Understanding Market Dynamics in Technology

The collision between AI-driven and traditional firms is reshaping entire industries. Here's what most people miss: it's not about technology adoption. It's about fundamentally different operating models competing head-to-head. Traditional firms are built on constraints: → Limited scale (more output = more people) → Narrow scope (stay in your lane) → Slow learning (experience takes time) AI-driven firms break these rules: → Massive scale with minimal resources → Cross-industry scope (Airbnb disrupts hotels without owning rooms) → Continuous learning from every interaction When these two models collide, the market dynamics shift dramatically. We're not just seeing disruption—we're watching the structure of our economy transform. The most successful organizations aren't asking "How do we add AI?" They're asking "How do we become an AI-first organization?" That's the difference between incremental improvement and exponential growth. Are you building for the old rules or the new game? #DigitalTransformation #AIStrategy #FutureOfBusiness

𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗮𝘀 𝗮 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗗𝗿𝗶𝘃𝗲𝗿: 𝗪𝗵𝘆 𝗠𝗼𝘀𝘁 𝗕𝗼𝗮𝗿𝗱𝘀 𝗰𝗼𝗻𝘁𝗶𝗻𝘂𝗲 𝘁𝗼 𝗚𝗲𝘁 𝗧𝗵𝗶𝘀 𝗪𝗿𝗼𝗻𝗴 After twenty years transforming technology organizations, I still walk into C-suite meetings where the conversation begins with: "What's the minimum we need to spend on technology to stay compliant and limit a breach?" This question reveals everything. It frames technology as an expense rather than an investment. It positions strategic capability as operational overhead. It treats innovation as a burden rather than a competitive advantage. The organizations that thrive ask different questions:  1. "How does this technology investment drive market advantage?"  2. "What business outcomes become possible with this capability?" This mindset shift transformed our Cyber Protection and Identity practice from $30M to $90M revenue. We stopped selling protection from threats and started enabling business growth. Results: 40% year-over-year growth and 95% client retention. The recent Palo Alto-CyberArk acquisition signals where the market is heading. Identity has evolved beyond cybersecurity into business infrastructure. With AI agents requiring system access and hybrid environments spanning multiple providers, traditional perimeter models cannot accommodate current reality. After implementing solutions for Fortune 500 clients across three continents, I've seen which organizations build sustainable advantages: those that understand technology as competitive differentiator, not a compliance checkbox. As an advisor to identity security companies, I've observed how organizations struggle with what we call 'identity dark matter' - the unseen parts of the access landscape that present real risk but remain unmanaged. Here's what distinguishes technology leaders from technology followers:   • 𝗘𝘃𝗲𝗿𝘆 𝘁𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗶𝗻𝘃𝗲𝘀𝘁𝗺𝗲𝗻𝘁 𝗰𝗼𝗻𝗻𝗲𝗰𝘁𝘀 𝗱𝗶𝗿𝗲𝗰𝘁𝗹𝘆 𝘁𝗼 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗼𝘂𝘁𝗰𝗼𝗺𝗲𝘀. No clear line to revenue or competitive positioning? Question the investment.  • 𝗥𝗶𝘀𝗸 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗲𝗻𝗮𝗯𝗹𝗲𝘀 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝗿𝗮𝘁𝗵𝗲𝗿 𝘁𝗵𝗮𝗻 𝗽𝗿𝗲𝘃𝗲𝗻𝘁𝗶𝗻𝗴 𝗶𝘁. The most secure organizations build resilience that allows bold strategic moves.  • 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗲𝘅𝗰𝗲𝗹𝗹𝗲𝗻𝗰𝗲 𝗰𝗿𝗲𝗮𝘁𝗲𝘀 𝘁𝗵𝗲 𝗳𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗳𝗼𝗿 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗮𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲. You cannot build transformational capabilities on unstable operations. The executive choice is clear: Will technology happen TO your organization, or will your organization leverage technology FOR competitive advantage? The companies answering this correctly won't just survive technological change. They'll define market leadership. What's been your experience positioning technology as a strategic driver rather than an operational requirement?

