AI-powered agents can navigate vast volumes of data, from indirect tax and value-added tax to R&D credits and transfer pricing assessments, autonomously gathering, analyzing and processing tax data to produce returns and compliance filings. Dramatically reducing the need for manual intervention means tax professionals may spend less time looking for information and more effort on strategic thinking and problem-solving top skills that 85% of the tax leaders surveyed say they value in future employees.
By ingesting project data and applying complex tax rules, tax bots can automatically extract fixed asset details, for example, analyze property tax obligations or assess eligibility for R&D credits, accelerating the tax return preparation with accuracy while uncovering tax savings manual processes might miss.
Real-world use cases are popping up in the M&M sector and businesses are starting to see where these agents may be helpful, moving beyond theoretical discussions to tangible results. Indirect tax functions, in particular, are at the forefront of adopting autonomous processes, with AI helping reduce costly errors and reverse audits.
As these technologies mature, autonomous tax returns will become the norm rather than the exception, enabling tax teams to focus on higher-value advisory roles.
Overcoming barriers
Despite the clear benefits, many M&M companies remain hesitant to fully embrace AI-driven tax transformation. Perceived risks around cost, regulatory compliance, data security and change management create inertia in sectors that have traditionally been slower to adopt new technologies.
But the landscape is changing. There is a growing precedent from tax and mining companies that have successfully built AI-ready data models and agentic tax flows. Companies no longer need to pioneer but instead can leverage recently paved trails and cloud-based solutions to manage their risk.
In keeping with the metaphor, transformation on this scale is akin to refurbishing a plane while in mid-air, with upgrades needing to be made without losing altitude or compromising safety and considering today’s needs while preparing for a new way of working. It’s a balancing act for certain, with cost pressures and demands from the C-suite to do more with less creating urgency.
And it’s not just more but focusing their efforts on differing priorities. Survey results indicate that internal tax personnel spend 53% of their time on routine tax activities and only 16% on specialized activities, with respondents preferring that routine activities be slashed by half (21%) and time spent on specialized activities doubled to 34%.
Tax functions are being asked to optimize, cut headcount and reduce costs while maintaining or improving their compliance and reporting quality. Whether starting now or holding off for better timing, doing so without a systemized, AI-enabled data layer will make meeting future expectations near impossible.
Accelerating integration
The good news is AI surpasses us in coding capability and excels at organizing and analyzing vast volumes of data with unparalleled efficiency. What would be a monumental effort in person-years is significantly easier and more efficient with AI, with the ability to make sophisticated data environments more accessible, streamlined and easier to stand up.
The time to act is now. Many M&M companies are effectively integrating AI across a range of use cases, marking a crucial shift from theoretical to tangible with real-world applications driven by business needs. By following their lead and applying standard models and AI tools to existing data, businesses can readily identify and bridge gaps for a more seamless integration, and work with cloud providers and databases to simplify the setup of underlying infrastructure.
Companies that delay may risk falling behind competitors that are already harnessing AI to automate tax processes, reduce errors and unlock new efficiencies. The regret of not having built a robust tax data foundation will only grow as autonomous tax technologies become mainstream.
