As enterprises grapple with rising AI costs and seek clearer returns on their investments, mid-tier IT services firm Persistent Systems is increasingly positioning cost control and outcome-based delivery at the centre of its AI strategy.
The company’s proprietary 3C Framework, designed to help enterprises scale AI initiatives from pilot projects to production, incorporates governance and cost management as core elements, Chief Operating Officer – Technology, Jaideep Dhok told FE.
“Cost becomes an inherent part of interoperability as customers tend to focus on cost neutrality or cost control right from the word go,” Dhok said. “If you look at our customer platforms like SASVA (services as a software enabled by virtual agents), they leverage this core architectural blueprint, which includes building blocks like governance.”
His comments come at a time when enterprises are increasingly evaluating the economics of generative AI deployments as token consumption rises and organisations move from experimentation to large-scale adoption. According to Dhok, Persistent’s focus sectors, including banking, financial services and insurance (BFSI), healthcare, life sciences and hi-tech have remained committed to AI investments despite heightened scrutiny around spending.
Token-Free Models
One reason is the firm’s deployment model. Given the stringent security and compliance requirements of many clients, Persistent often deploys AI models on-premise or within customer-controlled environments rather than relying entirely on public cloud services. “They’re not being charged on AI tokens, and our customers love that,” Dhok said, adding that he has not witnessed tighter AI budgets among the company’s clients.
The company is also benefiting from a broader shift in enterprise spending patterns. Organisations are using AI to drive efficiencies in existing projects and business-as-usual operations, with savings increasingly being redirected towards AI infrastructure and transformation programmes. “We’re basically one of the few firms that is benefitting from compression as it aids our transformation business,” Dhok said.
At the same time, clients are demanding greater accountability from service providers. Dhok said both traditional outsourcing contracts and AI-led transformation engagements are becoming increasingly outcome-oriented. While legacy projects are typically structured as fixed-price arrangements, transformation programmes are often linked to predefined milestones. “Persistent is ensuring we focus on total cost of ownership for customers in terms of their transformation, productivity growth and AI infrastructure costs,” he said.
Scaling Outcomes
To support these engagements, the company is scaling its team of forward deployed engineers (FDE), specialists who work closely with clients to drive adoption and organisational change. However, Dhok stressed that AI transformation extends far beyond deploying models. “There are various aspects of architecture, security, cloud, data and privacy that need an entire team to evaluate and validate,” he said.
Persistent is also seeing strong demand for modernisation projects among BFSI and healthcare clients, many of whom continue to operate decades-old systems. While replacing legacy technology is relatively straightforward, Dhok said preserving institutional knowledge remains a significant challenge. “There are legacy systems still which are 40 years old. A new tech platform is relatively easily built, but customers still have to understand internally how the system works. This context is where the bulk of the work lies,” he said.
The company also tracks productivity gains from AI coding tools used internally and by clients. However, Dhok said the focus remains on enabling teams to accomplish more work rather than directly translating efficiencies into workforce reductions. “We tend to focus more on those aspects,” he said.