The automation technology landscape has evolved from rules-based automation to machine learning, GenAI and Agentic AI. Agentic AI marks a pivotal moment as businesses prepare for change and technology leaders restructure their internal IT operations to accommodate this change and drive business growth.
Agentic AI helps businesses move from experimentation to execution and create measurable value across diverse industries.
“The requirement for agentic AI is now well established, in our conversations with several customers and their IT managers across the world. They are primarily looking for the right foundation, security and compliance framework to run Agentic AI in their environment,” says Piyush Saxena, SVP and Global Head of Google Business Unit, HCLTech.
Operational readiness is therefore essential for agentic use cases to work properly in production, he adds.
One of HCLTech’s banking clients is implementing an agent operating model for the next three years, spread across one hundred thousand agents.
“The core IT system must be robust and scalable for agentic AI to fit into the enterprise architecture and be tailored to agentic AI use cases to move into production. There is cautious optimism around agentic AI within the customer base,” he adds.
“IT process readiness is a necessity for agentic feasibility analysis or scaling AI design model readiness, or if businesses are looking at AI design principles for security. Organizations need to have the right foundation of agentic AI and a robust operational model in place that works seamlessly with multiple agents in their environment,” says Piyush.
Agent orchestration to implement multiple agents in a multi-cloud ecosystem requires interoperability and orchestration, which technology providers like HCLTech address.
The Security aspect, new skills
It is essential for businesses to govern agentic AI using safeguards such as guardian agents and ensure ethical, transparent and compliant autonomous behavior.
Security breaches on the agentic AI side can propagate to multiple agents, leading to serious impacts on the business and therefore, frameworks (OWASP, MITER OCCULT) ensure that organizations have robust security, defining governance, guardrails and control in accordance with Piyush.
AI/ML skills are the number one challenge for CIOs, according to the Foundry State of the CIO, 2025 study. Piyush agrees: “The evolution of new technologies is much faster than one can keep pace and therefore regular learning sessions and certifications on new skills become vital. With hyperscaler partners like Google Cloud, we are focusing on certification courses and new training programs to upskill and reskill employees and our teams.”
“We are seeing a demand for new skills like rapid engineering, ML, process engineering from a technical perspective and critical thinking, strategic monitoring and ethical reasoning from a human capabilities perspective. And combining both sides of skills is ideal for a successful AI journey for organizations,” says Piyush.
“Agentic AI provides corrective actions compared to traditional automation or GenAI, which is one of the most important attributes. End customers view Agentic AI as a dual tactic: creating a competitive advantage in the market or generating productivity gain that impacts business growth,” adds Piyush.
Strategic partnership with Google Cloud
HCLTech and Google Cloud are taking the plunge with industry-focused and workflow-specific agents to minimize manual work and improve the quality of decision-making across various use cases.
Both teams regularly participate in technical programs and certifications organized internally and by customer teams. “For example, training on the Gemini platform and its use in businesses, both from a technical and business perspective, has been beneficial,” says Piyush.
At the forefront of accelerating the adoption of agentic AI, HCLTech and Google Cloud launched more than 200 industry-specific and horizontal requirements agents in April 2025. “More than 200 are in the pipeline. For example, the Insight agent for the manufacturing industry helps with predictive detection and remediation solutions, a multi-agent designed for a multi-cloud environment. We, along with Google Cloud, are engaged in the training and certification of the entire customer base, primarily in the areas of finance and insurance, healthcare and life sciences, which are evolving at a rapid scale with regard to the adoption of agentic AI Apart from agentic AI as a megatrend, Edge Inferencing will witness greater importance in 2026,” adds Piyush.
With the advent of agentic AI, CIOs and technology leaders are well-positioned to adjust strategic IT priorities, mitigate new security risks, and reskill staff for a new era.
“As CIOs build their digital infrastructure in the world of AI, they must have a strong and clearly defined strategy for an adoption framework. The Agentic AI plan and its design must be communicated to all stakeholders in their organization for transparent vision and successful execution,” says Piyush Saxena, Senior Vice President and Global Head of Google Business Unit, HCLTech.
