Developing a Vision for Future Tech Innovations

🌍💡 The Future is Converging: Unlocking Value Through #Technology Synergies 🚀 The World Economic Forum’s Technology Convergence Report (June 2025), in collaboration with Capgemini, is a game-changer for understanding how today’s tech landscape is evolving. It’s not just about individual breakthroughs anymore—think #AI , quantum computing, or robotics—it’s about how these technologies combine to reshape industries, create new markets, and drive exponential impact. Let’s dive into the key insights and why this matters for leaders, innovators, and organizations worldwide! 🌐 🔑 The 3C Framework: A Roadmap for Innovation The report introduces the 3C Framework—Combination, Convergence, and Compounding—as a lens to navigate the complex interplay of technologies. Here’s how it works: Combination: Technologies like AI and quantum computing merge at the sub-component level (e.g., machine learning + quantum algorithms) to create novel solutions that tackle problems no single tech could solve. For example, quantum ML blends atomistic and molecular insights to revolutionize material design. Convergence: These combinations reshape value chains, enabling companies to enter new markets or create entirely new product categories. Think of Blue Ocean Robotics, which evolved from hardware manufacturing to offering AI- and spatial computing-powered collaborative solutions, boosting revenue and partnerships. This framework isn’t just theoretical—it’s a practical guide for organizations to identify high-value tech pairings, align them with core strengths, and seize strategic opportunities. 🌟 Eight Transformative Technology Domains The report highlights eight domains driving this convergence revolution: AI, Omni Computing, Engineering Biology, Spatial Intelligence, Robotics, Advanced Materials, Next-Gen Energy, and Quantum Technologies. Each is broken down into 238 sub-components, assessed by maturity (from experimental Genesis to scalable Commodity). The magic happens when technologies at different maturity stages combine—like pairing cutting-edge agentic AI with stable computer vision to power autonomous systems. Compounding: As adoption scales, network effects and economies of scale kick in, driving down costs and accelerating innovation. NVIDIA’s pivot from general-purpose GPUs to AI-specific frameworks like CUDA is a prime example—catapulting its market cap from $300B to $3T in just three years! 💡 Why This Matters for You Organizations must: Bridge Silos: Build cross-domain expertise to combine mature and emerging technologies. Seize Adjacent Opportunities: Identify where tech convergence creates new value chains, like robotics firms moving from hardware to service-based models. Balance Risk and Reward: Invest strategically in high-potential combinations while addressing ethical concerns, like those tackled by the WEF’s AI Governance Alliance or #Quantum Initiative.

A FUTURE TRIP Looking ahead to manufacturing a decade from now, I see a landscape transformed not just by individual technologies, but by their unprecedented convergence. Here's what I see: 1️⃣ The stark division between human and automated tasks will dissolve. Workers will use neural interfaces and augmented reality to control multiple semi-autonomous systems simultaneously. Biological computing elements will be integrated into production systems, with engineered microorganisms monitoring quality, processing waste, and even participating in assembly of certain components. 2️⃣ The manufacturing workforce will need capabilities in: - Multi-system orchestration rather than single-machine operation - Biological-digital interface management - Network optimization and exception handling - Materials programming and molecular manufacturing - Regulatory navigation across rapidly evolving frameworks 3️⃣ Successful companies will shift from product delivery to outcome delivery models. Manufacturing-as-a-Service will become dominant, with companies maintaining ownership of materials through multiple product lifecycles. Value will increasingly derive from the data generated during production and use rather than the physical product itself. Leaders preparing for this future should be investing now in development that bridges digital, biological, and physical domains. Decisions made today will determine organizational adaptability in this converged landscape.

The Product Market Fit Framework by Sequoia 👇 3 Archetypes of Product-Market Fit: 1. Hair on Fire 🔥 You solve a problem that’s a clear, urgent need for customers. The demand is obvious. Because of this, your category is likely crowded with competitors vying for market share. Your customers are actively wrestling with the problem, and likely comparing existing products to solve it. To succeed in such a dynamic, you must rise above the noise. The only way to do so is by delivering the best-in-class solution. And best-in-class products stand out because they are different, not merely better. You can’t just be faster or cheaper—you need a truly differentiated customer experience to have a durable advantage. 2. Hard Fact 💎 You take a pain point universally accepted as a hard fact of life, and see that it’s merely a hard problem that your product solves for the customer. Your customers have resigned themselves to just living with the problem. They’re not urgently engaged with trying to solve it. The status quo is just how it is, and change doesn’t seem like an option. You upend how things are done with an unexpected approach: Facts can’t be changed—but problems can be solved. The challenge to overcome is force of habit. Customers will have to change their current behaviors, and inertia is powerful. You need an approach that’s novel enough, for a problem that matters enough, to be worth making a change. 3. Future Vision 🎯 You enable a new reality through visionary innovation. It sounds like science fiction to customers, either because the concept is familiar but sounds impossible (like abundant cheap energy from nuclear fusion) or because no one ever imagined it (like the iPhone). Customers are not only not trying to solve the problem, they are either oblivious to it or predisposed to think it’s a pipe dream. Either way, the obstacle is disbelief: Customers must believe that your product represents a whole new paradigm—often with its own ecosystem. (The iPhone wasn’t just a device; its App Store was a new way of interfacing with the internet. Tesla isn’t just a car; it’s a network of cameras and self-driving software that’s a new driving experience.) Customers must find the paradigm and its possibilities irresistible. As discussed below, this path is often long, and finding the right route with the right commercial opportunities along the way is usually critical.

