Microtek International

The anxiety of professional future amongst professionals, parents and students in the age of AI is well addressed through this powerful article by Ashish Dhawan and Pramath Sinha which highlights why this conversation matters deeply. AI may disrupt jobs, but it could also push people closer to what truly matters — their interests, strengths, values, and purpose. Like every major technology wave before it, change is inevitable. The real opportunity lies in adapting early, staying curious, and building uniquely human skills that AI cannot easily replace.

For those following AI this is a must read as it gives a clear perspective of the trans-national AI progress Vs India and the gaps Jensen Huang recently said AI has 5 layers of value. The uncomfortable truth: India has almost no meaningful presence in any of them. 1. Energy AI data centres need enormous power. One large AI campus can consume as much electricity as a small city. China added almost as much new power capacity last year as India’s entire installed grid. 2. Chips The world’s AI chips are controlled by others: • Nvidia, AMD, Broadcom → US • TSMC → Taiwan • HBM memory → Korea • ASML chip-making machines → Netherlands • Key materials → Japan India still does not have a cutting-edge chip factory. Most of our best chip talent works for global companies, so the value gets created elsewhere. 3. AI Infrastructure India can build data centre buildings. Companies like Yotta, Adani and Reliance are investing. But the real AI infrastructure is still owned by others: • AWS, Azure, Google Cloud → US • Alibaba, Tencent → China Almost every Indian AI startup still runs on foreign cloud platforms. 4. AI Models The most powerful AI models come from: • OpenAI, Google, Anthropic, Meta → US • DeepSeek, Qwen → China India has promising players like Sarvam and Krutrim, but they are still far behind the global leaders. 5. Applications The biggest AI applications are also mostly American or Chinese: • ChatGPT • Copilot • Cursor • Claude • Agentforce India has strong SaaS companies like Zoho and Freshworks, but most Indian AI products still depend on foreign models. The Layer 5 gap is what stands out to me - India has the engineering talent but no agentic platforms at scale. We design chips for Nvidia and build SaaS for the world, but always one layer above someone else's stack. That's where the margin pressure lives. The real problems is this: 30 years ago, India chose services over manufacturing. That created giants like TCS, Infosys, Wipro and HCL. It built a $250B export industry. But services sit on top of the stack. They do not own the stack. China has a presence in all 5 AI layers. Korea owns the memory. Taiwan owns the factories. The Netherlands owns the machines. India is still largely a customer. And unless we start investing seriously in power, chips, infrastructure and original AI products, that will not change. Thoughts?

I have been thinking a lot about what AI is really doing to us beyond the hype, the demos and the endless productivity promises. 𝗜 𝗿𝗲𝗰𝗲𝗻𝘁𝗹𝘆 𝗰𝗮𝗺𝗲 𝗮𝗰𝗿𝗼𝘀𝘀 𝗞𝘆𝗹𝗲 𝗞𝗶𝗻𝗴𝘀𝗯𝘂𝗿𝘆’𝘀, “𝗧𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗘𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 𝗶𝘀 𝗟𝗶𝗲𝘀.” 𝗜𝘁 𝗶𝘀 𝘂𝗻𝗰𝗼𝗺𝗳𝗼𝗿𝘁𝗮𝗯𝗹𝗲, 𝗯𝗹𝘂𝗻𝘁 𝗮𝗻𝗱 𝗽𝗿𝗼𝗯𝗮𝗯𝗹𝘆 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝘁𝗵𝗶𝗻𝗴𝘀 𝗮𝗻𝘆𝗼𝗻𝗲 𝘄𝗼𝗿𝗸𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗔𝗜 𝘀𝗵𝗼𝘂𝗹𝗱 𝗿𝗲𝗮𝗱. A few points stayed with me: • AI is still not intelligence. It is prediction at scale. The problem is that it sounds incredibly convincing even when it is completely wrong. • The danger is inconsistency. These systems can solve complex problems and then fail at something surprisingly simple. That makes blind trust extremely risky. • We are producing more code, more content and more automation than ever before. But are we creating better work? I am not sure. In many cases, we are creating more things that are harder to verify. • AI is already polluting the information ecosystem. Search is becoming noisier, spam is becoming smarter and it is getting harder to know what is real. • The biggest risk may not be job loss. It may be skill loss. The more we outsource thinking, writing and judgment to AI, the less capable we become ourselves. • Accountability is disappearing. When an AI system makes a bad decision, who is responsible? The company? The model? The data provider? Nobody seems to have a clear answer. • And finally, I think we are underestimating how fast the economic and social impact could arrive. I do not agree that we should stop building AI. I strongly believe AI will transform industries, including marketing, technology and consumer businesses. But I do believe we need to slow down long enough to ask a harder question: Just because we can automate something, should we? The most underrated risk, in my view, is not that AI becomes smarter than humans. It is that humans become too dependent on AI to think for themselves. What's the risk you think is most underrated right now?

