It’s about reimagining the entire customer journey and creating new value propositions.”
Transforming industries
This AI-driven metamorphosis is impacting all sectors. In the demanding world of pharmaceuticals, an international laboratory leveraged AI to entirely rethink its drug discovery process. Rather than simply speeding up existing methods, they rethought their approach. By using AI to analyse vast amounts of scientific literature and patient data, they significantly reduced the time required for early-stage drug development.
Hal Barron, Chief Scientific Officer of GlaxoSmithKline, highlights this transformative potential: “AI enables us to ask fundamentally different questions in drug discovery. We are not just speeding up traditional methods; we are creating entirely new approaches to finding treatments.”
In the automotive industry, Volkswagen has also embraced reinvention. The company did not simply optimise its design process with AI; it completely reimagined it. By integrating AI capable of generating and testing new designs, they produced components that were 30% lighter and significantly reduced the design time.
AI in industry is not just about robots on assembly lines. It is about creating adaptive, responsive production systems that can learn and improve in real-time.
AI as an ally, not a rival
One of the greatest fears associated with AI is that it will replace humans. However, the most successful applications of AI-driven process reengineering show that it augments human capabilities.
NASA and ESA’s use of AI in their space missions is a perfect example: by reorganising mission control processes to allow for greater autonomy of probes, or by integrating autonomous systems into missions like the Perseverance rover or Φsat-2, these agencies have significantly increased mission efficiency and accelerated decision-making during operations.
As Erik Brynjolfsson, director of the Stanford Digital Economy Lab, says: “The most powerful combinations of AI are those that enhance human capabilities rather than replace them. We must focus on human-AI collaboration, not competition.”
Navigating between progress and caution
Of course, these radical changes come with challenges. Process reengineering requires significant investment, not only in technology but also in upskilling workers and redesigning workflows. It also raises important ethical questions, particularly concerning data privacy and decision-making autonomy.
According to Kate Crawford: “As we integrate AI into our processes, we must remain vigilant about issues such as bias, privacy, and accountability. Reimagining processes with AI is not just a technical challenge; it’s an ethical one.”
It should also be remembered that not all AI projects succeed. A holistic approach is crucial, focusing on value rather than technology for its own sake. Companies must prioritise high-impact areas, adopt agile implementation methods, and encourage collaboration across departments.