HCLTech’s AI Strategy Signals the Future of Application Development & Modernization Services

Strategy shifts in applications development accelerate and augment client outcomes

How will application services evolve in the era of AI? And how will clients maximize return on investment as they undergo application and IT modernization as well as digital transformation to facilitate AI adoption and push innovation? On May 6, TBR attended HCLTech’s inaugural Global Leadership Briefing for its Modern Application business, and HCLTech addressed the intersection of these two questions. HCLTech detailed clients’ current and future application needs and how its refreshed strategy enhances application capabilities and service quality.
 
HCLTech’s Modern Application business head, Padmaja Enjeti, explained the company’s view that “AI is not just accelerating application development, it’s basically redefining what applications are and how they’re engineered, and in what context.” AI is now embedded across workflows, architecture and design, rather than being simply an add-on. HCLTech defined how AI fundamentally has changed application development practice across its four pillars: AI-driven modernization, AI-native application development, intelligent quality engineering, and AI-driven integration. AI Force, HCLTech’s generative AI (GenAI) and agentic AI platform, is the company’s “execution backbone” at the core of its innovation efforts.
 
During the briefing the company detailed how AI Force is adapting each of these pillars. In this report, TBR will focus on discussions of specific AI Force solutions related to the AI-driven modernization, application development, and intelligent quality engineering pillars, as they are concrete examples of how the company is reshaping client outcomes. The cornerstone of the discussion about AI-driven modernization was AI Force.ATLAS, an agentic framework for modernization at scale. Vineet Gogia, HCLTech’s Modern Application practice director, provided an in-depth look at how the solution can reverse-engineer legacy code. AI Force.ATLAS generates a knowledge graph for dependency mapping, providing traceability and validation throughout the coding modernization process. The solution also has an interactive analyst-agent interface to answer client questions.
 
During the applications development discussion, global AI-native Application Development practice director, Venkatraman Natarajan, demonstrated AI Force.Agent Squad, an agent-powered framework for the autonomous software development life cycle. The solution offers an agent dashboard and control panel, supporting cohesive development workflows including feature development, bug fixing, re-architecture, PR review and security vulnerability remediation.
 
Charu Sharma, Integration practice director, demonstrated AI Force.QMetrix during the intelligent quality engineering portion of the briefing. AI Force.QMetrix is an interconnected quality engineering maturity assessment tool for an applications portfolio, including autonomous workflows and agents.
 
Together, these solutions enhance HCLTech’s value proposition and align with client demands for more trustworthy AI and less manual inputs, in TBR’s view. HCLTech places governance practices, such as human-in-the-loop and related transparent processes, as a key component across its AI Force solutions. As the company shifts toward agent-driven development, where applications are becoming more adaptive through AI Force, HCLTech becomes more agile.

How will HCLTech mitigate clients’ rising concerns about ROI?

Agile or not, IT services clients are demanding ROI across AI-related deals. According to TBR’s IT Services Market Forecast 2025-2030, clients are “prioritizing ROI, cost efficiency and accountability, increasingly favoring fixed-price and outcome-oriented engagements. Clients are also looking for measurable results and shorter payback periods and have lower tolerance for time-and-materials billing. This pushes vendors to absorb productivity gains internally instead of translating them into revenue through increased staffing levels. India-centric providers face the most immediate disruption due to their exposure to labor-intensive services.” Shortly after TBR published this report, HCLTech CEO C. Vijayakumar stated on the company’s 1Q26 earnings that HCLTech is experiencing a “deflation” around traditional IT services. In TBR’s view, HCLTech’s proactive approach positions the company well to engage with clients on newer areas, provided it can address their growing concerns around AI.
 
During the session, Enjeti touched on how the Application Development practice is evolving to accommodate clients’ rapidly changing demands. HCLTech is “focusing on building these new pricing models … along with our customers [and] delivery squads from an agentic squad construction perspective … where AI agents are amplifying human teams so we are able to commit to productivity at scale without linear headcount growth.” At the same time, the company is standardizing its factory model to drive repeatable outcomes. HCLTech is successfully leveraging AI Force solutions to deliver outcomes; however, these can vary dramatically. For example, AI Force.Agent Squad enabled a client to develop an application with 40% fewer defects and shorten the time to market by about 50%. With AI Force i-Catalogue, an AI-powered digital asset access and management solution part of the integration pillar, HCLTech helped a mining company modernize and standardize integration by implementing an Integration Competency Center. The solution improved automation efficiency by 25%, reduced onboarding time, and increased asset reuse by approximately 30%.
 
Meaningful outcomes from adopting advanced AI solutions can mean many things, such as reduced costs, enhanced service quality and decreased time to market. Amid rising ROI concerns, clients may have to decide which outcome(s) they are looking for. Sustaining advanced AI engagement momentum may depend on how well HCLTech can effectively communicate the importance of choosing a desired outcome and the right metric to measure its success. HCLTech needs to reassure clients that they can experience enterprisewide productivity improvements related to these AI engagements, but it will take time for the benefits to fully materialize.

Where is HCLTech’s road map from here?

Investments in platform-enabled solutions through AI Force, aligning with HCLTech’s engineering and software strengths, provide a strong near-term outlook, especially paired with the company’s industry-specific approach, which is becoming essential in the AI era. HCLTech is reorganizing its talent structure to be specialized, including dedicated teams — AI builders, AI super users and AI decision makers — which enhance task-specific expertise. Through the introduction of full-stack engineers, forward-deployed engineers and AI orchestrators, HCLTech is addressing new pricing needs.
 
Reengineering applications accelerates time to value and augments service quality; however, advanced AI capabilities evolve quickly. Over the next five years, HCLTech needs to protect margins, perhaps through fostering more value through IT consulting. The company also needs to protect itself from competition from other India-centric vendors, and TBR believes this will require persistent innovation and, most importantly, execution.