I am in NYC, where I serve as an Adjunct Professor of Law at Cornell Tech, teaching an intensive course entitled Law 6337: Law & Technology & Economics of AI. My students are exceptional. They are pursuing JD, LLM, MBA, or CS degrees. What a privilege! Here is the syllabus introduction: “Law & Technology & Economics of AI” explores AI markets as complex adaptive systems where law, technology, and economics co-evolve. Combining insights from “law & technology” and “law & economics,” the course equips students to navigate and shape this evolving ecosystem through integrated reasoning across the three domains. The course builds on three mutually reinforcing pillars. First, technology: we explore the technical architecture of AI systems, how they are built, trained, and deployed at scale. Second, economics: we study the market dynamics these technologies generate, the competitive strategies they enable, and crucially, how economic incentives feedback to shape technological trajectories. Third, law: we analyze how regulators respond to these novel market structures, and how legal interventions, in turn, redirect both business strategies and technical development paths. This is not a linear story. Each pillar continuously reshapes the others. Business models dictate which technologies get funded and developed. Regulatory frameworks influence which business models remain viable. Technical capabilities open new regulatory challenges while constraining possible solutions. The course treats AI markets as a complex adaptive system where technology, economics, and law co-evolve through constant feedback loops, a reality that demands integrated thinking rather than siloed analysis.

One of the hardest things to achieve in business and life is to see opportunities well in advance of others — and act to seize them. This is especially difficult in high-tech industries driving transformative trends.     It requires subtlety, patience, and operating along an arc that affords strategic alternatives. Having a willingness to stay the course, even when the path forward is not immediately clear can make all the difference when the fog finally lifts.     Two enduring lessons have shaped my approach to strategy over four decades. 1) The first is from Sun Tzu, who said “if you know the enemy and know yourself, you need not fear the result of a hundred battles.”       When I think about this simple advice, I like to apply it to an understanding of the market dynamics and trends. It naturally spills over to the value proposition, core competencies and sources of sustainable competitive advantages that are required to stay in the game and the stamina to ultimately win.  For businesses, this translates to deeply understanding your market, customers, competitors, and your own organization’s capabilities and how to manage it to create resiliency and flywheel effects. This insight has been shown to drive sustainable competitive advantages, mitigate risks, and anticipate the benefits of even subtle market moves.    2) The second is around strategic ambiguity and the patient accumulation of advantage.    I have learned that success requires seeing opportunities before others and staying with them longer than others and remaining flexible. This can happen by acquiring or creating technological disruptions and introducing products that enable customers to win.      Either way, as the disruptions progress, building a market leader as markets rapidly change is like navigating the board of the ancient Chinese game of Go, a metaphor for the market. Go is known for its simplicity in rules but extraordinary depths required around strategy.     There are countless examples across industries when some understandably questioned one bold move or another. Indeed, it can be difficult to anticipate and understand the incredible strategic value that can emerge.     This is in part because it is normal to focus on the past, and the present and that can get in the way of seeing the opportunity that lied ahead. I believe that there are countless lessons from the Go Board of countless businesses, about strategic moves that end up making a huge difference, even if they were viewed as contrarian at the time.     I believe that we will continue to see more of that in deep tech-especially in those markets undergoing massive transformations. Long-term thinking, combined with the patient accumulation of differentiated advantages often reveals its true value only in hindsight.   Such disruptions, however subtle, will eventually be obvious, even to a casual observer. So, think slowly, but act quickly. 

