How AI agents will revolutionise business operations

The past couple of years have seen businesses transform significantly through Generative Artficial Intelligence (GenAI). While GenAI is projected to significantly impact India's GDP, potentially adding between $359 billion to $438 billion by 2029-30, the next phase of transformation has already begun with the emergence of AI agents. This shift promises to establish new levels of efficiency, human-machine collaboration, and technical capabilities never seen before.

Understanding AI Agents

AI agents are goal- and action-oriented systems capable of autonomously making nuanced decisions, executing complex tasks, and handling end-to-end processes with minimal human intervention. They build upon RPA and AI technologies businesses currently use. Large Language Models (LLMs) provide the foundation for natural language understanding, enabling AI agents to interpret complex instructions, engage in meaningful and intuitive conversations, and generate creative output. Unlike GenAI, which requires extensive programming and manual updates, agents evolve through continuous learning and adaptation.

By integrating agents into their operations, companies can move beyond traditional automation to achieve sophisticated, context-aware solutions. So, while GenAI focuses on creating new content, AI agents autonomously analyse data, identify patterns, formulate strategies, make decisions, and implement them to meet pre-defined objectives. This gives users more time to focus on higher-level tasks. In tandem, these two technologies can create powerful solutions that combine creativity with action.

Transforming Industries through Actions

By powering agents to perform complex tasks, AI expands the scope of what can be automated. For example, in the insurance industry, agents can automate the entire claims process, from initial filing to final payout, resulting in faster processing times, reduced errors, and improved customer experience. It also significantly improves the quality of interactions between humans and agents, revolutionising customer service. So, while agents handle inquiries, offer tailored solutions, and process transactions, human representatives can focus on more value-added tasks.

In the financial sector, AI agents can analyse market trends, assess investment opportunities, proactively manage risk, and create personalised financial plans for individual clients. This frees financial advisors from data-heavy analysis, allowing them to focus on building relationships and offering strategic guidance. When it comes to the healthcare industry, agents can recommend personalised treatment plans based on each patient's unique needs and medical history. Agents can accelerate drug discovery and development as they swiftly analyse extensive datasets, identify potential drug targets, and predict their efficacy.

How Can Businesses Prepare for the Agentic Era?

To ensure measurable outcomes with active governance, businesses need to focus on an orchestrated agentic ecosystem that integrates agents, humans, and robots into cohesive workflows. Orchestration is all about action and results. So, while humans or agents make decisions, either humans or robots can act on them. It is the key to accelerating AI agents’ adoption as it will support a multitude of agents and integrate their actions into seamless workflows. Without orchestration, vibrant agentic infrastructures and controls, agents won’t scale effectively.

This evolution is not limited to developers. With the advent of low-code tools and basic prompts, even non-technical users can now develop agents for internal use cases. This democratisation of AI technology allows multiple processes to be streamlined through AI agents, helping businesses reach the market faster.

Despite its transformative potential, the adoption of agents is not without challenges. AI agents will primarily derive context from the company’s internal information. However, before the data can be utilised, it must be securely stored, moderated, and governed by appropriate frameworks. Training agents with accurate and secure data will be crucial for risk management and avoiding potential bias by AI.

Companies must also focus on investing in upskilling initiatives and can start with pilot projects in non-critical areas. Both the AI systems and the people working with them will need to change and learn as the technology changes. A human-in-the-loop approach will remain crucial, especially for critical decision-making. Managing and measuring the performance of various AI agents will be a complex task. It involves not only identifying the right metrics to monitor but also setting appropriate expectations for the agents. For example, an agent might process over 200 insurance claims in a week, but it's equally important for employees to assess whether this enhanced customer experience.

The future is both agentic and robotic, where agents serve as the digital brains and robots act as the digital arms and legs. Businesses must ensure that AI and automation go hand in hand to achieve success and truly shape the tech landscape. In the coming months, the momentum around agents will only intensify. A study predicts that the agents' market will grow from $5.1 billion in 2024 to $47.1 billion by 2030. This next wave of AI is poised to transform industries, driving progress not just through visionary ideas but through decisive action.

Arun Balasubramanian

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Arun Balasubramanian is Vice President and Managing Director India and South Asia at UiPath.