Remote Innovation Management

Last week, I held a quantum computing chip in the palm of my hand. Minutes earlier, I stood in front of WEIZAC—a 1950s computer that filled an entire room to deliver a fraction of your phone's computing power. The physical contrast is striking, but the strategic lesson is more profound: we're at a similar inflection point with AI today. 🔬 The Ecosystem Advantage What caught my attention wasn't just the technology—it was the ecosystem. Leading research institutions spinning off commercial ventures, which then contribute talent, capital, and real-world problem sets back to academic labs. This flywheel effect is how breakthrough research becomes market-defining companies becomes next-generation research. ⚛️ The Quantum-AI Parallel Quantum isn't just another computing paradigm—it's a reminder that the AI systems we're deploying today will seem primitive compared to what's being developed in research labs right now. Just as classical computing evolved from WEIZAC to quantum chips, AI will evolve from today's large language models to architectures we're only beginning to imagine. 💡 What Should Businesses Do? Don't just track the market – Stay connected to research organizations pushing the boundaries Look beyond today's deployments – The trends reshaping your industry in 5-10 years are being discovered in labs right now Build ecosystem connections – The companies that maintain strong ties to innovation hubs see the future coming first   The future doesn't arrive uniformly. It emerges from these innovation ecosystems, and proximity matters. 

Platformizing India’s Startup Future If India wants to become No.1, we don’t just need startups. We need a startup engine. And that engine must begin in colleges. Right now, what happens? Effort happens. Data disappears. Ecosystem never compounds. Every academic year resets. New students. New projects. Same mistakes. Same reinvention. We keep building… but we don’t stack. 👉 Without a platform approach, talent remains invisible. 👉 Without structured data, interventions remain emotional, not evidence-based. 👉 Without compounding, ecosystems stay fragile. ⸻ Platformization Changes the Game I recently came across InUnity - Innovation for Community – a digital competency and innovation platform designed exactly for this gap. What does it really do? • Captures student capability beyond academics • Records toolset, skillset, mindset • Tracks projects, internships, hackathons, certifications • Maps entrepreneurial traits (10-trait assessment) • Creates a live digital twin spider map across 8 core skills • Aggregates digital footprint across platforms Now this is powerful. Because when you capture the right parameters consistently, you don’t just store data — you create a digital twin of the student. And once you have digital twins + cohort data, magic begins. You start seeing: • Cause-effect of interventions • Which workshop improved what skill • Which hackathon led to startup formation • Which mentor interaction increased conversion to incubation That’s recursive learning. That’s compounding intelligence. ⸻ Real Ecosystem Impact This model is already implemented in Karnataka: • 30,000+ students • 100+ MSME challenges solved • 5 regional clusters In Maharashtra, under Nagpur Entrepreneurship Mission & Nagpur Next: The pilot is underway • 2,000 students • 20 live MSME challenges • TRL-based tracking lined up • Would ultimately create funnel of Startups flow into incubators ⸻ What Platformization Enables A. Skill gap analysis mapped to specific industry job roles B. Personalized recommendation of events & courses C. Smart matching of companies with closest-fit student inventory D. Guidance on which toolsets and skillsets to sharpen E. Continuous competency capture improving talent visibility This is not activity. This is structured talent manufacturing. This builds a talent intelligence layer connecting academia, industry, and entrepreneurship. ⸻ And here’s the key insight: When effort compounds, ecosystems rise. When effort resets, ecosystems stagnate. India doesn’t lack talent. India lacks structured compounding. Platformization is not a tech choice. It is a national competitiveness strategy. Time to move from scattered initiatives to a recursive, data-backed, compounding ecosystem. 🚀

