PodChats for FutureCFO: Finance Efficiency: Is Agentic AI the Answer?

While traditional automation and GenAI are making inroads in 2025, Southeast Asian CFOs face persistent efficiency challenges demanding more sophisticated solutions. 

Agentic AI emerges as a promising, albeit complex, answer by enabling autonomous execution of intricate finance workflows.

Its potential lies not just in incremental efficiency gains, but in fundamentally reshaping the finance function's operating model towards greater speed, accuracy, and strategic focus. Success hinges on overcoming significant data, governance, and talent challenges.

In this PodChats for FutureCFO, Nikhil Parambath, Regional Vice President, Asia, BlackLine, offers his thoughts and some suggestions for senior finance leaders looking to step out of the shadows of AI and into the real-world possibilities of Agentic AI as applied within the finance function.

Nikhil, welcome to PodChats for FutureCFO

1.       Which specific finance processes (e.g., closing, reconciliation, reporting, compliance) still represent the biggest bottlenecks to efficiency and strategic agility within the finance function in Asia in 2025?

2.       Where have traditional automation tools (like RPA) fallen short in delivering the transformative efficiency gains finance needs, particularly in our complex, diverse SEA operating environments?

3.       From your observation, how would you assess finance leaders in Southeast Asia in terms of their understanding of AI, Generative AI and Agentic AI (framed in the context of 2025)?

4.       For SEA finance leaders prioritising efficiency in 2026, what are the 1-2 most compelling, near-term practical applications of Agentic AI within core finance operations (e.g., dynamic forecasting, intelligent reconciliation, autonomous fraud detection)?

5.       What foundational data governance and integration challenges must SEA finance functions urgently address now to be ready to leverage this technology effectively in 2026?

6.       As AI agents potentially execute multi-step processes autonomously, how should finance leaders rethink internal controls, audit trails, and human oversight mechanisms to ensure accuracy, compliance, and ethical operation?

7.       How can Agentic AI agents be practically integrated with existing ERP systems, legacy platforms, and other best-of-breed finance applications common across SEA businesses without creating untenable complexity or risks?

8.       If Agentic AI takes over complex operational execution, how must the skillset and role of the finance professional evolve in 2026? What does "strategic business partnering" look like in this context, and how do we upskill our SEA teams?

9.       Traditional cost savings aside, what new metrics should CFOs use to evaluate the true efficiency and strategic value delivered by Agentic AI implementations within the finance function in 2026 (e.g., speed to insight, reduction in manual intervention points, improved forecast accuracy)?

10.   Finally, any recommendations for how should SEA finance leaders strike the optimal balance for 2026 and beyond?