Innovation Labs in Corporations

We may be standing at a moment in time for Quantum Computing that mirrors the 2017 breakthrough on transformers – a spark that ignited the generative AI revolution 5 years later. With recent advancements from Google, Microsoft, IBM and Amazon in developing more powerful and stable quantum chips, the trajectory of QC is accelerating faster than many of us expected.   Google’s Sycamore and next gen Willow chips are demonstrating increasing fidelity. Microsoft’s pursuit of topological qubits using Majorana particles promises longer coherence times and IBM’s roadmap is pushing towards modular error corrected systems. These aren’t just incremental steps, they are setting the stage for scalable, fault tolerant quantum machines.   Quantum systems excel at simulating the behavior of molecules and materials at atomic scale, solving optimization problems with exponentially large solution spaces and modeling complex probabilistic systems – tasks that could take classical supercomputers millennia. For example, accurately simulating protein folding or discovering new catalysts for carbon capture are well within quantum’s potential reach.   If scalable QC is just five years away, now is the time to ask : What would you do differently today, if quantum was real tomorrow ?. That question isn’t hypothetical – it’s an invitation to start rethinking foundational problems in chemistry, logistics, finance, AI and cryptography.   Of course building quantum systems is notoriously hard. Fragile qubits, error correction and decoherence remain formidable challenges. But globally public and private institutions are pouring resources into cracking these problems. I was in LA today visiting the famous USC Information Sciences Institute where cutting edge work on QC is underway and the energy is palpable.   This feels like a pivotal moment. One where future shaping ideas are being tested in real labs. Just as with AI, the future belongs to those preparing for it now. QC Is an area of emphasis at Visa Research and I hope it is part of how other organizations are thinking about the future too.

The last two days have seen two extremely interesting breakthroughs announced in quantum computing. There is a long path ahead, but these both point to the potential for dramatically upscaling ambitions for what's possible in relatively short timeframes. The most prominent advance was Microsoft's announcement of Majorana 1, a chip powered by "topological qubits" using a new material. This enables hardware-protected qubits that are more stable and fault-tolerant. The chip currently contains 8 topologic qubits, but it is designed to house one million. This is many orders of dimension larger than current systems. DARPA has selected the system for its utility-scale quantum computing program. Microsoft believes they can create a fault-tolerant quantum computer prototype in years. The other breakthrough is extraordinary: quantum gate teleportation, linking two quantum processes using quantum teleportation. Instead of packing millions of qubits into a single machine—which is exceptionally challenging—this approach allows smaller quantum devices to be connected via optical fibers, working together as one system. Oxford University researchers proved that distributed quantum computing can perform powerful calculations more efficiently than classical systems. This could not only create a pathway to workable quantum computers, but also a quantum internet, enabling ultra-secure communication and advanced computational capabilities. It certainly seems that the pace of scientific progress is increasing. Some of the applications - such as in quantum computing - could have massive implications, including in turn accelerating science across domains.

🌐 Had a fascinating conversation with Sabeer Bhatia (Hotmail co-founder) at TiEcon about the future of computing—particularly quantum. The consensus? 👉 Quantum chips won’t replace digital chips. They’ll augment them—just like GPUs did for AI. We discussed emerging quantum modalities: Superconducting (IBM, Google) Trapped Ions (IonQ, Quantinuum) Photonics (Xanadu, PsiQuantum) Neutral atoms (ColdQuanta) Topological qubits (Microsoft) Some great insights from leaders in the field: 🧠 Chetan Nayak (Microsoft): "Most quantum systems today are like analog radios—fragile and noisy. With topological qubits, we’re building something closer to digital transistors: stable, scalable, and resilient." 🧠 Jay Gambetta (IBM): "Quantum won’t replace classical—it’s about expanding the computational toolbox. The future is hybrid: CPUs, GPUs, and QPUs solving what no one system can." 🚛 Arvind Ratnam (QCNTRL): "Quantum chips are already solving problems where GPS fails—underground, underwater, or in jammed environments. That’s game-changing for logistics, defense, and autonomy." 🔬 Use cases gaining traction: Drug discovery Logistics optimization Post-quantum encryption Quantum-enhanced AI It’s clear: Quantum computing is becoming a critical co-processor layer—not a replacement. The next decade of computing will be hybrid, intelligent, and cross-disciplinary. #QuantumComputing #AI #FutureOfTech #TiEcon #QuantumChips #Microsoft #IBM #QCNTRL #DeepTech #Innovation #HybridComputing