The convergence of emerging technologies such as AI, immersive interfaces, and digital representations of people and customers will progressively redefine the dynamics of sales, shaping more adaptive, personalized, and emotionally aware interactions. In recent years we have seen strong signals of this transformation. Gartner has identified seven disruptions that are accelerating change: machine customers, multimodality, generative AI, augmented and virtual reality, emotion AI, digital humans, and the digital twin of the customer. Each of these elements carries a specific impact, but together they form an ecosystem that is starting to alter how companies design their customer experience strategies. Generative AI is already being used to create tailored content and recommendations. Emotion AI adds a new layer of sensitivity by interpreting sentiment and intention. Digital twins of customers allow organizations to simulate behaviors and predict preferences with growing accuracy. When combined with immersive tools such as AR and VR, these innovations create environments where engagement becomes more natural and interactive. The question is not only how to adopt these technologies, but how to shape them in ways that create value and trust in the relationship with customers. #AI #Sales #CustomerExperience #DigitalTransformation

Modern corporations are creating innovation ecosystems where internal teams work directly with portfolio companies, sharing resources, expertise, and market access. This integration goes far beyond traditional corporate-startup partnerships: ➡️ Shared Technology Platforms: Portfolio companies gain access to proprietary corporate platforms and APIs, while corporations benefit from rapid external innovation cycles. ➡️ Cross-Pollination of Talent: Employees move between corporate R&D teams and portfolio companies, creating knowledge transfer and cultural bridges. ➡️ Collaborative Product Development: Joint development projects between corporate teams and startups are becoming more common, leading to products that neither could create independently.

Now published – Digital Service Innovation in B2B Markets. In this paper, we identify key service- and digital technology-driven B2B innovation modes. Specifically, we focus on the three dimensions of service innovation: the service offering (the service product, or the ‘what’), service process (the ‘how’), and service ecosystem (the ‘who/for whom’). We then examine the implications of the following three digital technologies for service innovation: Internet-of-things (IoT), intelligent automation (IA), and digital platforms.   We find that IoT can transform physical resources into reconfigurable service products, IA can augment and automate a rapidly expanding array of service processes, and digital platforms provide the technical and organizational infrastructure for the integration of resources and stakeholders within service ecosystems. We are grateful to Marco Opazo, Oscar F. Bustinza and Chris Raddats, the editors of this special issue in the Journal of Service Management, for curating an excellent collection of articles on digital service innovation. Thank you!    Christian Kowalkowski Michael Ehret #B2B #AI #ArtificialIntelligence #IA #IntelligentAutomation #Innovation #IoT #InternetOfThings  

💡 A Paradigm Shift in Innovation: Are you ready for the compounding effects of Tech Convergence? The World Economic Forum’s latest report reinforces what Amy Webb has been proposing for years. We are no longer witnessing individual tech breakthroughs. Instead, we're in an era of deep “Tech Convergence”, where tectonic shifts in a multitude of technologies occuring in parallel begin to converge, slowly and then suddenly. This isn't just another buzzword; it's a fundamental reshaping of industries, value chains, and competitive advantage. The report introduces the powerful 3C Framework - 1️⃣ Combination: The report identifies eight key technology domains—from AI and Omni Computing to Engineering Biology and Quantum Technologies—that are not just advancing in parallel but are being actively *combined*. Think of AI enhancing next-gen energy grids or spatial intelligence revolutionizing robotics. In telecom, this means combining Edge AI with 5G/6G networks to create truly intelligent, decentralized systems. 2️⃣ Convergence: These tech combinations are dissolving traditional industry silos. For telecom, this is a pivotal moment. We are no longer just connectivity providers. By integrating AI, IoT, and spatial intelligence, we are moving into new value chains—becoming the central nervous system for autonomous vehicles, smart cities, and remote healthcare. The opportunity? To shift from providing infrastructure to enabling entire ecosystems. 3️⃣ Compounding: As these converged solutions scale, they create exponential returns. Network effects, cost reductions, and the emergence of new standards accelerate innovation in a self-reinforcing cycle. For instance, as intelligent grid systems powered by our networks become standard, the demand for more advanced connectivity and data processing will explode, fueling the next wave of investment and innovation. Key Takeaways for businesses: - Beyond Connectivity: Our future value lies in enabling the convergence of other technologies. We are the backbone upon which intelligent, autonomous systems will be built. - Ecosystem Leadership: The race is on to establish and lead new ecosystems. This requires strategic partnerships across industries—from automotive to healthcare and energy. - Strategic Investment: It's crucial to balance our portfolio between mature technologies (like cloud infrastructure) and emerging ones (like quantum communication) to capture value at every stage of the 3C cycle. The message is clear: the winners of tomorrow will be those who master the art of technology convergence. We must move beyond segmented thinking and embrace a systems-level approach to innovation. Every business will have to begin with a serious diagnostic of their level of maturity and readiness to be able to embrace these transformative platform shifts. #TechConvergence #WEF #Innovation #AI #Telecom #5G #6G #FutureOfTech #Strategy #DigitalTransformation #IoT #QuantumComputing

