AI is enabling us to compete at larger tables: Persistent Systems CTO

We have predominantly been a digital engineering company over the last 33-plus years. We began as a product engineering partner for some of the biggest product companies, many of whom are still our customers.

In the last four or five years, this shift in thinking and building rapidly, and innovating like product companies has become more marked. In that process, enterprises are modernising their infrastructure, and applications, and moving to the cloud. In the last decade, AI and data have become a central part of that agenda. 

There are two major ways in which we are helping our customers adapt to data. One is modernising their data infrastructure, making it more democratic and elastic with cloud and so forth. The second is monetising their data more effectively. Both things are interlinked and as much of a big swim lane as application modernisation itself. 

About two and half years ago, everyone became aware of the GenAI evolution and revolution, which has been dominating conversations for the last 24 to 30 months. The last calendar year was about experimentation. Everybody was trying to figure out how to harness GenAI for enterprise use cases and value, and how to do it safely at enterprise scale without compromising their data. We helped many companies do that over the last year. This year has been about taking those initial experiments and proofs of concept to production and pilots. 

Organisations globally realised they cannot walk away from this technology because it’s important for differentiating, surviving, and thriving. Nimbler and more forward-looking technology client companies, or high-tech companies who build software, often adopt these things more rapidly. Other companies in the enterprise space already modern in how they add their data infrastructure were able to adopt the AI revolution speedily, even while being cautious. 

Some companies are more cautious and circumspect in adopting AI, either because they are highly regulated, so every change they make in modernising requires them to first think of doing no harm. Sometimes, some companies are slower to adopt because their data infrastructure isn’t modern enough, their data silos are not unified enough and the data aren’t clean enough for them to rapidly and meaningfully adopt AI.  

AI, particularly GenAI, has, in the last two years, evolved rapidly, and almost exponentially in terms of the capabilities it delivers, but also in driving down the cost of compute, training, and inference. 2-3 years ago, it would take hundreds of millions of dollars and months of training to build something meaningful. Today you can do that at a much lower cost, with far more ease. Many more companies are building these large foundation models than ever. 

There are different patterns of companies adopting, but almost everybody is adopting AI. There can also be an expansion of revenue if AI is adopted cleverly.

Our go-to-market approach has transformed. We have pivoted to being an AI platform-driven digital engineering services company. The advent of Gen AI has fundamentally changed how people and organisations build software, and our business is to build software for our customers. We had to naturally adapt, or we wouldn’t survive. 

Our adoption of this change began early and that’s, in part, what our CTO office and innovation labs across the company do — spot trends early to figure out how they will affect our own business and customers’ business. The pivot we made is building a more comprehensive platform that changes everything about building software, right from design to software development to product management to sustaining that software, and patching and maintaining it – the entire life cycle, rather than taking a piecemeal view of it. 

More than comparing ourselves to a larger company, it is about how we create an advantage for ourselves. With AI and the platform approach, we are living what we propose and recommend to our customers — transforming the business of building software and our own business. 

We do many multi-year modernisation or digital transformation journeys for our customers. Even to win these, we have to understand customers’ requirements and change how we engage them. If we can assess their landscape better and the north star of where they want to go, we can use our platforms to deliver insights into their current landscape and give a more tailored and competitive proposal that is more outcome-driven rather than just time and materials-driven. 

With this technology, we can now compete at much larger tables than what our headcount size would allow, because it’s our headcount plus a suite of AI-powered platforms that make us more competitive to take on larger and more complex transformation journeys for our customers, expanding the universe where we can play, going after a much larger revenue base for us. Our mid-term to long-term intent is to be more efficient in terms of revenue per employee and margin per employee and that’s how the whole strategic story is coming together with these platforms. 

We prefer our engagements with customers to be longer-term relationships and they also refer to us as a long-term partner. We’ve had customers that have been with us for 33 years, with many larger players also being multi-decade customers. 

There may be customers who are multi-decade in existence, but it is, in part, our opportunity and responsibility to educate and enable them to be nimbler, to take advantage of technology, and to leapfrog their own competition. 

Our philosophy has always been that whatever our innovation and technology teams are doing on the cutting edge of tech, to bring that value to life inside a customer environment, show them that value, and take them on that journey of transformation. 

The cycle of transformation will get shorter as they move faster but transformation doesn’t end. It’s just that you get more done in a multi-year channel. We’re deepening our relationships with these customers, and our CEO addresses how the mix of our large customers is changing quarter over quarter. 

That’s a conscious journey we are on and at the same time, we are always expanding to new logos. The fun and the growth come from taking on larger clients and moving fast with them, rather than going with a slew of small clients. The growth vector will always be with the bigger companies.