🛑 Mr. Couchonomics Hype Check: Innovation Labs Are the Future of Corporate Disruption Every big company seems to have an “innovation lab,” “garage,” or “studio.” Foosball, beanbags, neon signage and endless slide decks promising the next unicorn 🦄 The theory suggests that one should isolate a small team, give them seed funding, and watch them out innovate the mothership. 📉 Reality check: 85% of innovation-lab projects never reach commercial launch (2022). Unfortunately most of the ideas die in PowerPoint purgatory The causes are depressingly predictable: ❗️Labs are measured on posters and P-O-Cs, not profit and pipeline ❗️Core business units block adoption (“Not-Invented-Here” syndrome) ❗️Incentives favor experimentation over scale-up funding ❗️Leadership churn means pet projects lose sponsorship mid-flight Unfortunately that’s lead to Innovation labs becoming great theatres of creativity, but terrible factories 🏭 of revenue. Real disruption happens when: ✅ KPIs are tied to P&L impact, not demo-day applause ✅ Lab teams embed with (and are funded by) core business lines ✅ CEOs are willing to sunset legacy cash cows to let new bets breathe Until then, the lab is often just a shiny box parked next to yesterday’s strategy. 💬 Have you seen an innovation lab that truly moved the needle? What made it different?

⚙️ 𝗖𝗿𝗲𝗮𝘁𝗶𝗻𝗴 𝘁𝗵𝗲 𝗥𝗶𝗴𝗵𝘁 𝗖𝗼𝗻𝗱𝗶𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻 Innovation and collaboration don’t happen by chance. They’re the result of deliberate choices leaders make—about tools, trust, partnerships, and how they invest. Too many teams talk about innovation without shifting how they actually work. If the conditions aren’t right, ideas stall, silos grow, and collaboration becomes performative. Here are four shifts that can make innovation real 👇 🛠️ 𝗔𝗱𝗼𝗽𝘁𝗶𝗻𝗴 𝗡𝗲𝘄 𝗧𝗼𝗼𝗹𝘀 Innovation isn't about chasing every shiny new tool—it’s about choosing what fits your context and improves value. Prioritise tools that promote transparency, fast feedback, and real collaboration. The goal isn’t more dashboards—it’s better decisions. 🤝 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗖𝘂𝗹𝘁𝘂𝗿𝗲 𝗼𝗳 𝗧𝗿𝘂𝘀𝘁 𝗔𝗿𝗼𝘂𝗻𝗱 𝗔𝗜 AI doesn’t replace ways of working—it transforms them. But without trust, it becomes another top-down imposition. Be clear about why you're using AI. Involve teams early. Transparency earns trust, and trust unlocks adoption. 🌍 𝗪𝗼𝗿𝗸𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗣𝗮𝗿𝘁𝗻𝗲𝗿𝘀 Great collaboration doesn’t come from contracts—it comes from shared purpose. Define roles clearly, run joint retros, and keep feedback loops tight. Don’t just hand off work—bring partners into your learning process. 💡 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗜𝗻𝘃𝗲𝘀𝘁𝗶𝗻𝗴 𝗳𝗼𝗿 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 If you want innovation, budget for learning—not just output. Fund pilot projects. Create space for safe-to-fail experiments. Treat innovation like a portfolio: quick wins and longer-term bets, backed by adaptive funding. The best organisations don’t just talk about innovation—they build the conditions for it to grow. That’s where momentum begins. Which shift is most relevant for your team right now? #Leadership #Innovation #Collaboration #AI #WaysOfWorking #OrganisationalDesign #WorkplaceCulture #BetterDecisions #FutureReady

🏢Introduction to 5G Labs in India 🏢 5G Labs in India are research and development centers focused on catalyzing the 5G ecosystem. They facilitate collaboration between service providers, academia, and industry to harness 5G's potential. Core Objectives 🎯 🌐 Network Evolution: Enhancing India’s telecom infrastructure for 5G readiness. 🤝 Partnerships: Bridging government bodies, tech companies, and educational institutions. 📈 Economic Growth: Leveraging 5G to boost India’s digital economy. Real-Time Examples ⏱️ 📍 Reliance Jio’s 5G Lab in Mumbai: Innovating in areas like IoT, AR/VR, and digital healthcare. 📍 Airtel’s Network Experience Centre in Manesar: Monitoring and testing network performance and security. 📍 IIT Madras 5G Testbed: An academic-industry collaboration to foster 5G technologies. Technological Innovations 💡 🚀 Indigenous 5G Test Equipment: Encouraging the development of local 5G test equipment. 🤖 Smart Manufacturing: Integrating IoT and AI to revolutionize India's manufacturing sector. 🚜 Agriculture Tech: Using 5G for precision farming and enhanced agricultural productivity. Industry Impact 🏭 🏥 Telemedicine: Facilitating remote healthcare services, especially in rural areas. 📚 Education: Enabling interactive and immersive learning experiences. 🌆 Urban Development: Supporting smart city initiatives across India. Challenges and Solutions 🧗 🏙️ Urban-Rural Divide: Expanding 5G infrastructure to rural areas for equitable access. 💸 Investment: Attracting significant investments for large-scale 5G deployment. 📚 Skill Development: Training the workforce in 5G-related technologies. Future Prospects 🔮 📶 Nationwide Rollout: Aiming for a comprehensive 5G network across urban and rural India. 🤖 AI and Machine Learning: Integrating these technologies with 5G for smarter solutions. 🌍 International Collaboration: Partnering with global entities for technological exchange. India's 5G Labs stand as the vanguards of innovation, driving the country towards a digitally empowered future. 🇮🇳💡🚀