Very happy to see our special issue examining the interface between strategy and digitalization - co-edited by Marko Kohtamäki, Rodrigo Rabetino, Vinit Parida & myself - out in it's entirety in International Journal of Management Reviews! Our editorial article (depicted below) conducts a review of the field from four perspectives: ▶️ Digital transformation - studies covering how organizations and their environments engage with digital technology-related transformation ▶️ Digital strategy - studies covering the enabling and conditioning effects of digital technology to strategies and strategizing ▶️ Digital business model innovation - studies examining the changes and novelties afforded in firm's business models by digital technology ▶️ Digital marketing - studies focusing on the changing role of marketing and sales in digital channels and facilitated and transformed by digital technology In my view, all these four fields are interconnected and interlaced with each others, but at the same time, there is interesting research focusing on each approach specifically. Link to the editorial article: https://lnkd.in/dsk9vQWE The special issue includes five great contributions: 1️⃣ "Uncovering the impact of digital technologies on strategising: Evidence from a systematic literature review" by Qijun Zhou et al https://lnkd.in/db-rWz9z 2️⃣ "Open strategy and digital transformation: A framework and future research agenda" by Thomas Ortner et al https://lnkd.in/dxVGVqeA 3️⃣ "Digital transformation in large established organisations: Four restructuring dilemmas based on dynamic capabilities" by Anastasia Kulichyova https://lnkd.in/dVSBEtyF 4️⃣ "Digital-sustainable business models: Definition, systematic literature review, integrative framework and research agenda from a strategic management perspective" by Maximilian Palmié et al https://lnkd.in/dSFSNMVU 5️⃣ "Digital ecosystems and their impact on organizations—A dynamic capabilities approach" by Felix Volz et al https://lnkd.in/dPSS3PEx Thank you all authors who submitted to the special issue, all reviewers, and the editors of the IJMR for your support! #Digital #Strategy #BusinessModel #Ecosystem #Data #Marketing

Technology today is more than infrastructure—it’s the foundation on which economies, societies, and organizations operate. But as we accelerate digital transformation, a pressing question arises: Are we building digital ecosystems that are not just fast and efficient, but also sustainable, resilient, and future-proof? Why This Matters - Sustainability: With data centres consuming massive amounts of energy, and e-waste becoming one of the fastest-growing waste streams globally, the digital economy has a real environmental footprint. Green IT, energy-efficient architectures, and circular design models aren’t optional anymore—they’re critical. Resilience: From cyberattacks to supply chain shocks, the digital world faces constant disruption. Systems need to be designed not only to recover but to adapt and thrive under change. Inclusivity & Accessibility: A resilient ecosystem is one that works for everyone. Bridging the digital divide ensures that growth isn’t limited to a few but is shared broadly across communities and economies. Trust & Responsibility: Privacy, ethical AI, and transparent governance are the cornerstones of a responsible ecosystem. Without trust, digital adoption cannot scale. What Does a Sustainable & Resilient Digital Ecosystem Look Like? - Green Cloud & Infrastructure – Data centres powered by renewable energy, carbon-aware computing, and optimized workloads. - Adaptive Cybersecurity – AI-driven threat detection, zero-trust architectures, and proactive risk management. - Digital Inclusion – Affordable access, user-friendly design, and accessibility-first solutions. - Responsible AI & Data Use – Bias-free AI, ethical data governance, and strong privacy frameworks. - Collaborative Ecosystems – Governments, businesses, and innovators co-creating standards, interoperability, and shared platforms. The Way Forward Sustainability and resilience are no longer “nice-to-haves.” They are strategic imperatives for digital transformation. Leaders who prioritize them today will shape digital ecosystems that are future-ready, trusted, and impactful. Let’s shift the conversation from “How fast can we go digital?” to “How responsibly, inclusively, and sustainably can we build digital ecosystems that endure?” Because the future is not just digital—it’s sustainably digital and resilient by design. #DigitalTransformation #Sustainability #Resilience #Innovation #TechForGood #FutureOfWork

