Market expert Ajay Bagga suggests a cautious approach to the market until July, citing upcoming tariff agreements as a potential sentiment shifter. Simultaneously, he highlights the burgeoning potential for Indian firms in Artificial Intelligence (AI), though he anticipates a couple of years before AI companies significantly impact the Indian landscape. The growth of AI is intrinsically linked to the development of data centers, while global economic uncertainties, particularly in China and the US, may influence IT spending.

Bagga emphasizes that "all bets are off till July," with July 9th being a critical date for tariff agreements that could positively influence market sentiment. While the short-term outlook (next 40-45 days) requires a "wait and watch" approach, the 12-month view for the Indian market remains strong. Key global concerns impacting risk sentiment include potential trade wars and the US fiscal deficit. These factors dictate capital flows, which tend to move towards the US when tariff risks diminish, and otherwise towards Europe, Japan, and select emerging markets. India, despite its strong domestic fundamentals and stable earnings outlook, is affected by this global overhang. Consequently, domestically-oriented sectors are currently favored, though a clearer understanding of US policies could see global sectors regain traction.

Regarding the AI transition, Bagga notes that while Indian companies have a history of successfully adopting new technologies, they often do so at a later stage. AI adoption is currently "catching up," with the launch of agentic software, where Microsoft is taking a leading role by deploying its software across multiple cloud platforms. Indian companies are expected to capitalize on these developments. However, economic slowdowns in China and the US pose challenges, potentially leading to cuts in marketing and software development—sectors where Indian IT firms are active. For AI to gain significant traction, it must drive substantial productivity improvements or cost reductions, for instance, by replacing human tasks with AI agents. Currently, AI agents' comprehension and solution-providing capabilities are still limited.

Bagga draws a parallel between the current AI wave and the IT boom of the last three decades. That earlier transformation, significantly enabled by Indian IT companies, involved moving services like banking online, drastically reducing operational costs for businesses as customers began to self-serve. AI, in comparison, is "just starting." Presently, companies involved in the foundational aspects of AI, such as chip manufacturers like Nvidia (the "picks and shovel" companies), are performing well.

Beyond chip makers, the next layer of opportunity in the AI ecosystem lies with entities that establish and power data centers. These power suppliers are expected to thrive. The third tier involves companies developing end-use AI applications, but their success hinges on end-user readiness and funding, which is not yet widespread. In this context, data centers are identified as crucial long-term infrastructure for AI's expansion. While there aren't many listed Indian companies purely focused on data centers yet, Bagga anticipates that utility-level companies, large corporations, and well-funded startups will step in to meet this "crying need." The government's initiative to procure more GPU chips for projects like the Indian stack and weather programs, along with private sector involvement in defense, will further drive demand for data centers.

A significant opportunity lies in integrating data centers with renewable energy sources, particularly solar power combined with storage solutions. Bagga points to recent instances where high solar generation led to zero incremental costs on electricity exchanges, suggesting that weekends could see surges of free power. Storing this energy for data center operations presents a viable business model. Alongside AI, Bagga also highlights the Global Capability Center (GCC) trend, with approximately 2,900 captive and third-party GCCs operating in India. Servicing these GCCs is currently seen as an easier avenue for Indian companies compared to the more complex AI domain. While AI is poised to be a major disruptor, its tangible impact on revenues and profits might take another two years to materialize.

The seemingly simple use of AI—from writing emails to generating portraits—incurs substantial backend costs related to data center capacity, cooling, and power consumption, which users often don't realize. Bagga shares anecdotes illustrating AI's pervasive influence, such as a Harvard professor's advice to be polite to AI tools and the alarming discovery of a thesis almost entirely written by ChatGPT. These examples underscore the immense processing power required, all of which relies on data centers, positioning them as fundamental infrastructure, akin to electricity, for the AI-driven future.