Agentic AI: Autonomous Generative AI agents
Agentic AI is defining a new era of intelligent and autonomous systems revolutionizing the way businesses operate. By harnessing the power of Generative AI (GenAI) and advanced language models, Agentic AI has moved beyond the simple task of automation to become a decision-maker that plans, orchestrates, and executes the entire workflow. Deloitte predicts that in 2025, 25% of companies that use GenAI will launch Agentic AI pilots or proofs of concept, growing to 50% in 2027.
Multiagent systems will redefine the future of work
Multiagent systems comprise of multiple AI agents working in tandem to tackle complex workflows by strategising, coordinating, and implementing independently. Deloitte enables organizations to deploy multiple, role-specific AI agents to understand requests, plan workflows, coordinate role-specific agents, streamline actions, collaborate with humans and validate outputs. It makes complex decisions in real-time, eliminating inefficiencies and streamlining workflows, for faster decision-making, better efficiency, and more agile business operations.
With its tendency to evolve over time, Agentic AI can adapt to changing business needs, ensuring that it remains effective and aligned with organisational goals. In addition to being effective and repeatable, AI agent-powered approach is fast, cost-effective and scalable.
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Adopting a strategic approach is crucial for Agentic success. Organisations must consideration six key things – identifying right use cases, ensuring tech ecosystem readiness, defining and measuring success of Agentic AI interventions, scaling and sustaining use cases, empowering employees to thrive alongside AI agents and finally deploying it responsibly.
Organisations must take structured approaches for selecting business processes for agentic transformation as per organisational needs and maturity levels. First approach is to qualify existing use cases if they are good candidates for Agentic AI and second is prioritising already existing use cases based on impact, ease of implementation and differentiability.
Building the right technical foundation today enables organisations to unlock the true potential of Agentic AI tomorrow. From preparing themselves in terms of establishing a data and AI foundation layer to ensuring seamless interoperability across systems, every step lays the groundwork for a scalable, sustainable and future-ready Agentic AI ecosystem.
This chapter presents simple framework for identifying the right measures of success, monitoring performance at every step and using results to guide decisions and actions consistently across the business.
This chapter covers how the right architecture, operating model and talent strategy help organisations strategically move agentic AI initiatives from experimentation to scaling. When these come together, it unlocks speed, scale and enables smarter decisions to shape outcomes that matter.
AI agents are no longer confined to experimental pilots. They are becoming embedded across enterprise workflows, acting as digital teammates that reason, decide and act. This chapter covers the organisational imperatives and skillsets for empowering a smooth human-agent interaction for long term success in agentic era.
This chapter looks at the six questions covered earlier through a lens of responsibility and guardrails, outlining risk landscape specific to agentic AI and translating responsible AI principles into concrete design patterns, controls and governance mechanisms suitable for enterprise deployment.
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