AI in tax doesn’t start with technology—it starts with clarity.
Connect with DMA to identify where AI can deliver real value in your tax function and chart a clear path forward.
Many tax departments are being told to implement AI into their tax function, but aren’t being given a clear path to do it. The result is a growing disconnect—tax teams understand their challenges but not the technology, while internal AI teams understand the technology but not tax processes. Closing that gap is quickly becoming one of the most valuable roles in the tax function.
The New Mandate: Implement AI in Tax
Executive leadership teams across large organizations, especially Fortune and Global 500 companies, are pushing for the adoption of AI, often with aggressive expectations around efficiency, automation, and cost savings. But inside the tax function, the reality looks very different:
- Tax teams are already stretched managing compliance, audits, and reporting
- AI initiatives are being prioritized at the enterprise level, not within tax
- Internal AI or IT teams are focused on broader operational use cases
- There’s little clarity on where AI actually fits within tax processes
The result? Tax departments are expected to adopt AI—but aren’t equipped to lead the effort.
Where Things Break Down
Most tax teams can quickly identify where automation would help:
- Managing high-volume tax inboxes
- Identifying anomalies in transaction data
- Improving use tax accrual accuracy
- Streamlining exemption certificate processes
- Supporting month-end close activities
The breakdown happens when those ideas need to be translated into something actionable. Tax teams may understand where AI could help, but often lack clarity on what’s realistically achievable, how to define requirements in a way AI teams can execute, how to prioritize use cases based on value, and even what data is needed—or whether that data is usable in its current state. At the same time, internal AI teams don’t have the tax context needed to design effective solutions. Without that alignment, projects stall, get deprioritized, or fail to deliver meaningful results.
Why Internal AI Teams Aren’t Solving This Issue (Yet)
Many organizations have invested heavily in AI centers of excellence. But those teams are typically focused on large-scale, enterprise-wide initiatives like supply chain optimization, customer analytics, and operational automation.
Tax rarely rises to the top of that list. And when it does, internal AI teams often need a well-defined use case, measurable business value, usable data, and significant input from tax personnel who already have full workloads. Without that foundation, projects often struggle to move beyond the planning stage. As a result, tax-related AI initiatives are frequently delayed or handed back to the business without a clear path forward.
The Need for a Different Kind of Tax Technology Partner
A different model is emerging. Many tax teams are being told that AI initiatives will be handled internally—that solutions should be developed in-house and aligned with broader enterprise-wide AI strategies. In theory, that approach makes sense. In practice, it often leaves tax teams responsible for driving initiatives they don’t have the time, technical expertise, or internal prioritization to execute on their own.
AI in tax doesn’t require a traditional technology implementation partner. It requires a partner that can bridge the gap between tax operations and AI execution by helping organizations:
- Identify practical AI opportunities within the tax function
- Translate tax challenges into executable use cases
- Align tax, AI, and technical stakeholders
- Support solution development and deployment
- Accelerate operational adoption and long-term value
In many ways, this mirrors the evolution of tax engine implementations. Organizations didn’t struggle because the technology didn’t work—they struggled because tax and IT weren’t aligned. AI is following the same pattern.
Operationalizing AI in Tax: The DMA Approach
Instead of forcing a one-size-fits-all solution, organizations are taking a more flexible, use-case-driven approach—and increasingly, they’re turning to DMA to help define and execute that strategy. DMA works directly with tax teams to move from idea to action, providing the structure, guidance, and translation needed to make AI initiatives viable within the tax function.
Start With the Problem, Not the Technology
DMA helps organizations clearly define the challenge, whether it’s inefficient inbox management, gaps in accrual accuracy, or manual review processes, so efforts are focused on real operational impact—not abstract AI concepts.
Bridge Tax and AI Teams
One of the most common challenges organizations face is translating tax requirements into something internal AI or IT teams can execute. DMA helps bridge that gap by aligning stakeholders, reducing rework, and accelerating progress.
Identify Viable AI Use Cases
Not everything needs AI. DMA works with clients to pinpoint where automation or machine learning can realistically deliver value, avoiding over-engineered solutions that never gain traction.
Support Solution Development and Deployment
Depending on internal capabilities and governance requirements, DMA may collaborate with internal AI teams, support solution development using approved enterprise technologies, or help accelerate deployment through proven tax-focused frameworks and automation solutions.
Build a Deployment Roadmap
From initial concept through execution, DMA helps outline how solutions will be developed, tested, and integrated—whether internally, externally, or through a hybrid model that aligns with the organization’s broader AI strategy.
Enable Long-term Scalability
Whether the goal is to transition ownership to internal teams or maintain ongoing support, DMA helps design solutions that can evolve with the organization and expand as new use cases emerge.
The DMA Approach in Action: Real-world Use Cases of AI in Tax
While every organization’s starting point is different, the underlying challenges and opportunities are often very similar. Below are examples of how DMA is helping companies move AI initiatives forward within the tax function:
Support Internal AI Teams With Accrual Analysis
A large multinational organization directed its tax team to build use tax accrual analysis capabilities internally using its AI center of excellence. The tax team had clear objectives but lacked a defined approach. DMA was brought in to help translate those requirements into executable use cases, define the data and logic needed for accurate determinations, and guide the internal AI team through development.
The result was a structured path forward that allowed the organization to keep development in-house while accelerating progress and improving accuracy.
Automate High-volume Tax Inbox Management
In another case, a company identified its general tax inbox as a major source of inefficiency, with significant time spent reviewing, routing, and responding to inquiries. Internal AI resources were limited and focused on higher-priority enterprise initiatives. DMA worked with the tax team to define the scope of automation, identify opportunities for classification and response generation, and build a roadmap that could be executed alongside internal teams.
This allowed the organization to move forward with automation without waiting for internal capacity to become available.
Define and Prioritize AI Use Cases for Tax Operations
A global organization with an established AI function was under pressure to justify any new initiative with measurable financial impact. Tax had several potential use cases—ranging from anomaly detection to certificate management—but no clear prioritization or quantified value. DMA helped evaluate each opportunity, define expected outcomes, and build the business case needed to secure internal support.
By aligning tax priorities with enterprise AI expectations, the organization was able to move forward with targeted initiatives that met both operational and financial requirements.
Accelerate Tax AI Deployment
A global organization had identified several AI opportunities within the tax function but struggled to move beyond planning and prioritization. Internal resources were focused on broader enterprise initiatives, leaving tax without a clear path to execution. DMA worked with the tax and technical teams to define requirements, support solution development efforts, and establish a deployment framework aligned with organizational standards.
This allowed the organization to move initiatives from concept to implementation while maintaining alignment with broader enterprise AI objectives.
This website content should be used for general informational purposes only, and not as a substitute for consultation with professional tax, legal, or other competent advisors.
Before making any decision or taking any action based upon information contained on this website, you should consult with a DMA professional.
Before making any decision or taking any action based upon information contained on this website, you should consult with a DMA professional.