The Future of Innovation Labs in Corporations

🔮 The Self-Driving Labs of the Future: Form Should Follow Function When we talk about self-driving labs, the common vision we’re offered is a futuristic laboratory—designed for human operation but run by humanoid robots. At first glance, this makes sense. It’s a straightforward extension of today’s labs: replace an 8-hour human shift with a robot that operates 24/7, and suddenly, research accelerates. But in reality, this model is not the most economical, safe, or efficient. Commercial cloud labs have already moved in a different direction—functioning more like fulfillment centers, where human labor operates at the physical layer while AI orchestrates the workflows. This approach optimizes throughput and cost rather than just replacing humans with robots. So what will the labs of the future really look like? The form should follow function. If the true goal is to accelerate research at scale, self-driving labs will resemble reconfigurable production lines, integrating: 🔹 Modular automation – Tools interconnected via gantry systems, robotic arms, and transfer stations, enabling execution of dynamically reconfiguring workflows. 🔹 Multi-scale sample handling – Systems designed to manipulate everything from nanomaterials to large-scale synthesis seamlessly. 🔹 AI-driven orchestration – Not just running individual experiments, but actively planning, optimizing, and adapting research pathways. This is where we can draw a direct comparison to today’s fulfillment centers—dense with robots, conveyor networks, and human oversight in strategic roles. The efficiency comes from integrated automation, not from mimicking human workflows. Will there still be labs with humanoid robots working alongside humans? Most likely, yes—especially in cases where: ✅ Human-in-the-loop training is needed. ✅ Small-scale efforts require cost-effective, flexible automation. ✅ The cost of humanoid robots drops significantly. But the true acceleration of research will not come from retrofitting humanoid robots into traditional labs. It will emerge from fundamentally rethinking lab design, building self-driving research environments that optimize for automation first, not human ergonomics. The biggest breakthroughs will come from labs that look entirely different from what we imagine today. What do you think—how far are we from this reality? 🚀🔬 #Automation #AI #SelfDrivingLabs #FutureOfResearch

The announcement from #vwgroup on its intent to form an #AI company is interesting, meaningful, and in line with my research over the last decades. Volkswagen has established a specialized “AI Lab” as a globally networked competence center and an incubator. It will identify new product ideas for the Group and coordinate them internally within the Group. It will not be limited to internal competencies. Still, it will actively invite external collaboration with technology companies to tap into the innovation potential and take advantage of the speed of the AI sector. Vijay Govindarajan (VG) and I write in our book, #FusionStrategy, that the new pockets of value in traditional industry sectors will be unlocked through real-time data and algorithms. Most industrial companies have succeeded in digitizing business processes inside their companies and, in many cases, with their extended supply chains. That has contributed to efficiency benefits, but much more is possible and will be realized in the decade ahead. The digitization of industrial products and business models is different. That requires a higher degree of coordination amongst the CxO teams. One option to consider is creating a central unit, such as what #vwgroup aims to do. Allowing for rapid infusion of ideas from an extended ecosystem of partners is a way to guard against potential disruption from ambitious startups who know how to attack with their agility and speed. Winning in the fusion future is more than starting AI projects to overlay on the old business models. Such AI labs--if they are to be truly strategic and transformative--should reveal how and why the value is likely to shift from standalone automobiles to the role of automobiles as computers-on-wheels connected to the cloud in the broader mobility and sustainability ecosystems. This idea should be of interest not only to other traditional automakers but also to leading legacy industrial companies in many sectors. #DigitalMatrix

When uncertainty looms, innovation teams are at risk of being on CFO’s chopping block. Most recently, I joined a half-day roundtable with an outstanding group of corporate innovators, convened by Peter Temes at the ILO Institute during which we tackled this pressing reality and paradox: Companies invest in innovation during good times... but they NEED it most during uncertain ones. This plays out in two ways: 🚫 The First Camp: Slashes innovation budgets at the first sign of trouble. "We’ll restart when things stabilize," they promise. By the time stability returns, competitors have already leapt ahead. 🤦♂️ The Second Camp: Keeps innovation teams intact—but strangles their impact. ROI on experiments must be immediate. Quarterly returns on long-term bets. Zero tolerance for the failures that actually drive learning. I’ve seen both—sometimes inside the same company. The result? Innovation teams lose morale. The best talent disengages—or walks. Stakeholders pull support. A "one-and-done" mindset kills promising ideas before they can grow. 💡 Look at financial services. They came late to the internet, mobility, and social media. Now they’re risking the same mistake with AI, ceding direct customer relationships to fintechs and risking relegation to utility status. Why does this cycle persist? Because the short-term savings of cutting innovation are immediately visible. The long-term catastrophe is invisible... until it's too late. 🔥 Here’s how to keep innovation alive when budgets tighten: 1️⃣ Dramatically lower the cost of individual experiments 2️⃣ Prioritize customer-backed innovation for real-time feedback 3️⃣ Create distributed innovation networks across the org 4️⃣ Speed up cycles by challenging slow status quo processes 5️⃣ Position innovation as risk management, NOT risk-taking ⏳ Don’t let uncertainty kill your company’s future. The best organizations don’t innovate despite uncertainty. They innovate because of it. 🚀 Innovation isn’t a luxury—it’s a lifeline. Julie Fishman, Alex Trotta, Miles Garrett, Andy Grove, Anthony Di Bitonto, Kate Pomeroy (née Stubbs) #innovation #leadership #learning