90% of innovation labs fail to fulfil their promise. (Here's a trap you need to avoid to ensure yours doesn't) Many companies that establish innovation labs,  regardless of the form they take  — accelerators, business incubators, and research hubs,  easily fall into the innovation lab dilemma. If they keep the lab inside the company,  bureaucracy can easily stifle or neutralise the new idea. But if they let the lab become completely isolated from the core business,  there's often no clear strategy aligned with the company's objectives — or no strategy at all. This lack of strategic alignment leads to the '𝐢𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧 𝐭𝐡𝐞𝐚𝐭𝐫𝐞' 𝐭𝐫𝐚𝐩,  efforts that appear innovative but don't produce any results. Ideas from these labs are disconnected from real customer needs.  Or there's no accountability for driving these ideas to implementation. So, how can you deal with that?  Simply shutting down the innovation lab is not the solution. You have to establish the connection. ✅ Priority #1: Establish clear goals and strategies for the lab that align with the company's overall strategy → What is the aim of the innovation lab? → After an idea is validated, what are the next steps? Where will the idea get further support? → How will the lab connect with end users or customers to address real problems? Next, implement a system to track progress and measure outcomes. Define and track costs and returns, whether financial or otherwise (such as new knowledge or insights). Innovation labs that don't have or can't manage metrics are set up to fail. P.S. Thinking about building your innovation lab or want to talk more about that? You're welcome to visit us at our weXelerate Innovation Hub in Vienna for a coffee and a chat. With 40+ innovators, including giants like Dynatrace, ING, and Santander, there are many innovation inspirations to explore. #innovation #ecosystem #leadership

Let’s take a short break from AI… and talk about quantum computing. Recently I found myself wondering: When should my “trends” slides include a section on the quantum economy? Because something’s shifting. Quietly—but somehow fast. In 2025 (the UN International Year of Quantum Science & Technology), we’ve already seen (weak) signals of change: → Microsoft announced a new type of chip (based on Majorana fermions)—a big step if proven valid → IBM released the second-gen Heron chip with 156 qubits, already used commercially → Google, Amazon, and Nvidia are progressing on error correction, essential for making quantum reliable → Startups like Xanadu, IonQ, Quantinuum are exploring different hardware models—from trapped ions to photonics. And beyond the hardware race, there’s growing talk of “quantum advantage”: The moment when a quantum computer solves a real-world problem that no classical computer can. We’re not fully there yet—but we’re getting closer. Use cases are emerging in: → Drug discovery and molecular design → Logistics and route optimization → Financial modeling and risk analysis → Simulating materials at atomic level And yes, quantum computing might not replace classical computing—but it could surpass it in specific tasks that involve vast probabilities and complexity. As someone who studies future shifts, I think now is the time to start building awareness, not just tech. I feel that I need to learn more about it. The tech is real, but the understanding is not widespread. We might need to: → Translate potential into language business leaders can use → Invest in talent—not just quantum engineers, but maybe quantum cyber experts and decision-makers who get it → Connect quantum progress to broader industry shifts and skills agendas. According to the 2025 WEF report on the quantum economy, industries such as finance, tech and telecom, pharma and healthcare, chemicals and advanced materials, energy, automotive, aerospace, and transportation are expected to be early adopters. Have you started thinking about how quantum might show up in your industry—or is it still too far off your radar? Because maybe, just maybe, now is the right time to start preparing. #Foresight #futureStation #FutureToday

