Hendersen

What we cover

AI Integration

Embedding AI agents into in-house tax workflows.

  • AI workflow design
  • Tool evaluation & selection
  • Compliance review
  • Internal capability building

AI Integration Services

Where AI actually pays back in the tax function

Within the tax function, the productive use of AI is narrower than the generalist literature suggests and the failure modes are specific. Document-heavy processes — invoice classification, contract review for VAT/IIT/withholding triggers, transfer pricing documentation drafting, ledger reconciliation — are where we see measurable cycle-time reduction. Generative work that produces a tax position or a number continues to require review by a qualified professional, and the workflow integration is where most implementations stumble. We work with tax teams on the realistic deployment.

Our services

Opportunity assessment

We begin with a process walkthrough of the in-house tax function — compliance, advisory, TP, controversy — and identify the points where AI assistants can remove cycle-time without compromising defensibility. The output is a short list of high-confidence use cases, sized in hours saved and risk-adjusted, with a sequencing proposal.

Vendor and architecture selection

We advise on the build-versus-buy decision, on the data residency and confidentiality requirements that flow from the nature of the documents involved, and on the integration patterns that fit the existing tax technology stack. We do not sell AI software; we help the client choose.

Implementation support

We work alongside the in-house tax team and the technology partner during the implementation: defining the prompt templates, the validation rules, the escalation paths, and the audit trail. The objective is a system that a tax professional can rely on for the day-to-day and that the audit committee can defend on review.

Governance and oversight

Tax regulators in China and elsewhere are publishing guidance on the use of AI in regulated processes. We help the client build the internal governance — the model-risk policy, the output-review controls, the human-in-the-loop requirements — that satisfies the existing rules and is robust to the next round.

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