 🏫Future University 🏫 In responding to one of my recent posts, Julie (JR) Rowland challenged me to envision the future university. I replied with a vision of the future university as a dynamic, decentralised physical and digital ecosystem that integrates education, work, and community service into a continuous learning journey. This new university is designed to adapt to the rapidly changing global landscape, harnessing the power of technology to make learning accessible, personalised, and directly applicable to real-world challenges. Its purpose is to foster lifelong learning, innovation, and collaboration, preparing individuals not just for today's jobs but for the challenges and opportunities of the future. Its value proposition is its ability to integrate theoretical knowledge with practical application, thereby enhancing individual capabilities, addressing societal challenges, and driving economic and social progress. Let's imagine a day in the life of a student attending this university: Maria is a learner at Future University, a global network without a traditional campus. Her day begins in her local community hub, a co-working space with advanced technology, including AI tutors, surrounded by a vibrant community of learners, mentors, and professionals from surrounding companies. Maria's morning is spent working on a project with a technology startup, part of her apprenticeship program. She's developing a sustainable energy solution, applying skills learned in her interdisciplinary studies. Her AI tutor facilitates the project, which suggests resources and learning modules based on the challenges she encounters in real time. Lunch is an opportunity for a mentorship meeting at the community hub, where Maria discusses her project's progress with her mentor, a senior engineer with global experience. They use a blockchain-based platform to record milestones and feedback, contributing to her personalised learning record. In the afternoon, Maria heads to an open innovation lab, a collaborative space where students, faculty, and industry professionals work together on research projects. Today, they're analysing data from their sustainable energy project to predict energy consumption patterns. This research is part of a larger initiative shared with partnering organisations across the globe. Maria spends her evening participating in a global skill exchange webinar, where she shares her project experiences with a global audience and learns from others working on similar projects. This platform allows her to connect with peers, enhancing her global network and exposing her to diverse perspectives. Before bed, Maria reflects on her day's learning, using her digital portfolio to document her achievements, skills and areas for growth. This portfolio, secured on the blockchain, is a comprehensive record of her lifelong learning journey, accessible to potential employers and collaborators. #futureofeducation #Highereducation

A decade ago, I worked with designer Yves Béhar on a set of principles for design in the era of AI and robotics. Watching the situation unfold between the current administration, OpenAI and Anthropic, these tenets feel more relevant than ever. For those unfamiliar with Yves' work, he became known in the early 2000s for integrating tech into his industrial design practice. He was the co-founder of Jawbone and August Smart Lock, and designed popular products like the Frame TV for Samsung and Snoo for Happiest Baby. While I ran communications for his studio, fuseproject, we were already seeing the massive potential impact AI and robotics would have on our daily lives. However, we also saw technologists innovating without a clear vision for how these technologies would be applied, and the potential negative impacts this could have. Based on the work coming out of the studio, we laid out a manifesto for how these new technologies should be designed. We then did an international speaking tour to share these principles (see the full breakdown in the Fast Company article in the comments). The manifesto is as follows: The design of new technologies should 1) solves an important human problem 2) be context specific 3) enhance human ability without replacing the human. 4) consider everyone, of every ability, in everyday life 5) make the technology itself discreet 6) consist of platforms over products, that grow with needs and opportunities 7) build long-term relationships without creating dependency 8) ethically learn and predict human behavior 9) accelerate new ideas 10) remove complexity. A decade later, I am watching the world's most powerful technology snowball in real time: agents producing agents, our ability to discern fact from fiction diminishing, and the biggest names in tech offering to remove safeguards for faster adoption. I can't help but thinking, where is the discourse? And where is the vision? We are in an accelerationist era. As we sprint into the agentic future, I do wish we, as an industry, could at least align on our destination. It is hard to imagine our best possible future when such powerful tools are leveraged for weapons rather than uplifting humanity to its fullest potential. I'm working on some collective thought leadership to imagine a better future with technology -- follow this space to stay involved. 

