Innovation in action: Jason Marx on agentic AI, firm intelligence, and the global future of tax & accounting

 

Accounting is undergoing a major shift in how work gets done as artificial intelligence becomes a business-critical tool. In this Q&A, Jason Marx, CEO of Wolters Kluwer Tax & Accounting, shares how the company is leading this transformation through Firm Intelligence, its global strategy that integrates responsible AI, expert content, and connected platforms to help professionals work more efficiently and deliver greater value.

AI is reshaping how tax and accounting work gets done. What impact is this having on the profession, and how are firms evolving to take advantage of it?

We’ve entered a new era of AI, one in which systems can do more than generate an answer. Agentic AI can interpret an objective, plan and coordinate multiple steps, use the appropriate data and tools, take permitted actions, and return work to a professional for review at defined points. In tax and accounting, that matters because the work is not a single prompt. It is a connected process shaped by deadlines, source documents, tax law, firm policies, review standards, and professional judgment.

Across the profession, we’re seeing three major shifts:

• Embedded and connected intelligence. Professionals do not want another disconnected tool. They want intelligence inside the systems where they collect documents, research issues, prepare returns, review work, manage engagements, and advise clients.
  
  
• Transparency, trust, and expert oversight. In a regulated profession, a plausible answer is not enough. Professionals need AI grounded in trusted content, with visible sources, reviewable outputs, and expert-in-the-loop oversight, so that professional judgment and accountability remain central.
  
  
• The rise of the hybrid professional. Tax and accounting professionals are combining technical knowledge, data fluency, critical thinking, and client skills. AI can reduce the time spent assembling information, while professionals apply judgment, investigate exceptions, communicate implications, and advise clients.

The goal is not to remove the expert from the work. It is to redesign the work so that technology carries more of the routine tasks, and professionals can devote more attention to judgment, client outcomes and the decisions that matter.

What makes Wolters Kluwer Tax & Accounting’s AI strategy different?

Our approach starts with the professional workflow, not the model. Agentic AI refers to technology that can coordinate and act across multiple steps. Wolters Kluwer Expert AI is how we bring those capabilities into professional work, grounded in trusted content and domain expertise, embedding them within the CCH portfolio, and applying expert-in-the-loop governance so that professionals remain in control of the outcome.

That approach rests on three strengths:

• Domain expertise. Our capabilities draw on expert-curated content, tax logic, and professional context, so outputs are relevant to high-stakes work and can be evaluated by a qualified professional.
  
  
• End-to-end integration. Intelligence is built into the CCH environments customers already use. Data, documents, research, and workflow context can work together instead of forcing professionals to move information among disconnected tools.
  
  
• Global scale, local precision. Tax and accounting requirements vary by jurisdiction, language, and practice. Our global portfolio is developed to address local regulatory and professional needs while applying consistent principles for security, governance, and responsible AI.

The difference is not simply that AI can respond. It is that the intelligence is connected to the content, data, controls, and workflow required to help a professional complete and defend the work.

What AI innovations are firms seeing from Wolters Kluwer Tax & Accounting today, and what’s next?

We’re bringing Expert AI into the tax workflow, from document intake and research through preparation, review, and advisory. CCH Axcess Scan uses agentic capabilities to classify documents, extract information, and map it into the return. CCH Axcess Intelligence connects firm documents and tax-return context with authoritative CCH content, helping professionals research, analyze, and review work with visible sources. CCH Axcess Advisor uses existing tax data and trusted content to identify and prioritize advisory opportunities and guide consistent service delivery.

Together, these capabilities reduce the time professionals spend gathering and moving information, giving them a stronger starting point for review, judgment, and client service. Professionals remain responsible for the outcome, with Expert AI supporting them inside the systems they already use.

What can firm leaders do now to prepare for what’s next?
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Firms will gain more from AI when they connect it to how work is designed, how talent develops, and how value is delivered to clients. I would encourage leaders to ask five questions:

Is our technology improving the professional’s starting point?

Efficiency matters, but the larger opportunity is to give professionals a stronger starting point by surfacing the right information, source material, exception, or recommendation when judgment is required. Measure progress by whether the workflow reduces rework, strengthens review, and supports more consistent client outcomes.

Where is our talent spending time, and what’s that time worth?

Map the work that consumes professional capacity. Determine what should be automated, delegated, redesigned, or removed, and then intentionally redirect time toward complex analysis, review, client communication, and advisory work.

Are your people prepared for new roles, not just new tools?

AI adoption changes how people learn. If entry-level professionals spend less time on repetitive preparation, firms must create new ways for them to build technical depth. That can include reviewing AI-assisted work, investigating exceptions, tracing conclusions to authoritative sources, participating in client conversations, and learning how experienced professionals apply judgment.

How are we redesigning career paths?

Traditional development models often relied on years of repetition before professionals gained exposure to analysis and client work. Firms can now bring those experiences forward, but they must do so deliberately. Early-career professionals need structured opportunities to build critical thinking, tax research, data literacy, communication, problem solving, and relationship-management skills. Managers will need to become coaches of judgment and reviewers of both human and AI-assisted work. Senior professionals can extend their expertise across more engagements without becoming the bottleneck in every process.

Do we have the governance needed to scale responsibly?

Leaders need clarity about approved use cases, data access, review points, decision rights, documentation, escalation, and accountability. Agentic AI should operate within permissions and controls that reflect the risk of the task. The more consequential the decision, the stronger the requirements must be for visible sources, professional review, and clear ownership..

This moment is an opportunity to make the profession more attractive as well as more productive. When technology reduces low-value friction, people can engage in meaningful work earlier, see a clearer connection between their efforts and client outcomes, and build careers that combine technical mastery with human judgment and trusted relationships.

That is the promise of intelligent professional work: connected systems, embedded insight, and technology that strengthens rather than replaces professional judgement. The firms that lead will use AI to expand expertise, improve decisions, develop people, and deliver greater client value with confidence.