Q2 2026 R&D Tax Credit Best Practice Roundtable

Here’s what you need to know:

• AI is changing the R&D process—not the qualification rules.
  AI can dramatically improve documentation, analysis, and efficiency, but companies must still prove technical uncertainty, experimentation, and qualified activities under the same IRS standards.
• Documentation is more important than ever.
  The IRS continues to focus on substantiation, business component identification, and statistical sampling. Organizations should build documentation that can withstand an audit—not just satisfy annual compliance.
• Human oversight remains essential.
  AI should support the R&D study, not make qualification decisions. Tax professionals must review, validate, and own the conclusions to avoid “black box” risks during an examination.
• Data has become a strategic asset for R&D credits.
  Systems like JIRA, Microsoft Teams, Slack, calendars, and other collaboration platforms provide contemporaneous evidence that is often more reliable than traditional SME interviews. Organizations that capture this data early gain stronger audit support.
• R&D is expanding beyond engineering.
  AI is enabling product managers, analysts, and other business functions to contribute to innovation. Companies should ensure their R&D credit process identifies qualified activities across the organization—not just within engineering teams.
• The best-performing organizations combine AI with strong governance.
  Leading tax departments are embedding AI into their workflows while maintaining clear policies, executive oversight, and audit-ready documentation. AI delivers the greatest value when paired with disciplined processes—not used as a replacement for them