Hexaware CEO R Srikrishna Discusses AI Pricing Models and Fresher Hiring

The IT sector faces a complex environment as companies navigate artificial intelligence-related costs and shift toward lateral hiring. Hexaware CEO R Srikrishna addressed these industry dynamics in a recent discussion, detailing the firm's approach to pricing models, workforce composition, and research and development initiatives.

Addressing the rationale behind introducing multiple pricing models for customers, Srikrishna explained that the primary objective is to participate in token economics. As token costs become a material part of IT budgets, the company aims to add value to clients rather than act as a reseller. This approach allows Hexaware to participate in token revenue while optimizing costs for its clients.

On the topic of workforce composition, Srikrishna acknowledged that the percentage of freshers in the hiring process has seen a reduction across the industry. He described this trend as temporary, drawing parallels to past cycles where the industry successfully scaled training processes to meet demand. According to Srikrishna, younger talent often demonstrates strong capabilities in artificial intelligence because many graduates are AI-native, having utilized these technologies during their education. However, he noted that customer hesitation remains a primary factor behind the slower adoption of freshers in initial program phases, with clients typically preferring more senior talent for AI initiatives.

Highlighting internal practices, Srikrishna stated that Hexaware's AI labs, research and development teams, and platform building units employ individuals with an average age of around 26 years. The company's investments in research and development have enabled faster development cycles, allowing teams to build minimum viable products in eight weeks and deliver first releases in twelve weeks.

The discussion also touched on how artificial intelligence is changing customer spending habits regarding legacy technology debt. Historically, clients often hesitated to invest in technology upgrades due to time constraints, risks, and high expenses. Srikrishna noted that AI has made these processes more deterministic, leading to deals exceeding $10 billion focused on tech debt remediation and modernization.

"The integration of artificial intelligence into IT operations is fundamentally shifting how companies approach both pricing models and talent acquisition. While client hesitation has temporarily reduced fresher hiring, the reality is that younger generations bring native familiarity with AI tools that will become invaluable as adoption matures. IT service providers must balance immediate client preferences for senior talent with long-term capability building, especially as large-scale modernization and tech debt remediation projects continue to expand." — Dr. Shishir Gupta, Founder & CEO, StartupLanes