I was delighted to continue our "An Evening with" series, where we recently welcomed renowned tech analyst Benedict Evans for an exclusive fireside chat. This marks Benedict's third speaking engagement in Singapore, and we're honored to have hosted him as part of our distinguished speaker series. His insights on technology trends and market dynamics provided invaluable perspectives for the INSEAD community. Here are some of the highlights of our discussion: 1. The Moving Target of Intelligence: "'Intelligence is whatever machines haven't done yet.' When it works, we stop calling it AI. Ten years ago, machine learning was AI. Now image recognition is 'just software.'" 2. The Excel Effect "Young people won't believe this, but before Excel, junior investment bankers used to work really long hours. Now with AI, we won't work less - we'll do massively more analysis." 3. The Apollo Program Paradox "Today's AI development is like building the Apollo program without understanding gravity or rocket mechanics. We know bigger models work better, but we don't know why. We're scaling empirically without a theoretical foundation." 4. The False Competition Question "Market definition is everything. Coca-Cola will say they compete with water. Ferrari's critics will say they monopolize 'Italian sports cars with horse logos.' Both are kind of true." 5. The Infrastructure Evolution "My father had to install his own turn signals in the 1950s. Today, built-in turn signals are technically 'anti-competitive' - they killed the after-market. But that's progress, not monopoly." 6. Market Power Reality Check "Amazon has ~8-9% of US retail. Calling it a monopoly is weird - they invented their business model and dominate that, but retail remains hugely competitive." 7. The Filter Bubble Trap "Every discovery path eventually fills with noise, forcing you to find new paths. This isn't the internet getting worse - it's the natural evolution of information channels." 8. The Regulation Timing Problem "Tech evolves faster than regulation. By the time you've gone through due process, you're regulating problems from five years ago in an industry completely different now." 9. Semiconductor Economics: "With each chip generation, costs went up massively, and participants went down dramatically - from dozens to essentially one (TSMC)." 10. Innovation Integration "Today, if you bought a phone without a web browser, you'd think it was broken. Yet in the '90s, bundling browsers was seen as anti-competitive." Thank you, Nancy, Alexander, and Endora, for co-hosting this event with Black Mangroves.

The Hidden Factors Behind Our Technical Choices Technology is everywhere, shaping how we communicate, work, and interact with the world. But how often do we truly understand the technical aspects of the choices we make? A simple but telling example comes from a casual conversation: One person asked another, “Do you prefer iOS or Android?” The response was immediate: “iOS.” Curious, the first person followed up: “Why?” The answer? “Because iPhones have nice cases.” At first, this might seem like a trivial or humorous answer. But in reality, it reflects a broader truth: many people might make technology decisions based on non-technical factors—and this extends well beyond personal device choices. Technology Decisions in the Workplace In the corporate world, technology decisions may not always be based solely on technical capability. Many organizations may stick with familiar tools simply because they have always used them, even if better alternatives exist. Sometimes, decisions may be influenced by peer pressure—if a competitor or industry leader adopts a particular tool, others may follow suit without critically evaluating whether it’s the right fit. User experience may also play a significant role. A platform may not be the most powerful, but if it has a cleaner interface or appears easier to use, it can become the preferred choice. Additionally, there may be a natural resistance to change. Even when switching technologies could bring long-term benefits, the perceived risk and effort required to transition may prevent organizations from making the leap. Bridging the Gap Between Perception and Reality For engineers, product managers, and decision-makers, understanding these dynamics is crucial. The best product doesn’t always win purely on technical merit. User perception, ease of use, and overall experience matter just as much—if not more. How Can We Make Better Decisions? Educating stakeholders is important, but it’s also essential to keep explanations simple and focused on impact rather than overwhelming people with technical details. Recognizing that choices are often driven by emotion, habit, and convenience can help in designing products that resonate with users. A great product not only needs to function well but should also feel intuitive and easy to adopt. Encouraging deeper discussions around technology choices can also lead to better decision-making, helping organizations move beyond surface-level preferences to identify the right solutions for their needs. #Technology #DecisionMaking #ProductManagement #UX #TechLeadership