𝐓𝐡𝐞 𝐒𝐞𝐜𝐫𝐞𝐭 𝐁𝐥𝐮𝐞𝐩𝐫𝐢𝐧𝐭 𝐁𝐞𝐡𝐢𝐧𝐝 𝐒𝐮𝐜𝐜𝐞𝐬𝐬𝐟𝐮𝐥 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧 𝐇𝐮𝐛𝐬 𝐚𝐧𝐝 𝐂𝐞𝐧𝐭𝐞𝐫𝐬 𝐨𝐟 𝐄𝐱𝐜𝐞𝐥𝐥𝐞𝐧𝐜𝐞 (𝐂𝐨𝐄𝐬) Most organizations build “innovation labs.” Few create value-generating engines that scale. Here’s the truth: Innovation isn’t luck - it’s a governance-enabled discipline designed to convert ideas into business impact. In 2025, the most successful 𝐆𝐥𝐨𝐛𝐚𝐥 𝐂𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐂𝐞𝐧𝐭𝐞𝐫𝐬 (𝐆𝐂𝐂𝐬) follow one principle: 👉 Start with business problems, not shiny tech. Every initiative must tie directly to a measurable outcome - revenue growth, cost efficiency, time-to-market, risk reduction, or customer experience. Here’s a 𝐬𝐭𝐞𝐩-𝐛𝐲-𝐬𝐭𝐞𝐩 𝐩𝐥𝐚𝐲𝐛𝐨𝐨𝐤 for building your Innovation Hub or CoE that actually works 🔹 Step 0 - Prep for Success • Craft a 2-page Sponsor Brief: vision, top 3 objectives, expected outcomes. • Identify an executive sponsor & business champion. • Form your core leadership team (Program Lead, Tech Lead, HR, Security, Architect). 🔹 Step 1 - Diagnose & Define • Run stakeholder interviews across BU, IT, Legal, Procurement, HR. • Prioritize use cases by business impact × feasibility. • Create a CoE Charter with mission, KPIs, and scope. 🔹 Step 2 - Target Operating Model & Governance • Choose your CoE archetype (Centralized, Hybrid, Distributed). • Design governance: Steering Committee, Product Council, Compliance Review. • Finalize funding model (chargeback, shared, or capex-run). 🔹 Step 3 - Build the Foundations • Establish cloud/data/MLOps/CI-CD platforms. • Create a reusable asset library and compliance templates. • Define your reference architecture and onboarding plan. 🔹 Step 4 - Launch Your Lighthouse • Pick 1–3 high-impact use cases. • Build MVPs, measure success, and scale proven ideas. 🔹 Step 5 - Productize & Scale • Harden MVPs into production-grade solutions. • Develop playbooks, capability pods, and enablement programs. 🔹 Step 6 - Build the Right Talent & Culture • Blend senior expertise with local talent. • Foster innovation rituals - demo days, hackathons, show-and-tells. 🔹 Step 7 - Governance, Risk & IP • Clarify ownership of IP, data governance, and ethical AI standards. • Integrate compliance and security reviews into delivery. 🔹 Step 8 - Measure & Improve • Define KPIs: impact, efficiency, quality, ROI. • Review quarterly and capture lessons learned. 🔹 Step 9 - Scale & Partner Ecosystem • Expand across BUs and domains. • Build startup, academia, and vendor partnerships for acceleration. 🔹 Step 10 - Sustain the Engine • Institutionalize operations and governance. • Embed continuous improvement and innovation cycles. follow Devjyoti Seal for more GCC insights

A CEO asked why his innovation lab stalled. I asked one question - and he went silent. When a tech CEO shared: "We have smart people. We invested in tools. We created an innovation lab. But nothing's happening." I asked just one question: "When was the last time someone on your team openly disagreed with you?" His silence told the whole story - his leadership style silenced them. McKinsey research reveals a startling truth: 85% of innovation practitioners report that fear consistently holds back innovation, yet only 26% of leaders create psychological safety for their teams. The most expensive item in your boardroom isn't the technology. It's the breakthrough idea that remains unspoken. Here are the five patterns agile leaders use to build psychological safety for innovation: 1. The Visible Vulnerability Pattern 🛡️ ↳ Start innovation meetings by sharing your biggest recent mistake ↳ Publicly celebrate lessons from failures, not just wins ↳ Replace "Who's responsible?" with "What system failed?" 2. The Idea Protection Protocol 🌱 ↳ Implement the 2-minute rule: No criticizing ideas for first 2 minutes ↳ Create "rough draft" zones where half-formed concepts are sacred ↳ Eliminate phrases like "we've tried that before" 3. The Silence Breaker Method 🔑 ↳ Start with written ideas before verbal sharing ↳ Track speaking patterns to identify whose voice is missing ↳ Use anonymous submission channels for high-risk ideas 4. The Curiosity Framework 🔎 ↳ Respond to all ideas with: "What would make this possible?" ↳ Replace "yes, but" with "yes, and" language ↳ Ask "what am I missing?" at decision points 5. The Agile Experiment Loop ⚡ ↳ Define "micro-experiments" that can fail safely ↳ Create 24-hour innovation sprints with protected failure zones ↳ Document both successes AND instructive failures Last quarter, a client team using these methods uncovered a product insight that led to their most successful launch in 3 years. From my Olympic training to executive coaching, I've seen this pattern repeatedly: Elite performance doesn't emerge from comfort. It emerges from psychological safety balanced with high expectations. What signals are you sending about risk and innovation? Please share below ⬇️ ♻️ Repost to help leaders unlock trapped innovation 🔔 Follow Eva Gysling, OLY for more