AI-related spending in the US has jumped from just $33 billion in 2022 to an estimated $862 billion this year. Nvidia's data-centre revenue alone is projected to rise from $15 billion to nearly $394 billion over the same period. With numbers like these, it's hardly surprising that investors across the world are looking for ways to participate in the AI boom.
Whether it's global technology funds, AI-themed ETFs or individual tech stocks, the temptation to jump aboard is understandable.
But before you do, it may be worth asking a few questions.
DSP Mutual Fund's latest NETRA report argues that while AI could transform industries over the coming decade, investors shouldn't assume every company riding the AI wave will automatically become a winning investment.
Here are four questions every investor should think about before chasing the rally.
1. Are companies making money, or just spending it?
Every new AI announcement seems to come with another billion-dollar investment.
But bigger spending doesn't automatically translate into bigger returns for shareholders.
According to the report, AI investment in the US has grown from 0.1% of GDP in 2022 to around 2.7% in 2026, making it one of the largest capital spending cycles in modern history. Yet much of that investment is still being made upfront, while the revenues needed to justify it are yet to fully materialise.
DSP estimates that nearly $1 trillion could be spent on AI infrastructure this year. To generate adequate returns across the ecosystem, businesses and consumers may eventually need to spend $2.5 trillion to $4 trillion annually on AI products and services.
What this means for you: A company announcing massive AI investments may sound exciting, but investors should pay equal attention to whether those investments are actually translating into profits and cash flows.
2. Do you know what your AI investment is actually betting on?
Most people think AI is all about software.
The next phase of AI is likely to be driven by the physical infrastructure behind it, advanced chips, GPUs, memory, data centres and electricity.
The report notes that newer AI models can consume 100 to 1,000 times more computing resources than earlier models. Some of the world's largest AI data centres now under construction could consume as much electricity as around five million households.
That means two AI funds may both carry the "AI" label but invest in completely different parts of the value chain.
What this means for you: Before investing, look beyond the theme. Check whether your fund owns software companies, semiconductor makers, infrastructure businesses, or a mix of all three.
3. Has too much optimism already been priced in?
This may be the most important question of all.
Since 2020, six of the world's biggest technology companies, including Microsoft, Amazon, Alphabet and Meta, have collectively spent about $1.29 trillion on capital expenditure, comfortably exceeding the roughly $911 billion spent by six global oil and gas giants over the same period.
Meanwhile, technology companies are now worth more than $41 trillion globally and trade at around 37 times trailing earnings, compared with roughly 23 times for seven other major sectors combined.
None of this proves AI stocks are expensive.
But it does suggest expectations have become exceptionally high. When markets expect near-perfect execution, even strong earnings can disappoint investors.
What this means for you: Great companies don't always make great investments if you buy them at any price.
It's easy to feel that India has been left behind while global AI stocks race ahead.
But the report offers a different perspective.
Unlike global markets, India's technology sector is dominated by IT services rather than semiconductor or hardware companies. As a result, technology's weight in the Nifty 50 has fallen from around 19% in late 2021 to nearly 7% today, even as global technology indices have become increasingly driven by AI hardware companies.
But concentration works both ways. The sectors that rise the fastest during a boom can also fall the hardest if sentiment changes.
What this means for you: Missing part of a rally can sometimes mean avoiding the biggest risks if the cycle eventually cools.
AI could well become one of the defining investment themes of the next decade. But successful investing isn't about buying every exciting story, it's about separating a great technology from a great investment.
The AI revolution may be real. The bigger question for investors today is whether the market has already priced in much of that future.
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