When we value a business, we aren’t valuing it in isolation; we’re valuing it in context. The industry sector, sub-sector, and business model give that context. They define how the company creates value, where it competes, and what drives its financial performance. 1. Industry Sector ,,Defines the macro context The industry sector (e.g., technology, manufacturing, retail, healthcare) tells us: ⦿The economic cycle sensitivity (cyclical vs. defensive). ⦿The growth potential of the overall market. ⦿The typical risk profile — e.g., volatility, capital intensity, regulatory exposure. ⦿The valuation benchmarks — certain sectors have established multiples (e.g., Tech uses EV/Sales or EV/EBITDA; Banks use P/B). Example: A 20% EBITDA margin in software is average. In retail, it’s exceptional. The same number means different things depending on sector context. 2. Industry Sub-Sector ☞Narrows down competitive dynamics Within each sector, sub-sectors define specific value drivers and business risks. For example, within “Technology,” we might compare: ◼︎SaaS (recurring revenue, high margin, scalable) ◼︎Hardware (capital heavy, low margin) ◼︎IT services (labor intensive, moderate margin) Each sub-sector has different: ◼︎Revenue models (recurring vs. transactional) ◼︎Cost structures (fixed vs. variable) ◼︎Competitive intensity ◼︎Typical valuation multiples Example: A SaaS company might trade at 8–10x revenue, while a hardware company in the same sector trades at 1–2x. The sub-sector explains why. 3. Business Model — Connects strategy to value creation The business model is how the company turns inputs into profits. It determines: ◼︎Revenue stability (subscription vs. one-time sales) ◼︎Scalability (how profit grows relative to cost) ◼︎Capital requirements (asset-light vs. asset-heavy) ◼︎Cash flow profile (how quickly it converts revenue to cash) This directly affects valuation because investors pay for: ◼︎Predictable, scalable cash flows. ◼︎Efficient capital use. ◼︎Sustainable competitive advantage. Example: Two companies in the same sub-sector — both in food delivery — might have very different valuations if one owns logistics (asset-heavy, low margin) and the other acts as a platform (asset-light, high scalability). 4. Integration in Valuation Models When performing valuation — whether DCF, Comps, or Precedent Transactions — these elements define: ◼︎Discount rate / risk premium (sector risk, cyclicality) ◼︎Growth rate assumptions (industry potential) ◼︎Comparable company universe (sector + sub-sector peers) ◼︎Multiples benchmark (EV/EBITDA, P/E, etc.) ◼︎Terminal value assumptions (based on business model sustainability) Valuation isn’t just about financials,it’s about contextualizing those numbers within their economic reality. The sector tells you where the company plays. The sub-sector shows how it competes. The business model explains why its financial structure deserves its valuation multiple. Nada Nasri, MBA, CMA®

AI’s Real Bottleneck Is Becoming Harder to Ignore At first glance, the AI ecosystem looks vast and competitive. The chart suggests something more concentrated. What stands out is not how many companies are involved, but how capital, compute, and dependency keep circling back to a very small number of players. Nvidia and OpenAI sit close to the centre of that loop, with cloud providers, hardware suppliers, and AI platforms increasingly tied together through spending, investment, and long-term commitments. History offers a useful constraint here. Early in major technology cycles, capital spreads widely in search of optionality. As those cycles mature, the economics tend to narrow. Scarce inputs, infrastructure control, and scale start to matter more than narratives. We have seen this pattern before. Railroads. Telecoms. Cloud computing. The story always feels expansive, but the economics quietly concentrate. The chart makes that shift easier to see. Capital raised by AI platforms flows quickly toward compute. Cloud providers recycle spending back into hardware leaders. Strategic investments blur the lines between customer, supplier, and owner. On the surface, the ecosystem looks diversified. Beneath it, correlations rise and dependency increases. For investors, this is less about chasing every AI-adjacent idea and more about understanding where leverage actually sits. Positioning that assumes equal participation across the AI value chain risks missing how asymmetric outcomes tend to become. Volatility in secondary names is not random noise. It reflects growing reliance on a narrow set of capital-intensive choke points. In a more fragmented world, where geopolitics, energy constraints, and capital intensity increasingly shape returns, concentration of control tends to assert itself earlier than consensus expects. Looking ahead, the discipline here isn’t about prediction. It’s about paying attention. Watching where capital keeps flowing, where flexibility quietly turns into dependence, and where prices start to reflect control rather than potential has mattered in every major technology transition. It’s beginning to matter again. In my free weekly market commentary, I focus on the issues discussed in this post, along with the economic and geopolitical factors shaping today’s investment environment. In the Global Investment Letter, that same framework is applied directly to major global markets and asset classes, including my own positioning, risk management, and areas where trend changes may be developing. You can receive the weekly commentary and review sample issues here: https://lnkd.in/g2mBz8fJ #markets #investing #artificialintelligence

