From Control to Intelligence in Regulatory Reporting

The Agentic Gap is Regnology’s AI readiness snapshot of regulatory reporting in 2026.

Based on feedback from 276 practitioners across 22 countries, with a large majority inside financial institutions, it reveals that regulatory reporting has reached a tipping point: while 71% of organizations are either exploring or piloting AI, only 16% describe AI as embedded in operations.

Scale buys experimentation, not adoption. The gap that matters lies between piloting a use case and trusting AI in the reporting cycle, and not by the size of the institution.

What our research shows

Provides citable benchmarks from the 2026 snapshot - framed for leaders diagnosing where experimentation ends and trusted use begins. 

  • Large institutions lead AI pilots but not embedded use. The largest institutions lead on piloting at 49%, yet sit at around 8% embedded - broadly in line with every other size band, where embedded use remains flat at roughly 8–15%.
  • The gap that matters is pilot to trust. Activity is not the same as adoption. Understanding where a use case falls between experimentation and reliance within the reporting cycle is the first step toward closing the agentic gap.
  • Modernization sets the context for AI. Regulatory reporting modernization leads departmental priorities at 77%; AI adoption itself ranks at 29%. AI is considered in the service of problems institutions are already working to solve.
  • Investment clusters around analysis and workflow. Data analysis (66%) and workflow automation (49%) lead AI priorities; compliance reporting and risk management rise with maturity.
  • Economics favor targeted agentic work. Running the reporting process absorbs roughly 30–50% of reporting spend. Technology accounts for about 40%, much of it shared infrastructure rather than removing manual steps. Illustrative Tier 1 case studies suggest roughly 15–25% of spend could be addressable by agentic workflows.*

*Directional estimate from Oliver Wyman research commissioned by Regnology, based on illustrative Tier 1 case studies.

Inside the report 

The report outlines a practical approach to guides organizations from maturity diagnosis to governed production, addressing several critical areas: 

  • 01

    Where financial institutions stand today

    Adoption stages from exploratory through piloting to embedded — and why the meaningful gap lies from pilot to trusted use, not by institutional size.

  • 02

    What’s driving AI investment

    How modernization, data quality, and economics shape where AI attention is concentrated in the reporting value chain.

  • 03

    Where the barriers remain

    Explainability, auditability, domain translation, supervisory expectations, plus the data and governance foundations that must precede automation.

  • 04

    How institutions can move the needle

    A value-versus-readiness framework, principles for matching authority to workflow, and a path from pilot to production.

FAQs

What is the agentic gap in regulatory reporting?

The agentic gap is the distance between piloting a use case and trusting it inside the reporting cycle, not the distance between large institutions and small ones. Scale buys experimentation; trust is earned separately, through governed and auditable workflows that keep accountability with people.

Do larger institutions lead on AI adoption in regulatory reporting?

They lead on experimentation, not on embedded use. Among the largest institutions, 49% are piloting AI, yet embedded use sits at around 8% — broadly in line with other size bands, where embedded use remains flat at roughly 8–15% across every tier.

What share of reporting spend could agentic AI address?

Regnology's research estimates that roughly 15–25% of regulatory reporting spend could be addressable by agentic workflows, concentrated where manual effort remains substantial across a small number of high-value activities.

Who should read this report?

Head of regulatory reporting, Chief Data Officers, Chief Risk and Compliance Officers, Chief Finance Officers, Chief Technology Offficers, Chief Operating Officers, Transformation leaders, Supervisory authorities responsible for AI adoption.

Download the Agentic Gap report

The Regnology AI readiness snapshot

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