The bigger questions

Summary: When an entire industry is written off, investors face a challenge that goes beyond picking individual stocks. This piece looks at how to think through major technological and economic shifts, and why reasoned conviction can matter most when the market is gripped by fear and noise.

For quite a while now, one of the biggest worries in our markets has been that India’s software companies are nearing the end of a long, profitable road. Every pundit came to the same conclusion: AI would write the code, answer support calls and run the back office, while the IT services industry would shrink and perhaps die. Investors seemed to agree, and the combined market caps of the largest listed companies fell to half. In fact, a well-known research house, Bernstein, wrote an open letter to the Prime Minister and warned about a broad white-collar employment crisis.

I’ll use this atmosphere of fear to make my point about how investing actually works. A sector is written off when the investor who thinks and the investor who reacts get separated. Picking good stocks at good value is only half the story. The other half, which is more difficult, is to take a reasoned view on the larger economic and technological forces that will shape the future of those companies over the years, and to hold that view with logic and conviction.

To explain, I’ll walk you through an analysis of the fear of AI I described above. Note that in this article, the method of the analysis matters more than the conclusion. The first thing to absorb is that we have been at such junctures earlier. Take ATMs, or in fact, bank computerisation in general. When these arrived, it was supposed to be the end of bank clerks and cashiers, and there was widespread fear that they would sharply reduce the number of employees banks needed. What actually happened is that it made banking cheaper, therefore much more accessible and led to a massive expansion of the industry. Can you imagine today’s banking network being affordable with automation? A tool that makes a task cheaper expands the demand for that task. The nature of the work changes, but the total quantity needed increases.

Apply this principle to software. If AI makes creating and running software cheaper, then it’s self-evident that the world will need far more software and related services, not less. In fact, there’s a long-standing principle named ‘Jevons’ Paradox’. As long ago as 1865, economist William Jevons noted that James Watt’s efficient steam engine used far less coal and because of this, factories installed more engines and burned more coal. The total amount of software services needed globally is not fixed; it’s constrained by what can be created and used economically.

Over the next few years, every business in the world will move from dabbling in AI like a hobbyist to running AI tools properly across its operations. This is a huge task and mostly a messy, unglamorous job:  cleaning up decades of old data, connecting new systems to old ones, keeping them secure, compliant with laws and regulations and generally taking care of details. This is the kind of work our services industry has spent three decades learning to do at scale. There is a further twist that AI pessimists miss — many companies globally are discovering that buying the technology is easy and getting a real return from it is hard, and this is the gap Indian services firms are needed to close. The evidence for what I say is already visible: larger companies are reporting billions of dollars in new AI-related business while AI fear peaks.

Sure, this does not mean that the road ahead is smooth. The next couple of years may be problematic because efficiency will happen, but new demand will take time. Our own view at Value Research, which is a considered judgment rather than a certainty, is that the way services work is priced and organised will change a lot, but eventually there will be more work, not less.

This is the part of our work at Value Research Stock Advisor that is easy to overlook by our members. Everyone can see the list of recommendations we put out, as well as the stock-level analysis behind it. Less visible are the higher-level trends that can broadly influence businesses and the economy. Of course, many members ask ‘higher level’ questions that we firmly ignore. For example, “What will the level of the Sensex be a year from now?” However, developing a reasoned view on a fundamental shift like AI is central to the kind of thinking we do on stocks. This kind of analysis is a major part of our job.

I have described earlier the disciplined process that underlies our success. Our process begins by eliminating rather than selecting, by discarding companies that fail our tests of governance and financial health. Only then do we look at the survivors of this elimination round and judge which of them will generate real wealth for you. A carefully considered view on a development like AI does not override this discipline; it adds to it and helps us judge who stands to gain and why. It’s part of our system in which every month our research team revisits each of our three portfolios: Long-term Growth, Aggressive Growth and Dividend Growth. When the facts change, we act on them and tell you why.

For Rs 9,990 a year, what you are buying is not the list but the thinking that produced and maintains that list, and the team that maintains it through the kind of fear gripping investors. Anyone can hand you the names of a few good companies; that’s not difficult. The real value lies in someone who has worked out the answers to the day’s big questions so your investment decisions aren’t swamped by fear and noise. 

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