The agentic blueprint: Engineering autonomous enterprises

HCLTech experts Piyush Saxena and Mangesh Mulmule outlined a blueprint for enterprises to adopt agentic AI, emphasizing data quality, operational safety, and modular design. The company is collaborating with Google Cloud to accelerate adoption through prebuilt agents and implementation frameworks.

The rise of agentic AI is reshaping how organizations think about automation and how it puts them on the path to becoming fully autonomous enterprises. Agentic AI transforms the traditional IT model by shifting routine task execution from humans to intelligent systems capable of independently managing workflows. For example, it’s already proving effective in customer service use cases, where AI agents can autonomously process requests such as authorizations for returned merchandise. However, not all applications or use cases are ready for autonomous operations. That’s why organizations need an agentic blueprint, according to two HCLTech experts in a recent video discussion. “Organizations need to be very clear in terms of having their agentic blueprint with defined outcomes,” said Piyush Saxena, senior vice president and global head of the Google Business Unit at HCLTech. IT leaders should take a thoughtful, structured approach and consider factors such as data quality, operational safety, and reliability before fully trusting autonomous systems. In addition, enterprises must put data at the core of agentic transformation, said Mangesh Mulmule, vice president of HCLTech. It’s critical to design systems that deliver “the right data at the right time to the AI agents to ensure that AI outputs remain relevant and trustworthy,” he said. This strategy requires robust data pipelines, integrated architectures, and a clear understanding of how information flows across the organization. Mulmule also noted the importance of designing agents with specific, well-defined objectives. “By creating modular and reusable components, organizations can build scalable ecosystems of AI agents that can be applied across multiple business processes,” he said. A platform-based approach further supports this scalability, enabling consistent monitoring, governance, and lifecycle management of AI systems. Ultimately, the transition to an autonomous enterprise requires more than just technology. That’s why organizations should work with providers that have built strategic partnerships that marry their expertise in engineering, AI capabilities, and IT infrastructure. For example, HCLTech’s collaboration with Google Cloud helps organizations accelerate adoption by providing prebuilt agents, implementation frameworks, and industry-specific solutions. “We are one of the seven GSI partners that Google Cloud has selected globally to drive the Gemini Enterprise Adoption Program https://www.hcltech.com/press-releases/hcltech-launches-gemini-enterprise-business-unit-accelerate-agentic-ai-adoption ,” Saxena said. “We are training different personas on the customer side to help them identify the right set of use cases and help them in rolling out Gemini Enterprise with our engineering model.” Working together, HCLTech and Google Cloud help enterprises ease deployment complexities and ensure a scalable path to becoming fully autonomous organizations. Agentic AI offers immense potential to redefine how work gets done, but success depends on careful planning and execution. By combining clear strategy, robust data foundations, and strong operational controls, organizations can move confidently toward a future where intelligent agents drive efficiency, innovation, and competitive advantage. Learn more about HCLTech’s approach to agentic AI and download a copy https://www.hcltech.com/agentic-ai of the enterprise AI market report.