Simon Ninan

What if the next pivotal arena of power isn’t defined by borders or armies, but by the circuitry, code, and cloud behind every device we hold? Chris Miller and Vishnu Venugopalan show that despite Apple’s highly visible shift toward India and Southeast Asia, its supply chain remains deeply rooted in China, particularly in areas such as semiconductors, displays and precision machining, largely through foreign-owned operations. Their detailed mapping of factory counts and ownership structures reveals a deeper truth: where something is made matters less than who controls the intellectual property, the process expertise and ultimately the margins. Final assembly may relocate, but control remains concentrated. Behind that architecture lies a broader geopolitical and economic reality. In today’s world, influence travels through both components and code. Power belongs to the countries that command chip design, firmware pipelines, and cloud infrastructure. Without clear visibility into how value and authority are allocated, both financially and strategically, we see only the surface. Efforts to centralize advanced production inside a single state face structural limits, because no nation alone holds the entire ecosystem of inputs, specialized suppliers, and technological capabilities accumulated over decades. Attempting to rebuild those foundations risks eroding profitability and slowing the very innovation firms depend on. True strategic autonomy demands more than relocating factories. It requires coordination across industrial capacity, digital infrastructure, and sovereign control over data, standards, and critical technologies. Apple’s supply chain is more than a logistics model, it is a prism through which to view 21st-century power. And this goes far beyond Apple. Big Tech firms have become geopolitical actors, shaping global norms, influencing standards, and even shifting the balance of influence between emerging and established powers. The defining question is no longer “Where is the product made?” but “Who governs its lifecycle, its code, its data, its standards?” Those who master that spectrum won’t just compete. They’ll define the era ahead. #geopolitics #digitaleconomy #supplychains #digitalsovereignty #strategicautonomy #valuecapture #bigtech #nationalsecurity #globalinfluence American Enterprise Institute Chris Miller Vishnu Venugopalan https://lnkd.in/dDsXZn4n

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Every Sunday, I recap the biggest themes in AI, tech, and markets. This week, India's AI land grab intensified, regulators drew the line, attention wore a jersey, OpenAI joined the chip war. ▪️India is the world’s most strategic AI frontier - and the labs are bundling, billing, and localizing fast to become its default. ▪️The DOJ didn’t break up Google, but it broke its grip on defaults - a scalpel, not a sledgehammer, in the platform power playbook. ▪️Fantasy football is back - not just to crown champions, but to monetize ritual, identity, and belonging one Sunday at a time. ▪️OpenAI is building chips and Google is exporting TPUs. NVIDIA is still king, but surrounded by revolutionaries building guillotines in their garage. 📩 Full post here: https://lnkd.in/g7K6p4f7

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𝐈𝐬 𝐲𝐨𝐮𝐫 𝐜𝐨𝐦𝐩𝐚𝐧𝐲'𝐬 𝐦𝐮𝐥𝐭𝐢-𝐦𝐢𝐥𝐥𝐢𝐨𝐧 𝐝𝐨𝐥𝐥𝐚𝐫 𝐀𝐈 𝐢𝐧𝐢𝐭𝐢𝐚𝐭𝐢𝐯𝐞 𝐛𝐞𝐢𝐧𝐠 𝐨𝐮𝐭𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐞𝐝 𝐛𝐲 𝐚 $20/𝐦𝐨𝐧𝐭𝐡 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐬𝐮𝐛𝐬𝐜𝐫𝐢𝐩𝐭𝐢𝐨𝐧? A new MIT NANDA report suggests the answer is a hard yes. While 80% of organizations have piloted GenAI, a staggering 95% get zero ROI from their investments. Even worse, only 5% of custom enterprise AI tools ever make it to production. This is the "𝗚𝗲𝗻𝗔𝗜 𝗗𝗶𝘃𝗶𝗱𝗲": a chasm between high adoption and low transformation. The report is clear: the bottleneck isn't the technology, it's the strategy. We're confusing activity with progress, and it's stalling real transformation. The 5% of firms successfully crossing this divide are executing a fundamentally different playbook. Here are their three strategic shifts: 1️⃣  𝐅𝐫𝐨𝐦 𝐓𝐞𝐜𝐡 𝐏𝐫𝐨𝐜𝐮𝐫𝐞𝐦𝐞𝐧𝐭 ➔ 𝐂𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠: The impulse to build a proprietary tool is tempting, but the data is brutal: internal builds fail twice as often as partnerships. Successful deployments from strategic partnerships hit a 66% success rate, while in-house efforts languish at 33%. Winning firms treat AI not as a one-off purchase, but as a co-developed capability, focusing their internal resources on integration, not reinvention. 2️⃣ 𝐅𝐫𝐨𝐦 𝐓𝐨𝐩-𝐃𝐨𝐰𝐧 𝐌𝐚𝐧𝐝𝐚𝐭𝐞𝐬 ➔ 𝐅𝐫𝐨𝐧𝐭-𝐋𝐢𝐧𝐞 𝐄𝐧𝐚𝐛𝐥𝐞𝐦𝐞𝐧𝐭: Central innovation labs don't have all the answers. The most successful AI initiatives are sourced from frontline managers who understand the workflows intimately. They're also discovering the highest ROI isn't in flashy sales tools but in quiet back-office automation, slashing BPO spend by $2-10M annually and cutting external agency fees by 30%. 3️⃣ 𝐅𝐫𝐨𝐦 𝐒𝐭𝐚𝐭𝐢𝐜 𝐓𝐨𝐨𝐥𝐬 ➔ 𝐃𝐲𝐧𝐚𝐦𝐢𝐜 𝐀𝐬𝐬𝐞𝐭𝐬: This is the core issue. Most AI pilots stall because the tools are static. Users complain they "don't learn from our feedback" and "can't be customized to our specific workflows". Leaders, however, demand systems that adapt. They view their AI not as a depreciating software license, but as an appreciating asset. As it learns from proprietary data and processes, it becomes a true VRIN resource: valuable, rare, and inimitable: creating a durable competitive moat. The window to build this moat is closing fast. The report's consensus from IT leaders is that key vendor relationships will be locked in over the next 18 months. Soon, the advantage won't come from having an AI, but from the compounding value of a learning system deeply integrated into your core operations. The real prize on the horizon is the "𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗪𝗲𝗯": where these systems autonomously coordinate and create value. The critical question for leaders is no longer "Should we adopt AI?" It is "Are we building a static tool or a learning asset?" 𝐒𝐨𝐮𝐫𝐜𝐞 𝐥𝐢𝐧𝐤: https://shorturl.at/rA2DI #AIStrategy #GenAI #DigitalTransformation #BusinessStrategy #Leadership #Innovation #ROI

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