Stop being the IT department’s repair shop—start leading strategic change. You’re more than just tech support—here’s how to prove it. Tech leaders, it's time to rewrite your role. You're not just the person who keeps the lights on - you're the visionary who illuminates new paths forward. Here's how to make that shift: 𝟭. 𝗔𝗹𝗶𝗴𝗻 𝗧𝗲𝗰𝗵 𝘄𝗶𝘁𝗵 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗚𝗼𝗮𝗹𝘀 Every project should answer: "How does this drive our strategy?" When you present, lead with outcomes, not gigabytes. Show how IT propels the company forward. 𝟮. 𝗕𝘂𝗶𝗹𝗱 𝗕𝗿𝗶𝗱𝗴𝗲𝘀 𝗔𝗰𝗿𝗼𝘀𝘀 𝗗𝗲𝗽𝗮𝗿𝘁𝗺𝗲𝗻𝘁𝘀 Be curious. Learn what keeps other leaders up at night. Then, offer solutions they haven't even dreamed of yet. Your value skyrockets when you solve problems beyond the server room. 𝟯. 𝗖𝗵𝗮𝗺𝗽𝗶𝗼𝗻 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 Don't wait for permission to innovate. Pilot new ideas that could transform the business. Be the catalyst for "what if" conversations that open new possibilities. 𝟰. 𝗠𝗲𝗮𝘀𝘂𝗿𝗲 𝗪𝗵𝗮𝘁 𝗠𝗮𝘁𝘁𝗲𝗿𝘀 Capture the impact of your work in terms the C-suite cares about. Revenue generated. Costs saved. Customer satisfaction improved. Let the numbers tell your story. 𝟱. 𝗖𝗹𝗮𝗶𝗺 𝗬𝗼𝘂𝗿 𝗦𝗲𝗮𝘁 𝗮𝘁 𝘁𝗵𝗲 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆 𝗧𝗮𝗯𝗹𝗲 Inject tech insights into high-level planning. Show how IT isn't just a support function - it's a cornerstone of future success. Your perspective is essential. 𝙏𝙝𝙚 𝙎𝙩𝙖𝙩𝙨 𝘿𝙤𝙣'𝙩 𝙇𝙞𝙚: - 32% of IT pros feel they lack leadership skills to advance. It's time to invest in yourself. (Global Knowledge) - 70% want leadership roles, but only 40% get needed development. Seek mentors and training. (Gartner) - IT leaders with business savvy are 2.5x more likely to reach the C-suite. Master the big picture. (Deloitte) The shift from "fix it" to "future it" won't happen overnight. But with persistence and vision, you'll transform not just your role, but your entire organization's relationship with technology. Pick one of these steps. Implement it this week. Share your results. Let's change the narrative together.

Every major tech revolution has reshaped not just the tools we use but the structures, norms, and expectations of society itself. From personal computing to smartphones, history shows that our predictions often miss the mark—not because we can’t imagine advanced technology, but because we fail to see how it will fundamentally alter our way of life. Consider the famous flying car example. In the 1950s, people envisioned a future of advanced tech while clinging to familiar norms. Flying cars were imagined with suburban houses, nuclear families, and 1950s social structures still intact. What they missed was that transformative tech doesn’t just enhance existing systems—it disrupts them. The same pattern repeated with personal computers, initially seen as glorified typewriters or niche tools. Instead, PCs democratized creativity and spawned entire industries. Early visions of the Internet were limited to digital storefronts and libraries; no one anticipated the blogosphere, social media, or the collapse of traditional gatekeepers in media and commerce. Smartphones? First dismissed as "tiny PCs," they became the foundation for new behaviors... ridesharing, dating apps, and a 24/7 social identity. Today, we stand at a similar juncture with AI and large language models (LLMs). Some see them as tools to make existing workflows faster or smarter, but history suggests a larger transformation is coming. AI could redefine what we think of as "applications" or "interfaces," moving us from static web pages to dynamic, conversational systems that blur the boundaries of platforms and experiences. The lesson from flying cars? The real challenge isn’t envisioning futuristic tools—it’s imagining how they’ll disrupt the stable components of our lives. With AI, we must ask not just what it can do, but how it will reshape our assumptions, norms, and interactions. The future isn’t just about better tools. It’s about a different world and SaaS in particular is not going to look or feel like it does today.

