In a recent interview, Johnson Idesoh, Absa’s Group Chief Information and Technology Officer, discussed the evolution of artificial intelligence (AI) with a particular focus on the emerging concept of “Agentic AI.” This new category of AI differs from traditional generative models like OpenAI’s ChatGPT in that it can autonomously solve complex problems without requiring continuous input from users.
Agentic AI is envisioned as a network of autonomous agents capable of taking purposeful actions based on a deep understanding of their context, thus blurring the lines between human decision-making and machine capabilities. This shift was a key topic at the 2025 World Economic Forum in Davos, where leaders considered the implications of entering what is termed the ‘Intelligent Age.’
One area where Agentic AI could have a significant transformative impact is in the financial services sector. While existing automation and predictive analytics have led to incremental improvements, they often necessitate human intervention. In contrast, Agentic AI can execute complex workflows, learn from real-time data, and initiate multi-layered actions independently. For instance, instead of merely flagging irregularities, an Agentic AI could autonomously quarantine suspect transactions and notify relevant parties, revolutionizing compliance, fraud detection, and liquidity management.
Moreover, the technology promises to integrate siloed operations across various functions within financial institutions, facilitating synchronized decision-making. For example, it can enhance stress testing by adapting simulations dynamically based on live data inputs. In customer interactions, Agentic AI could shift the traditional reactive model to a proactive approach, enabling institutions to anticipate and meet client needs before requests are made.
Despite its potential, the adoption of Agentic AI raises important challenges and ethical considerations. Issues such as accountability, the risk of discrimination, and the alignment with institutional missions warrant careful examination. As these systems take on more roles traditionally held by human workers, a collaborative model where humans and machines enhance each other’s strengths is imperative.
Idesoh concluded that rather than rendering systems like ChatGPT obsolete, the evolution to Agentic AI represents an opportunity for growth and adaptation, underscoring a vision for a future where AI serves to complement human roles rather than replace them. The potential for Agentic AI to redefine operational frameworks and improve human-technology interactions in various industries, particularly finance, is significant and warrants ongoing exploration.
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