Author: Arun Sharma
More startups die from poorly executed scaling than from failed initial products. The transition from product-market fit to durable operating business is where most fail — and the failure patterns are predictable.
India has produced 110 unicorns. The country has the world’s third-largest startup ecosystem. But the gap between potential and actual share of global venture outcomes remains wide. What’s working, what’s broken, and what comes next.
From the EU AI Act to China’s generative AI rules to state-level US action, AI regulation is becoming a fragmented but consequential reality. Here’s what business leaders need to navigate it.
Every VC is now an AI fund. Every pitch deck references AI. The contrarian founder — building seriously in categories the market is ignoring — has structural advantages that the current hype cycle obscures.
Seed-stage valuations have risen sharply, AI is crowding out everything else, and warm introductions still dominate deal flow. First-time founders without established networks face a structurally harder fundraising environment.
OpenAI raised $40 billion at a $300 billion valuation. Sovereign wealth funds are writing cheques that traditional VC cannot match. For the next generation of founders, the implications are not straightforward.
Gartner projects that more than 40 per cent of agentic AI enterprise deployments will be cancelled by the end of 2027 — not because the technology does not work, but because the organisations deploying it are not ready. The gap between deployment speed and governance maturity is becoming the defining risk of the AI era.
A new class of entrepreneur is hitting seven-figure revenue without a single employee, a venture capital term sheet, or a traditional business plan. The solopreneur economy is real, it is growing, and it is rewriting the rules of what a business can look like.
The race for AI talent has become the defining hiring challenge of the decade — and it is no longer confined to Silicon Valley. From Mumbai to Manchester, every serious company is now competing for the same scarce pool of machine learning engineers, AI product managers, and data scientists who can actually build what the boardroom is promising.
The VC funding climate has fundamentally changed. Before you pitch your next round — or decide not to — here’s the data-driven framework for choosing the right funding path for your startup in 2026.