🚀 2026: My Vision for the Next Tech Leap After reviewing many of the major 2026 tech outlook reports, here is my vision for the year ahead, a year where technology finally grows up. 🇪🇺 Europe Steps Ahead With the EU AI Act in force, Europe is now the only region with a complete framework for trustworthy AI. As of today, this gives us a real advantage: clarity for businesses, protection for citizens, and a model of innovation built on trust. 🤖 AI Beyond LLMs 2026 won’t be about bigger models, it will be about the right models: ✅ LLMs for reasoning and creativity ✅ DSLMs for specialized sectors ✅ Small sovereign models for privacy & edge ✅ Multi-agent systems that collaborate ✅ Physical AI embedded in robotics and devices The era of “one-size-fits-all AI” is over. 🛡️ Security & Sovereignty Go Mainstream AI-powered attacks rise. Deepfakes scale. Europe responds with GDPR + DSA + DMA + the AI Act turning trust into a competitive advantage. ⚡ Quantum, Energy & Sustainability Accelerate AI’s energy demand forces rapid innovation: microgrids, hybrid infrastructures, sustainable architectures. Quantum moves closer to real applications. 👥 The Real Differentiator? Leadership. Technology alone won’t make the winners of 2026. Governance, ethics, culture, and human judgment will. After decades across major tech revolutions, I see 2026 as a true inflection point. The choices we make now will determine whether innovation becomes a force for shared progress or amplified risk. 2026 will reward courage, discipline, and a future built not just to be smarter… but wiser. Do you agree with my vision? Please let me know in the comments below 👇 #BigIdeas2026 #LinkedInNewsEurope

One of the biggest gaps I see (everywhere) is this: not enough vision. When I work with senior leadership teams to imagine the future of their company or market, we almost always hit the same roadblocks: – The ideas are not ambitious enough – The ideas are too ambitious – Or the ideas only fit into one of three “comfort zones”: 1️⃣ What’s achievable within my team/budget 2️⃣ What’s achievable only with cross-org consensus 3️⃣ What’s achievable only with an industry coalition It's no wonder only 5% of AI pilots succeed (per MIT). That’s why I built this vision-mapping framework 👇🏼 Here’s how to run it with your team: 1️⃣ Before showing the grid, have everyone write 3 future visions for your product/service/org/market. 2️⃣ Reveal the grid and explain the axes. 3️⃣ “Show & tell”: Each person explains their visions and places them on the grid. (Pro tip: the group must reach agreement before moving on.) 4️⃣ Step back, analyze, and see where your team needs more bold + achievable ideas—and how balanced you are across direct control, cross-org, and industry-wide visions. 🎯 The goal is to create a portfolio of bold and achievable visions: some within your control, some requiring collaboration across the organization, some with the potential to make markets or reshape the ecosystem. This is part 1 of a 3-part workshop we've run with hundreds of senior executives at The Future Solving Company—Follow along if you'd like more insights, tools, and learnings to help leaders create powerful visions of the future and then make them real.

🌐 Harnessing the Future: Navigating the 2024 Hype Cycle for Emerging Tech💡 As we explore the revelations from Gartner's 2024 Hype Cycle for Emerging Technologies, let's delve into some groundbreaking technologies shaping our approach to software development, AI, and cloud. Some technologies have particularly caught my attention as they are central to my discussions with my clients: 🧠 Unsurprisingly, Generative AI is swiftly advancing towards the Peak of Inflated Expectations. ☁️ Cloud Native, crucial for building and running scalable applications in environments such as public, private, and hybrid clouds, is nearing the Trough of Disillusionment. Its capabilities for resilient and flexible deployment make it a cornerstone in modern tech infrastructure. 👨💻 AI-Augmented Software Engineering and Internal Developer Portals are both designed to boost developer productivity through more intuitive interfaces and automated tools, significantly reducing developers' cognitive load. These technologies are eagerly pushing towards the Peak of Inflated Expectations. 🔄 GitOps employs git repositories to manage infrastructure and software configurations, promoting a version-controlled, collaborative, and declarative approach. This method is currently on its ascent towards the innovation trigger. 🤖 Autonomous Agents, capable of independent operation and decision-making, are poised near the Trough of Disillusionment. These agents are set to redefine AI interactions and autonomy within tech solutions. What experiences have you had with these technologies, and what potential do you see for their future application? 🔗 Source: Gartner, August 2024 https://lnkd.in/eB4JWvnd #EmergingTech2024 #GartnerHypeCycle #GenerativeAI #CloudNative #SoftwareEngineering #AI #TechTrends #InnovationInTech