AI IS REWRITING THE VENTURE CAPITAL PLAYBOOK AS INVESTORS RETURN TO HIGH-RISK DEEP-TECH BETS

Artificial intelligence is beginning to change not only the technology industry but also the way venture capital investors decide where to put their money, with global funds increasingly moving beyond traditional software and SaaS companies toward high-risk, capital-intensive deep-tech businesses. The shift represents a significant change in the startup investment model that dominated much of the past decade, when venture capital investors generally preferred software businesses capable of scaling rapidly without requiring enormous physical infrastructure. The rise of AI has challenged that model because the largest opportunities increasingly involve technologies that require laboratories, advanced hardware, specialised energy systems, computing infrastructure and years of research before reaching commercial scale. According to recent industry analysis, more than $150 billion has been invested in deep-tech companies outside the AI sector since 2024, exceeding the amount invested across the entire previous decade. Areas attracting increasing attention include nuclear fusion, space technology, advanced robotics, energy systems, brain-computer interfaces and other frontier technologies. AI itself is helping accelerate this transformation because machine-learning systems can reduce the cost and time required for research, simulation and experimentation. Technologies that previously required extensive physical testing can increasingly be modelled digitally before prototypes are built, allowing startups to explore complex engineering problems more quickly. This is creating a new category of venture opportunity sometimes described as “moonshot” investing, where investors accept a much longer path to profitability in exchange for the possibility of building companies with extremely large long-term markets. The success of companies such as SpaceX has also demonstrated the potential returns from backing businesses that initially appeared too capital-intensive or technically difficult for conventional venture investing. At the same time, the risks are considerably higher. A software startup can often launch a product within months and test market demand relatively quickly, while a deep-tech company may spend years developing technology before generating meaningful revenue. Scientific uncertainty, manufacturing complexity, regulatory approvals and enormous capital requirements can all create obstacles. Investors therefore face a very different risk-return equation. The transformation is particularly relevant to India, where the startup ecosystem has historically been dominated by consumer internet, fintech, SaaS and digital platforms but is now seeing growing interest in semiconductors, space technology, defence technology, advanced manufacturing, clean energy and industrial AI. India’s large engineering talent base and expanding digital infrastructure could provide an important foundation for these sectors. However, the country will need significantly greater access to long-term capital, research infrastructure and industry partnerships if Indian deep-tech startups are to compete globally. The AI revolution could actually make that transition easier because AI-powered design, simulation and automation can lower some of the traditional costs associated with scientific and engineering development. The changing venture-capital environment also creates an important warning for founders. Investors are becoming less interested in businesses that simply add an AI feature to an existing software product and increasingly want defensible technology, proprietary data, specialised infrastructure or a clear technological advantage. This could result in a more mature startup ecosystem in which companies are judged not only by user growth but by the strength of their intellectual property, engineering capabilities and long-term competitive position. For established Indian businesses, the trend could also open opportunities for strategic investment and partnerships with startups working on industrial automation, energy efficiency, robotics, manufacturing intelligence and supply-chain technology. Odisha could potentially benefit from this transition because its industrial base in metals, mining, manufacturing and energy provides real-world environments where deep-tech solutions can be deployed at scale. The larger message from the latest venture-capital shift is that the next generation of billion-dollar companies may not look like the internet startups of the previous decade. They could be companies building physical infrastructure, energy systems, advanced machines, space technologies or scientific platforms. AI is acting as the catalyst, but the investment story is increasingly becoming much broader than AI software itself. For venture capital, the age of relatively predictable software scaling may be giving way to a new era where investors are once again willing to finance difficult scientific and engineering problems in pursuit of much larger technological breakthroughs.