After many years of analysing the "triple helix effect" in Australian and global contexts, I've observed a persistent gap between innovation ecosystem potential and actual performance. We excel at mapping connections—between universities, businesses, and government agencies—but struggle to activate these dormant relationships. The critical insight? Having someone's contact details (even on LinkedIn) differs vastly from genuine collaboration. The transformation requires three elements: problem-focused interaction around specific challenges, trust-building through repeated engagement, and governance mechanisms that align different organisational incentives. Most ecosystems exist in "structural potential" rather than functional activity. Universities house transformative research locked in publications. Corporations possess the capabilities to solve social problems but lack pathways to community organisations. Government agencies hold regulatory knowledge that could accelerate innovation, yet operate in isolation. The solution isn't just more networking events. It's creating focal challenges that demonstrate mutual value, supporting system integrators that speak multiple "languages," and designing incentive structures that reward collaboration over transactions. For policymakers: ecosystem activation can be catalysed but cannot be mandated. Focus on creating opportunities for valuable collaboration rather than requiring it.: https://wix.to/zJN0qgM #InnovationEcosystems #Trust #InnovationManagement

“Your Moat Is the Ecosystem” — Jensen Huang on Strategic Advantage Today, I watched a fantastic conversation between Perplexity CEO Aravind Srinivas and NVIDIA CEO Jensen Huang, where Huang unpacked why building a product is just the beginning, and why ecosystems are the real engine of long-term impact and defensibility. Some key points from this discussion that I am sure will be relevant to the partnership communities. 1. Your product isn’t enough. “Your strategy is beyond the product you’re making... It’s not just what you make, but how you take that product to market, how you position among others, and maybe the ecosystem around you that supports the product.” What does this mean: In AI world, great tech without the ecosystem is a dead end. Ecosystems drive adoption, relevance, and defensibility. 2. Ecosystems can make or break adoption. The failure of NV1 wasn’t just about technical decisions, it was that no one could build on it. Developers had no tools. Applications had no support. “No tools could really handle that… No application developers could deal with it.” What does this mean: If your ecosystem can’t engage, your innovation won’t land. 3. CUDA’s success was ecosystem-first. CUDA wasn’t just a better compute architecture—it became a platform because Nvidia committed the entire company to building the ecosystem around it. “Everything inside the company had to be CUDA-compatible. Everything outside the company had to be CUDA-compatible.” That required evangelism, APIs, developer support, and relentless discipline—ecosystem as strategy, not afterthought. 4. Ecosystem is also your moat. He contrasted CUDA’s rise with Open Computing Language (OpenCL), noting that great ideas exist everywhere, but sustained company-wide commitment to building the surrounding infrastructure is rare. That’s what made CUDA the standard. 5. Ecosystem-first innovation is Nvidia’s playbook. Today, with platforms like Omniverse, Digital Twins, and Cuda-Q (quantum+classical computing), Jensen is highlighting it again: “In order for that [new platform] to take off, the ecosystem has to flourish… Developers, end-customers, use cases, it all has to be invented out of nothing.”