By Rajan Padmanabhan, AVP, Unit Technology Officer, Data Analytics and AI, Infosys
Enterprises, for the past decade, have leaned significantly into AI-powered intelligent automation. This is now clearly evolving into an emerging era defined by agentic AI driving value for enterprise transformation. Agentic AI for enterprise, at its core, is intelligent systems marked by their ability to drive autonomous decision-making, reasoning, and adaptive action. These systems integrate reasoning with continuous learning, enabling them to navigate complex scenarios, make appropriate contextual decisions, and act without constant human involvement.
This is starting to fundamentally redefine how organizations not only operate, but also their fitness for market. From improved operations, supply chain optimization based on anticipation of potential disruptions before they occur, to customer service systems that autonomously resolve issues, and planning tools that model scenarios and recommend action plans, the transformation is profound.
AI-amplified Humans. And Human-amplified AI.
The value of agentic AI lies in its ability to augment human judgment. By processing vast streams of information, identifying otherwise hidden patterns, and executing decisions at scale, agentic AI allows human talent to focus on problem finding and framing, strategy plotting, creative problem-solving, and critical relationship building. While AI handles the cognitive load, humans can expand contextual wisdom, provide ethical guidance, and shape the strategic pathways. This makes organizations simultaneously more efficient and more human-centric.
There is, however, the dimension of accountability as AI systems gain autonomy. When an agentic system decides on a course of action, who bears responsibility for outcomes? How do we ensure these decisions align with organizational values and even societal norms? How do we maintain transparency in decision-making processes that may involve several layers of complexities in reasoning? We need human-led governance frameworks to address these questions. Organizations need robust mechanisms for oversight, unambiguous accountability structures, and ethical guardrails that can contain AI behavior from design through deployment. While the regulatory landscape evolves, making proactive ethical leadership is essential for enterprises that adopt agentic AI.
A Framework for Transformation
The most successful implementations of agentic AI follow a humans amplifying AI and AI amplifying humans philosophy anchored in making bottom-up micro-changes that are incremental, people-centric and ensures seamless integration with minimal friction.
This begins with the Plus 1 principle: Identify repetitive tasks in everyday workflows and introduce AI to handle them along with one additional step. For example, using an AI assistant to summarize meeting notes, then gradually draft follow-up emails with AI and eventually lean on AI for engagement strategies. This helps grow and build trust and functional competence gradually and organically.
Persona-specific AI assistants prove far more effective than generic solutions. For example, a marketer needs different capabilities than a sales representative or a finance manager. Tailored assistants that understand function-specific context, lexicon, and workflows integrate easily into existing playbooks rather than forcing adaptation to fit-all tools.
Targeted Micro Processes drive meaningful results. Rather than pursuing broad transformation initiatives, successful organizations identify high-impact, low-risk scenarios—expense report processing, routine customer inquiries, financial reconciliation,market research—where agentic AI can deliver immediate value while teams build familiarity and confidence.
Crucially, transformation requires continuous upskilling. Teams need more than tools related training. They need a deeper grasp of their own capabilities, limitations, and patterns of collaboration and communication. Making this learning investment will make sure that AI amplifies rather than alienates people.
Transparent governance establishes trust. Clear policies on AI decision-making authority, human oversight requirements, and escalation procedures create psychological safety. When employees understand how AI systems work and where humans retain control, adoption accelerates.
Finally, people need to feel heard. Users need forums to report issues, suggest improvements, and share success stories. Instituting these platforms creates a virtuous cycle of refinement while fostering ownership, engagement and better management.
Agentic AI has brought us all to an important inflection point in enterprise transformation. It has the potential to set right the AI pilot purgatory that has quickly scaled but, for the most part, failed to create sustainable enterprise value or competitive advantage. This is because implementing AI agents require more than to be simply plugging them into existing workflows. They call for those workflows to be reimagined and relaid with agents at the heart of it all.
The systems for strategic governance need to come with it. The enterprise will need to recast itself to go from dispersed initiatives to strategic programs, from use cases to real business impact, and from siloed efforts to unified cross-functional centralized change making. The agents can then supercharge operational agility and create substantial new revenue opportunities.
The need of the hour will also be drive adoption while earning and keeping employee trust. The right governance to manage agent autonomy with human wisdom and discretion will be key. Enterprises that navigate this transformation thoughtfully will gain unprecedented strategic agility, operational excellence, and competitive edge.