Just got back from AIBoomi in Chennai - with a lot of clarity.
Spoke to a bunch of tech leaders, besides the traditional midnight adda.
Same underlying tension: AI is moving fast. Most businesses are not. What's the strategy?
The session by Dr. Anand Deshpande added to my thinking about AI, and what we at Indus Net Technologies (INT.) can do about it in terms of overall strategy.
Sharing a few takeaways:
1) We are still early. Uncomfortably early.
What we're seeing today (largely LLMs) is just the first layer. The real shift will come from agentic systems and more advanced models that can reason, simulate, and act.
2) AI will not be equally accessible This is not like SaaS where everyone gets the same tools. AI depends on compute, energy, infrastructure, and geopolitics.
Access itself will become a competitive advantage.
3) Data sovereignty is going to reshape architectures
Countries will push for AI systems to run locally. Enterprises will follow. This means "just using global APIs" is not a long-term strategy.
4) Enterprise AI will fail without fixing data first
Most companies are underestimating this. Their data is fragmented, unstructured, and risky. AI on top of bad data just creates faster mistakes.
5) Agent-ready systems will become the new baseline
AI agents will interact with enterprise systems—but most systems today are not designed for that.
There's a real opportunity here in "agent management" and system redesign.
6) If you don't build your own intelligence layer, you don't have a moat
Depending only on foundational models is convenient—but fragile. The real defensibility will come from proprietary data + domain-specific intelligence.
7) Trust, liability, and audit will become board-level issues
AI errors won't just be technical problems—they will be legal and financial risks. Most companies are not prepared for this conversation yet.
8) Speed is the only real advantage smaller companies have
AI compresses execution cycles. If you're slow, hierarchy-heavy, or consensus-driven—you will lose to faster teams, not necessarily bigger ones.
9) The shift from "jobs" to "work" is real
AI increases productivity → reduces effort needed → changes how value is priced.
There may not be a shortage of work. But traditional "jobs" will definitely get redefined.
Few things to think about:
"How will AI change everything - in my industry and in other places?"
This is worth thinking. It underline threats and opportunities.
A more useful question might be: "What will not change in the next decade?"
Because those are your anchors.
- Customer expectations. - User experience. - The need for trust. - Change management. - Deep domain understanding.
If those don't change, then the real game is:
How do you use AI to strengthen these fundamentals—not distract from them?
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