Tania Segovia Tornero: Tax teams are increasingly asked to do more with less. On top of meeting the compliance requirements imposed by local tax authorities, they need to meet the requirements of the digital tax agenda.
Tania Segovia Tornero: But at the same time, they are being asked by the business to reduce costs and drive efficiencies. I am very happy to be discussing with my colleagues about Agentic AI.
Tania Segovia Tornero: How is Agentic AI helping and impacting tax functions already today?
Chris Rogers: It’s already having an impact on tax functions and it's quite exciting.
Chris Rogers: What's been interesting over the last many years is that evolution of AI from traditional rule-based systems to machine learning, large language models, and now agentic AI.
Chris Rogers: So I see it as very much part of a continuation of the journey.
Chris Rogers: What's particularly interesting about agentic AI is the ability to chain different elements together, enabling end-to-end tax processes.
Chris Rogers: This allows identification of tax leakage, optimisation opportunities, and broader deployment across transaction planning.
Chris Rogers: This broadens the opportunity to deploy AI within the tax function and enables professionals to focus on higher value-add activities.
Tania Segovia Tornero: Amar, anything to add on this one?
Amar Thakrar: The impact of agentic AI has been pretty positive.
Amar Thakrar: When I was a kid, although I didn't dream of working in tax, I wanted to do something meaningful, and tax gave me that opportunity.
Amar Thakrar: Systems, processes and data sometimes got in the way, taking time away from interpretation and value-add work.
Amar Thakrar: Agentic AI has taken over that burden, allowing professionals to focus on the intellectual part of their roles.
Amar Thakrar: Some professionals need more support as processes change, and change management is becoming increasingly important.
Tania Segovia Tornero: I think this is really interesting.
Tania Segovia Tornero: I would like to explore more about the specific AI use cases that agentic AI can bring into the tax team.
Tania Segovia Tornero: John, do you want to pick up this one?
John Georgiou: The AI journey started with transactional processing and evolved into document production and tax research using generative AI.
John Georgiou: Agentic AI allows discrete activities to be chained together, for example in transfer pricing processes.
Chris Rogers: The global element is important. Agentic AI allows standardisation across territories while supporting local-specific needs.
Tania Segovia Tornero: The opportunity to implement agentic AI is amazing, but there are also risks and challenges.
Tania Segovia Tornero: John, could you talk us through the challenges of agentic AI adoption?
John Georgiou: One challenge is identifying the right use cases and building a strong business case.
John Georgiou: Another emerging challenge is AI governance, which tax authorities and auditors will increasingly expect.
Tania Segovia Tornero: How will the future tax function be shaped by agentic AI?
Amar Thakrar: Tax authorities will increasingly embrace agentic AI, which will influence how the tax community operates.
Amar Thakrar: This will shift tax work upstream toward data quality, governance, and real-time interaction.
Tania Segovia Tornero: Anything to add, Chris?
Chris Rogers: Skills within the tax function will change significantly, with data and AI literacy becoming critical.
Chris Rogers: The relationship with advisors will also evolve, particularly around AI governance.
Tania Segovia Tornero: Thank you very much. It was really helpful and insightful to hear from you today.
