The automation technology landscape has evolved from rule-based automation to machine learning, GenAI, and Agentic AI. Agentic AI is at a pivotal moment as enterprises prepare for the transition and technology leaders reimagine internal IT operations to address this change and ensure business growth.
Agentic AI helps companies move from experimentation to execution and creates measurable value across industries.
“Agentic AI requirements are now well established in conversations with multiple clients and their IT leaders around the world. They primarily want the right foundation, the right security, and the right compliance framework to run Agentic AI in their environment,” said Piyush Saxena, SVP and Global Head of Google Business Unit at HCLTech.
Therefore, production readiness is essential for agent use cases to perform well in production, he added.
One of HCLTech's banking customers is implementing an agent operating model across 100,000 agents over the next three years.
“Core IT needs to be robust and scalable to allow Agentic AI to fit into enterprise architectures and be suitable for Agentic AI use cases moving into production. There is cautious optimism about Agentic AI across the customer base,” he added.
“IT process readiness is necessary for agent feasibility analysis, scaling the preparation of AI design patterns, or if an enterprise is considering AI design principles for security. Organizations need to have the right agent AI foundation in place and a robust operational model that works seamlessly with multiple agents in the environment,” says Piyush.
Coordinating agents to implement multiple agents in a multicloud ecosystem requires interoperability and orchestration, which technology providers like HCLTech are working on.
Security, new skill set
It is essential for enterprises to manage Agentic AI with guardrails like Guardian Agents to ensure ethical, transparent, compliant and autonomous behavior.
As security lapses on the Agentic AI side can spread across multiple agents, resulting in severe business impact, frameworks (OWASP, MITER OCCULT) help organizations ensure robust security and define governance, guardrails, and controls according to Piyush.
According to the 2025 Foundry State of the CIO Study, AI/ML skillsets are the biggest challenge for CIOs. Piyush agrees, “New technologies evolve faster than we can keep up, making regular learning sessions and certifications for new skill sets essential. Working with hyperscalar partners like Google Cloud, we are focusing on certification courses and new training programs to upskill and reskill our employees and teams.”
“We believe that new skill sets are required from a technical perspective, such as prompt engineering, machine learning, and process engineering, and from a human capabilities perspective, such as critical thinking, strategic monitoring, and ethical reasoning, and a combination of both skills is ideal for a successful organization's AI journey,” says Piyush.
“Agentic AI provides corrective action compared to traditional automation and GenAI. This is one of its biggest attributes. End customers consider Agentic AI to be a dual tactic: either create a competitive advantage in the market or increase productivity that impacts business growth,” Piyush adds.
Strategic partnership with Google Cloud
HCLTech and Google Cloud will work with industry-focused, workflow-specific agents to guide your migration, minimizing manual effort and improving decision quality across a variety of use cases.
Both teams regularly participate in technical programs and certifications hosted internally and by customer teams. “For example, the training on the Gemini platform and its use in the enterprise was beneficial from both a technical and business perspective,” says Piyush.
At the forefront of accelerating the adoption of Agentic AI, HCLTech and Google Cloud launched over 200 industry-specific horizontal needs agents in April 2025. “More than 200 agents are in development. For example, the Insight agent for manufacturing will help with predictive detection and remediation solutions that are multi-agents built for multi-cloud environments. We are working with Google Cloud on training and certification across our customer base, primarily finance, insurance, healthcare, and life.” In addition to agenttic AI as a megatrend, edge inference will become even more prominent in 2026, Piyush adds.
With the advent of Agentic AI, CIOs and technology leaders are poised to align their IT strategic priorities, mitigate emerging security risks, and reskill their staff for a new era.
“As CIOs build digital infrastructure in the world of AI, they need a well-defined and robust strategy for their deployment framework. The Agentic AI blueprint and its design must be communicated to all stakeholders in the organization for a transparent vision and successful execution,” said Piyush Saxena, SVP and Global Head of Google Business Unit at HCLTech.
