116 VIEWPOINT The future of finance with agentic AI NILOY SENGUPTA: KYNDRYL Financial services organisations are preparing for a new era where agentic AI will drive digital transformation and redefine business operations “Financial institutions that do not embrace Agentic AI risk falling behind competitors” The financial services sector is often characterised by its rapid pace, wealth of data and demand for high-precision decision-making. The industry has long leveraged technological advancements to enhance efficiency, from early computational models to sophisticated algorithms. Now, agentic AI is emerging as the latest disruptor for business operations, and it promises a future where intelligent systems operate in partnership with organisations to provide unprecedented autonomy and adaptability. This technology goes beyond passive data retrieval and traditional automation, and moves towards autonomous, goal-orientated intelligence. Agentic AI systems are defined by their ability to perceive environments, reason through complex situations, create multistep plans and adapt independently to achieve objectives with minimal human supervision. A vast number of potential use cases for agentic AI have already been identified across the financial services landscape, with key areas including efficiency, productivity and customer experience. For instance, an increasing number of customers now expect personalised interactions with the services they use. Agentic AI can proactively analyse vast amounts of customer data – including spending patterns, life events and financial goals – to proactively recommend products and services when they are most relevant for the customer. This will not only prompt an increase in conversion rates, but also a reduction in customer support wait times. The financial sector is inherently exposed to a range of risks such as fraud, which is where agentic AI can also help. Agents can be deployed to continuously monitor transaction patterns in real time, perform continuous credit risk assessments, autonomously monitor financial markets and carry out other tasks. To successfully transition from the theoretical potential of agentic AI to practical implementation, organisations need to develop a structured, strategic approach. Ideally, the deployment will be carried out in phases to minimise potential risks and observe the return on investment in different areas. The first three to six months should be the foundation stage where the basic infrastructure is established. Organisations need to align AI initiatives with their overall business strategy, which will help them to maintain a clear vision of their digital transformation rather than deploy technology for the sake of it. During this stage, they will also need to ensure that their data infrastructure is unified, up to date and accessible so the AI model can use it effectively. In months six to 12, organisations can launch pilot tests to demonstrate the key areas of deployment. Once organisations are in the second year of implementation, they can shift
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