Trust, Agency, and the Innovation Paradox

By Pierre Baqué, CEO & Co-Founder, Neural Concept
‍

What makes some companies so innovative while others spend millions in innovation to end up struggling to deliver radical change? Innovation budgets are continuously growing and dedicated innovation teams are multiplying, yet operational innovation – the kind that truly changes how products are designed and delivered – remains rare.‍

The problem is usually not technology, talent or ambition: it is trust.

‍

The Innovation Paradox

Innovation is what makes businesses flourish or die today. Every company, in almost every industry, particularly in advanced technologies and manufacturing, has now understood that the insane current progress of AI technologies will create exponentially growing gaps between businesses who are capable of embracing AI in their core processes and others. 

What makes innovation work or die in a business? What cultural elements make the success of an AI adoption strategy? After helping hundreds (literally) of companies adopt AI over the last 5 years I want to share some observations. 

In many organizations, innovation is treated as something separated from operations. Companies create dedicated “innovation teams”, tasked with exploring new ideas, new technologies, and new approaches. 

At first glance, it seems logical. But structurally, it creates a distance between those who imagine the change and those who must implement it. And over time, the gap widens: Innovation teams explore, operational teams deliver, and the two rarely converge. 

{{highlight}}

‍

Excitement and disillusion in bringing innovation to European industry:
the Neural Concept experience

When we launched Neural Concept in 2018, we were coming to the market with a breakthrough, unique technology that no one had ever heard of: Generative and Physics based Neural Networks for 3D engineering. 

At the time, we got a strong initial interest coming from  large European corporations, typically known for their struggles in implementing innovation. That was exciting and surprising. Had we found a good market of early adopters, ready to expand? We started establishing collaborations, licensing our code and iterating with the needs of these early customers.

We were wrong. We quickly understood that we might actually be very far away from our goal of transforming the industry. Although they were genuinely interested and eager to learn, our “early adopters” were often part of dedicated innovation or research groups, created precisely to facilitate and ignite innovation in those large corporations. These teams were curious, forward-looking, and eager to experiment, but translating that curiosity into real deployment proved difficult: the gap between innovation units and day-to-day engineering operations was significant. In fact, these teams shared our challenge: they had to “sell” innovation internally to operational colleagues who held the actual business pain. So we hadn’t reached our customers, we had just passed our mission to intermediaries who were clearly less motivated about our technology’s success than we are, less expert with our product and no industry-wide perspective. 

At the same time, we were struggling to convince other companies, reportedly faster, more innovative and with forward looking product developments, to use our tool – which was lacking maturity.

Real traction came later. As our technology matured, we suddenly got a very strong pull from the US and from the cost-pressured automotive industry, but the team profile was different: we were not talking to “innovation” teams anymore but to operational engineers working under genuine delivery pressure. They could start observing the value of our technology and being able to implement it on their own. The most striking fact is that, despite being very innovative, process innovation and exploration is never a goal for those teams. Their goals are execution, delivery and product quality. What makes them innovate on methods is the pressure to innovate on outcome and the capabilities given to them to do so.

‍

The Slippery Slope of R&D teams 

What we experienced is not anecdotal. It reflects a deeper organizational pattern. 

I postulate that the creation of dedicated “Innovation” teams for a business is a slippery slope that needs to be handled carefully. The alternative model, where innovation trust is maintained within operational teams, is more effective.  This might cause other organizational challenges and go against the sole productivity focus of the teams, but I believe that this is the best approach to both operational efficiency and innovation. In every company we have seen making this shift, the pattern is consistent: give engineering teams genuine ownership of innovation, accept the temporary friction of changing how people work, and they will deliver more innovative products, faster – more than any dedicated innovation unit ever could.

This difference in organization and how close innovation is to the core business is the most striking contrast I have observed between traditional European companies and innovation-oriented technology companies (in the US, in Europe or in Asia). It is rooted not only in organizational structure, but in how deeply teams are trusted to innovate and progress, independently from a pre-set roadmap imposed by top management. 

Europe has the talent, the engineering depth, and the industrial complexity to lead the next wave of AI-driven product development. What it often lacks is the organizational courage to trust the people closest to the problem. The companies that will win are not those with the best innovation strategy on paper, they are those who have the confidence to empower, create a culture of disruption and give the resources for their teams to evolve. 

‍