‘First published on India Business Law Journal’
By: Dr. Ajai Garg and Subroto Kumar Panda
Business has always been about risk, the balance between success and a failure of the enterprise. However, the latest product of the fifth industrial revolution may either be the greatest boon to humanity ever known or the end of commercial life as it is presently understood. The problem is that no-one knows which it will be.
The launch of ChatGPT by OpenAI in 2022 forced artificial intelligence (AI) to the forefront of commerce and everyday existence in a way no tool has done before. AI-related companies now dominate stock markets as investors clamour to be part of the unprecedented expansion of the industry. The rush to build the data centres necessary to feed the AI behemoth will likely see spending on construction balloon to more than USD1.4 trillion between 2024 and 2027. It has also raised fears that such centres will deprive cities and regions of electricity and water as they power up and then have to be cooled.
Bridging AI hype and value
The problem for end users of all kinds is knowing how to use this new technology. At the same time, they must invest time and funds in re-engineering and retraining. Some are further ahead in meeting the challenge than others. A fifth of information-technology companies say they are using AI. Economy-wide, however, only 5% of businesses acknowledge using it in their processes. The perception gap between investor enthusiasm and business reality seems unsustainable. Agentic AI systems, capable of planning and executing more complex tasks, may be the answer to producing value from this technology.
AI agents are able to execute complex tasks autonomously, take decisions and adapt to specific requirements. They can interact with other AI agents, all without human monitoring. This improves the scale, productivity and efficiency of businesses, making the technology viable in key sectors such as manufacturing, retail, health care, fintech, agriculture and travel and logistics. With such capabilities, AI agents turn passive tools into proactive teammates. The real breakthrough is in vertical processes, in which agentic AI automates complex business workflows involving many steps and systems. They supercharge operational agility and unlock new revenue streams.
AI agents transforming operations with data
In operations processing, agents carry out routine, data-intensive tasks, thereby enabling humans to focus on higher-value work. However, they go further, transforming processes, reducing delays and adapting products to individual requirements. For example, an agent may rearrange deliveries without human intervention in response to weather-related disruptions or material shortages. However, ensuring that an AI agent can process problems requires context. Data provides such context and an understanding of the business through collaboration and the bridging of specialisations.
To forecast costs accurately, manufacturers must understand their supply chains. Suppliers, material expenses and transport all affect costs. AI agents can consider these factors in real time, while data from sensors on machines and components predict the effect of repairs and production outages. This allows agents to keep customers informed about delivery status and delays, and to provide compensation if need be.
Agentic AI: Data, risk and regulation
Agentic AI is still developing and there are challenges. AI agents are only as powerful as the data with which they are provided. Organisations must give agents access to high-quality, timely and unified data. Practical goal setting is as crucial for agentic AI as it is for a traditional workforce. Agents may make mistakes, particularly as their algorithms get up to speed. Procedural guardrails will mitigate risks. As AI agents replace humans the biggest challenge for regulators will be to distinguish AI agent-created outcomes to those produced by humans.
Agentic AI appears to be something out of science fiction. AI that works and acts independently to perform routine and complex tasks may seem far-fetched. However, if correctly implemented, its benefits will soon become all too real. The speed at which AI agents have been employed throughout various work environments has accelerated during the past year. A survey reveals that 79% of companies are using agentic AI. Although many entities have invested in AI without seeing immediate bottom-line benefits, agentic AI promises significant productivity gains that fuel increasing commercial adoption.
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