Wrong Timing, Right Product Even the most refreshing product can feel out of place at the wrong time.  Imagine you’ve developed an innovative solution on the cutting edge of technology, which you believe serves a need by providing a solution to a potentially big problem. What could possibly go wrong? For one, the market might not be ready and still in its infantile stage. This can manifest itself in one or more ways: 1. Market Readiness The infrastructure, technology adoption, or regulatory environment may need to be more mature to support your product. For example, while it might seem like introducing electric cars into a developing market would be a great idea, but simply the lack of charging stations and road networks would make it a difficult product to successfully bring to market and scale. 2. Consumer Awareness Sometimes, consumers may not yet recognize the need for your product. It takes time to build awareness and educate the market.  For instance, when smartphones first appeared, many people didn't see the need for internet access on their phones until they experienced the benefits firsthand. 3. Economic Climate Launching a premium product during an economic downturn can negatively impact its success, regardless of its potential benefits. An example is luxury goods launched during a recession; even if the product is exceptional, the majority of consumers will typically  cut back on non-essential spending. Conclusion In the end, timing is crucial in innovation. Even groundbreaking products can falter if market conditions aren't conducive. Entrepreneurs must focus on superior solutions and consider the broader market environment. Understanding market readiness, consumer awareness, and economic climate can distinguish a thriving product from one that fades. Thus, thorough market research, strategic planning, and patience are essential to ensure a product meets the market at the right time.

Markets are always evolving, and technology never stands still. When we launched BCJobs, our biggest competitor wasn’t LinkedIn, Indeed, or other niche job boards. It was the newspaper. Recruiters didn’t believe the masses would embrace online hiring. “Only geeky people use the internet,” they said. But change came fast. When Google AdWords arrived, we could spend quarters to make thousands of dollars. It was an incredible arbitrage opportunity. But like all good things, it didn’t last. As the cost to acquire customers on AdWords rose, we didn’t double down on diminishing returns—we kept what worked and pivoted. We asked ourselves, “Where is the ball going next?” The answer was mobile and social. We noticed companies searching for Facebook recruitment tools, but the options were slim. So, we built a LinkedIn-style recruiting app for Facebook, optimized for recruitment searches in their directory. The result? 40,000 installs in 18 months—without spending a dollar on ads. Fast-forward to today: the tools that worked then won’t work now. Markets adapt, audiences shift, and strategies expire. So, where’s the next opportunity? Ahem, AI. Yes, everyone’s talking about it, but the companies that figure out how to apply AI in unique, untapped ways will create the next outsized returns. Consider the ever-changing dynamics in play today: The rise of no-code and low-code tools empowering non-technical creators. Web3 and the decentralized internet reshaping how we think about ownership. Shifts in consumer behavior, like the demand for sustainable, transparent brands. Emerging markets adopting mobile-first technologies at breakneck speeds. When you combine a deep understanding of market dynamics with the ability to leverage them in fresh, innovative ways—that’s where the magic happens. So, where do you see the ball moving next? #AI #MarketTrends #TechInnovation