Introducing autonomous innovation; an always-on innovation engine
Philippe De Ridder
CEO and Founder
Innovation is undergoing a tectonic shift. As AI advances, we find ourselves heading towards a new era — one where innovation is not just constant but autonomous. Welcome to Autonomous Innovation; where artificial intelligence and human imagination unite to revolutionize the way we imagine, create, and launch new ideas.
From design thinking to Autonomous Innovation
In the 1990s, design thinking emerged, prioritizing empathy and iterative prototyping for user-centric solutions. By 2010, the Lean Startup methodology built upon these principles, emphasizing rapid experimentation and customer feedback to guide businesses towards sustainable business models. Both paradigms transformed innovation approaches worldwide. The emergence of Creative AI marks a historic development in innovation. Autonomous innovation leverages artificial intelligence to supercharge the innovation process, making it faster, more efficient, and at times even self-directed. This is not just another technological upgrade—it’s a paradigm shift.
What is Autonomous Innovation? The definition of what’s next
Autonomous Innovation is not about integrating AI into an existing system but about reimagining the entire innovation cycle. It’s about developing an always-on innovation engine that leverages AI to constantly imagine, create, and launch new products and services, with exceptional quality, speed, and success rates that were previously unimaginable.
Imagine a scenario where your business’ next big idea is generated while you’re asleep. Or a world where products evolve on their own, drawing from real-time user feedback. That is Autonomous Innovation.
The proof is in the pudding
AI has unique capabilities for synthesis, ideation and modeling human behavior. GenAI-generated ideas are already outperforming human ideas. The below charts show that for ideation, a human+AI collaboration yields the best results. In essence, when GPT-generated ideas get rated by an independent (human) customer panel and the best ideas get fed back to the LLM, the average idea quality will improve even more.
Large Language Models have a unique capacity to model customer personas and panels to work with across the whole innovation journey. It is obvious that Simulated Human Samples will never be able to mimic customers better than humans themselves, but these first results are promising, especially given that humans are not always able to state their own future behavior accurately.
There is no time to waste; the first movers are already leveraging AI to create new products and services
Coca-Cola is unleashing Y3000, a soda co-created between humans and AI that is meant to taste just like the year 3,000.
AB InBev has created the world’s first beer and full marketing campaign made with AI, naming it Beck’s Autonomous.
To create this product for Gen Z, Unilever worked with specially designed AI to analyze 6,000 perfume ingredients with 3.5 million potential combinations.
AI is enabling the discovery of new drugs by autonomously ideating and testing potential new molecules for existing conditions.
Building towards a new innovation engine
With the power of AI in innovation, we are building towards a new innovation engine, where AI helps us generate a concept, validate it and provide customer insights, so humans can curate the ideas to inform an innovation investment decision.
And we’re evolving towards autonomous innovation, where AI will generate the concept, validate it and make an informed decision – all at unprecedented speed and quality.
As an example, imagine a global fashion brand, where their Autonomous Innovation engine generates thousands of new fashion concepts, then validates them in a shop, and concludes with providing the decision on which concepts to kill or scale based on the collected data.
What the future of Autonomous Innovation will bring
From governance to new products, Autonomous Innovation will help us overcome current, human constraints and open the door to boundless innovation.
Autonomous innovation methodologies
Improving the speed, depth and breadth of innovation – resulting in increased investment confidence through hyper-validated concepts and adaptive outputs.
Autonomous innovation governance
Better coordinated corporate innovation activities, relying less on manual data capture, more accurate data and better decision-making.
Autonomous innovations
New products, services and businesses that adapt and improve themselves to be more inclusive and better meet the needs of individual consumers.
Autonomous go-to-market models
‘Launching and learning’ in the market in real-time with autonomous feedback loops – resulting in launches that stick.
Autonomous customized GPT models
Custom methodologies that rely on internal company or project data – creating a competitive advantage against startups.
"Autonomous Innovation isn't just another tech upgrade; it's a shift in the very way we perceive and execute innovation. Those who pioneer in adopting this approach stand to gain a considerable competitive advantage"
The future of innovation is here, and it’s autonomous
Embracing this shift means stepping into a world where algorithms meet aspirations, where innovation is unbound, and where AI and human ingenuity merge to redefine the way we build tomorrow’s products and businesses.
Autonomous Innovation strategy
Develop your strategy for the future role of AI in innovation – to develop an always-on innovation engine that imagines, creates and launches new products and services with unprecedented quality, speed and success.
