Rethinking the IT organization today for the Agentic AI era

The automation technology landscape has evolved from rule-based automation to machine learning to GenAI to Agentic AI. Agentic AI marks a pivotal moment, as the enterprises prepare themselves for the shift and tech leaders will restructure their internal IT operations to navigate this change and ensure business growth.

Agentic AI is helping businesses transition from experimentation to execution and create measurable value across various industries.

“The requirement for Agentic AI has been well established now, during our conversations with multiple clients and their IT leaders across the globe. They are primarily seeking the right foundation, right security and right compliance framework to run Agentic AI in their environment,” says Piyush Saxena, SVP and Global Head, Google Business Unit, HCLTech.

Operational readiness is therefore a must for agentic use cases to perform well in production, he adds.

One of the banking clients of HCLTech is implementing an agentic operating model for the next three years, spread across one hundred thousand agents.

“The core IT must be robust and scalable for Agentic AI to adapt in enterprise architecture and suitable for Agentic AI use cases to move into production. There is cautious optimism around Agentic AI across the customer base”, he adds.

“The IT process readiness is a necessity for agentic feasibility analysis or scaling AI design pattern readiness, or if enterprises are looking at AI design principles for security. The organisations should have the right Agentic AI foundation and a robust operating model in place that works seamlessly with multiple agents in their environment,” says Piyush.

Orchestrating agents to implement multiple agents in a multicloud ecosystem requires interoperability and orchestration, which tech providers like HCLTech address.

The Security aspect, new skillsets

It is essential for enterprises to govern Agentic AI using guardrails like guardian agents and to ensure ethical, transparent and compliant autonomous behaviour.

Security lapse on Agentic AI side can spread across multiple agents, resulting in severe business impact and hence frameworks (OWASP, MITRE OCCULT) ensure that the organisations have robust security in place, defining governance, guardrails and control as per Piyush.

The skill sets in AI/ML are the number one challenge for CIOs, according to the Foundry State of the CIO Study, 2025. Piyush agrees, “The evolution of new technologies is much faster than one can keep pace and hence regular learning sessions and certifications on new skillsets become vital. With hyperscaler partners like Google Cloud, we focus on certification courses and new training programs to upskill and reskill the employees and our teams.”

“We see the demand for new skillsets like prompt engineering, ML, process engineering from a technical perspective and critical thinking, strategic oversight and ethical reasoning from a human ability perspective. And the combination of both sides of skills is ideal for a successful AI journey for organisations”, says Piyush.

“Agentic AI provides corrective action over traditional automation or GenAI, which is one of the biggest attributes. The end customers regard Agentic AI as a two-fold tactic – create competitive advantage in the marketplace, or there is a productivity gain that impacts the business growth”, adds Piyush.

Strategic Partnership with Google Cloud

HCLTech and Google Cloud aretraversing the shift with industry–focused and workflow-specific agents to minimize manual work and enhance decision-making quality 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 the enterprises from both technical and business perspectives has been beneficial”, says Piyush.

At the forefront of accelerating the adoption of Agentic AI, HCLTech and Google Cloud launched over 200 industry-specific and horizontal need agents in April 2025. “More than 200 are in the pipeline. For example, the Insight agent for the manufacturing industry helps in predictive detection and correction solutions, a multi-agent built for a multicloud environment. We, along with Google Cloud, engage in training and certification across the customer base, mainly financial and insurance, healthcare and life sciences, which are moving at a rapid scale with respect to the adoption of Agentic AI. Besides Agentic AI as the mega trend, Edge Inferencing will witness more prominence in 2026”, adds Piyush.

With the advent of Agentic AI, CIOs and technology leaders are well poised to adjust strategic IT priorities, mitigate new security risks and reskill staff for a new era.

“As CIOs build their digital infrastructure in the AI world, they must have a clearly defined, robust strategy for an adoption framework. The Agentic AI blueprint and its design must be communicated to all the stakeholders of their organization for a transparent vision and successful execution,” says Piyush Saxena, SVP and Global Head, Google Business Unit, HCLTech.