Many experts have been issuing warnings over the impact that AI could have on India’s software industry. But Zoho CEO Sridhar Vembu says that the industry’s problems go much deeper than that — there are current issues that plague the industry, which will only be exacerbated with AI.
Vembu argues that India’s software industry became bloated because of excess capital infusion from a variety of sources. These companies then used this money to aggressively market their services, which caused IT budgets at their client companies to balloon. Western companies outsourced their IT development to India, and they didn’t mind the inefficiencies because they were saving money in spite of them. And because Indian companies billed corporations based on hours put in by human workers, they had no reason to streamline their operations either. But AI can now create much of this code at a fraction of the cost, which will lay bare how inefficient IT systems had become over the years.
Here is Vembu’s post in its entirety:
What is ailing the software job market is not AI taking away jobs (not yet anyway).
Here is my thesis, as a participant and observer of software for 30 years. Over those 30 years:
1. Massive over-capacity steadily developed in enterprise software due to a flood of VC, PE and IPO money.
2. Software vendors applied liberal doses of marketing spending to spread Fear (of missing out) and Uncertainty (“tech is changing, you need us”) and Doubt (“are you confused? trust us”) among corporate customers and the result was ever growing IT spending. Enterprise IT budgets kept rising because which CIO or Board would want to be seen as lagging? Major corporations in the West have layers and layers of duplicated IT systems, lots of money spent to acquire them and even more money spent to get the disparate systems to work together. The more inefficient IT systems ended up becoming permanent resource drains, requiring vast human resources to simply keep them running.
3. Large enterprises in the West found those needed human resources in India – transferring those inefficiencies to IT services firms in India, often multiplied by 3 or even 4! That “multiplied inefficiency” happened because IT budgets were kept fixed in dollar terms and more people got hired in India to “get more done”. Result? A large number of IT jobs in India came to depend on those original inefficiencies and the multiplied inefficiencies.
4. Note how Indian banks and financial institutions are more IT savvy, while spending far less, than established financial majors in the US – Indian firms did not have the budgets to splurge! Necessity made them highly efficient and today India’s financial institutions are able to fend off foreign competition easily.
5. One of the deep facts about software is that often a 2 person team can solidly outperform a 20 person team and a 10 person team can do the work of a 200 person team. This is not just due to talent disparity – even when the large teams have equivalent talented people, they can easily end up being wasted on unproductive projects.
6. When people are billed by the hour or by the staff month (input metrics), as it happens often in IT services, there is zero incentive to remove those inefficiencies, to empower the 2 person team as opposed to hiring 20.
It is those multiplied inefficiencies in IT, built up over decades, that is facing a reckoning now.
Now enter AI. A large amount of code is boilerplate code in many projects and AI can eat such code for breakfast. Depending on the nature of a project AI can offer 10-20% productivity gains. Significant but not the 10x or 100x leap yet to destroy jobs on a vast scale.
But those AI gains of today pale in comparison to the “multiplied inefficiencies” built up over decades. This reckoning nearly happened in the aftermath of the Global Financial Crisis (GFC 2008-9). It got postponed because the central banks flooded the world with money and a part of that money flooded into enterprise IT. The pandemic unleashed another flood of money into enterprise IT. Those floods are now history and we have a serious drought. That is why I am pessimistic about the software job market, even before accounting for AI.