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What happens when AI-powered R&D claims meet AI-powered HMRC inspections?
We’ve reached a pivotal moment: businesses are increasingly using AI to prepare their R&D tax claims, while HMRC is under scrutiny for whether it uses AI to help decide which claims to challenge. A recent tribunal decision has pushed this issue into the spotlight, raising serious questions about transparency, fairness, and the future of compliance.
What we know from recent rulings, reports and industry articles
Tribunal ruling: The First-tier Tribunal has ordered HMRC to disclose whether it used AI in decisions to reject R&D tax credit claims. The court found that public interest in transparency outweighed HMRC’s argument that secrecy was needed to protect tax enforcement. At the time of writing HMRC is still to comply with the tribunal court and explain it's use of AI.
Taxpayer confidence: Legal and advisory commentators highlight risks around trust, due process, and fairness if HMRC does not clarify its use of automation.
Adviser use of AI: Industry articles describe how AI is already being used to draft narratives, extract technical details and align claims with HMRC’s Additional Information Form requirements and associated Guidelines.
Data protection: There are concerns about sensitive technical or commercially confidential R&D information being input into third-party AI tools.
Enquiry environment: Surveys and industry reports show enquiry rates have risen, with HMRC devoting more resources to scrutinising claims and taking a more agressive approach.
Could AI turn claiming UK R&D incentives into an "arms-race"?
It's clear that AI is aleady transforming how R&D tax claims are prepared, because businesses and advisers are increasingly using AI driven tools to:
Draft narratives aligned with R&D Guildelines and the online Additional Information form.
Extract technical details from project documentation, lab notes, or software repositories, saving time and reducing human error.
Model costs and apportionment by analysing time logs, payroll data, or expenditure patterns, highlighting potential qualifying costs quickly.
Used responsibly, these tools raise claim quality by making processes more systematic and reducing the risk of omissions.
At the same time, HMRC may be deploying its own AI-driven systems to screen and prioritise claims for enquiry. These might analyse submission patterns, flag anomalies against sector norms, or detect linguistic signals in narratives that suggest templating or generic responses. While this can help HMRC focus resources on the riskiest claims, it also opens the door to false positives if unusual but legitimate R&D activity looks statistically abnormal.
That sets up a potential arms-race scenario:
On one side, claimants refine submissions to satisfy machine-driven filters.
On the other, HMRC adapts its algorithms to detect such optimisation.
The result? Faster processing overall, but also the danger that genuine innovation is flagged incorrectly, leading to more enquiries and decisions that are hard to challenge because the reasoning is embedded in opaque algorithms. This risks eroding trust in the system — both for businesses making claims and for HMRC caseworkers tasked with explaining why an AI-flagged claim deserves further scrutiny.
Best practice for claimants and advisers:
Always keep human oversight and sign-off alongside AI drafting.
Maintain an auditable trail of prompts, drafts, and revisions — if HMRC questions whether AI was used, transparency will matter.
Stress-test claims against known enquiry triggers such as large year-on-year jumps or unusual cost allocations.
Policy and enforcement implications for HMRC:
HMRC should publish high-level transparency standards about the use of automation in compliance.
Any enforcement AI should be explainable and auditable, with safeguards against error amplification.
Training and upskilling for both HMRC caseworkers and advisers is essential to catch errors that automated systems miss.
The bottom line for AI in R&D claims and Inspections
AI can make R&D claims more consistent and HMRC inspections more efficient. But it can also make the interaction brittle if models are treated as unquestionable authorities. The tribunal’s demand that HMRC disclose its use of AI is a watershed moment: it shows that transparency is not optional, it’s the foundation of trust.
For businesses and advisers, the challenge is clear: embrace AI where it improves quality and efficiency, but always pair it with human judgement, proper documentation and readiness to explain both the content of a claim and the role AI played in creating it.
Get insights into all the key aspects of claiming R&D tax relief and RDEC.
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