AI Force 2.0 Marks HCLTech’s Shift from Assistance to Autonomous AI
By C P Balasubramanyam ·
The first version of AI Force arrived in 2024, at a time when enterprises were still figuring out how generative AI could fit into their software development workflows. Two years later, HCLTech believes the conversation has fundamentally changed.
On April 1, HCLTech announced AI Force 2.0, the latest version of its proprietary enterprise AI platform, positioning it as a system that combines agentic AI and generative AI to automate and augment workflows across software engineering, data engineering, IT operations and business processes. HCLTech describes the platform as a model-agnostic and modular system that enables AI agents to analyse data, make context-aware decisions and take autonomous action at scale.
“AI Force 2.0 represents a significant leap forward in how enterprises harness AI solutions for transformation,” Vijay Guntur, CTO and Head of Ecosystems at HCLTech, had said in a statement during the launch. “By unifying agentic intelligence with enterprise-grade GenAI, we are enabling our clients to fundamentally reimagine software, data and operations lifecycles.”
But why did the company feel the need to build a second version in the first place?
In an interaction with AIM, Ananth Subramanya, Executive VP and Head of Customer Success and Product Management – AI Force, HCLTech, revealed that three major shifts in enterprise AI adoption drove the development of AI Force 2.0.
The first was the industry’s transition from generative AI systems that respond to prompts to agentic AI systems capable of pursuing goals autonomously. According to him, this shift requires orchestration, decision-making and continuous learning capabilities that go beyond conventional GenAI deployments.
The second was the growing demand for enterprise-grade governance, security and compliance as AI programmes moved from pilot projects into organisation-wide deployments.
The third was the realisation among clients that isolated AI use cases were no longer enough. Enterprises increasingly want AI integrated across functions and workflows, with measurable business outcomes rather than productivity gains confined to a single team.
Subramanya said AI Force 2.0 was designed to address these shifts through a broader platform approach that supports cross-enterprise AI adoption while remaining flexible through subscription or licensed commercial models and interoperability across multiple technology ecosystems.
That evolution reflects lessons learned from the platform’s original focus on software engineering.
He said AI Force 1.0 deliberately concentrated on software development lifecycle (SDLC) workflows because they represented one of the earliest and most mature applications of enterprise AI. The approach enabled the company to scale adoption quickly and demonstrate measurable value for customers.
However, those deployments also exposed several realities of enterprise AI. Among the lessons were the challenges of implementing responsible AI in production environments, scaling beyond pilot programmes, moving past productivity-focused metrics and managing security, governance and legacy system integration.
Those experiences eventually shaped the architecture of AI Force 2.0.
According to him, the platform has evolved from what was effectively a collection of generative AI use cases into an enterprise-wide platform architecture. He said AI Force 2.0 introduces an AI Store containing pre-built use cases, connectors and skills, while enabling capabilities spanning engineering, IT operations and business workflows.
A notable change is the platform’s model-agnostic design. Rather than relying on a single foundation model provider, AI Force 2.0 can work across multiple large language models. He said this approach is intended to prevent vendor lock-in and provide greater flexibility as the AI ecosystem evolves.
Subramanya also highlighted several architectural additions, including context-aware AI agents capable of reasoning, planning and acting autonomously within governance boundaries, a modular plug-and-play design, embedded responsible AI controls and support for cloud, hybrid and on-premises deployments.
If AI Force 1.0 was centred on assistance, HCLTech argues AI Force 2.0 is centred on autonomy.
The company describes the latest platform as a shift from assistive AI tools towards agentic systems capable of taking actions independently while remaining within enterprise guardrails. Rather than merely supporting individual tasks, these systems are intended to redesign and automate end-to-end workflows.
He said this opens possibilities such as continuous operations, faster decision-making, integrated workflows and broader automation across enterprise functions. At the same time, the company emphasises a human-in-the-loop model, arguing that explainability and transparency become increasingly important as AI systems take on more complex responsibilities.
The platform’s evolution also reflects how AI adoption has changed inside HCLTech itself.
Subramanya said AI Force has become foundational to its delivery model and is now used across all managed services programmes. HCLTech also claimed the platform has strengthened client adoption and deal momentum by serving as a front-door AI offering across global accounts.
While the company did not disclose specific revenue figures, it pointed to measurable outcomes, including faster time-to-market, improved decision-making, lower downtime and incident resolution times measured in minutes rather than hours.