AI leadership is not defined by adoption alone. It is defined by alignment between usage and belief. Most narratives focus on who is adopting AI fastest. The data shows a more important distinction. Winners are those where adoption and sentiment reinforce each other. As EY highlights, countries like India, China, KSA, and the UAE combine high adoption with strong positive sentiment. In contrast, many developed markets show lower sentiment despite growing usage. Alignment Advantage: Markets with both high adoption and positive sentiment create momentum. Users are more willing to experiment, trust, and expand AI usage across workflows. Sentiment Drag: In markets where adoption rises but sentiment lags, scaling slows. Skepticism introduces friction in deployment, governance, and user acceptance. Strategic Divide: The global AI race is not just about capability or infrastructure. It is about how populations perceive and accept AI-driven authority. What looks like uneven adoption is actually a divergence in trust and cultural readiness. The real challenge is not accelerating AI deployment. It is aligning adoption with belief to sustain long-term scale. via EY

Meta’s latest move from search to capturing intent feels like a turning point for the advertising industry. For years, Google owned digital intent. Now Meta is building a very different playbook powered by AI, creators and discovery. Three things stood out to me: • Meta is no longer waiting for people to search. It is using AI to predict intent before the consumer even knows what they want. • Instagram, Reels and WhatsApp are becoming powerful commerce and advertising engines, not just social platforms. • The future of advertising will be less about keywords and more about recommendation, personalization and discovery. As a marketer, I believe this is one of the biggest shifts our industry has seen in years. The race is no longer just about search. It is about who understands people first.

If you're heading to #adobesummit , don't miss this session with Mario Ciabarra and Jake Canaan -- especially if you are trying to move from data to action faster.

This is probably the clearest way I have seen AI explained. We keep debating whether AI is “smarter” than humans. I think that is the wrong question. Terence Tao, the smartest mathematician alive in his paper “Mathematical Methods and Human Thought in the Age of AI”recently described AI as being great at breadth, while humans are great at depth. Instead of buying into the common, one-dimensional narrative that artificial intelligence will simply evolve from "subhuman" to "superhuman" and ultimately make humanity entirely redundant, Tao urges us to look at the bigger picture. Much like the Copernican revolution proved the Earth is not the center of the universe, Tao suggests we need to realize that human intelligence isn't the only, or necessarily the highest, form of intellect. Historically, we have treated other forms of storing or creating knowledge—like animals, books, and computers—as secondary. However, we actually exist within a much richer universe of intelligence. Both human intelligence and computer intelligence possess their own distinct strengths and weaknesses. The true potential lies not in viewing them as direct competitors, but rather in focusing on collaboration. AI can scan, connect and process far more information than we ever can. But real insight, judgment and original thinking still come from people. The winning formula is not Human vs AI. It is Human + AI. The people who get this are 10 x more productive. The rest are still debating if AI is smart enough.