As regulatory requirements continue to evolve, compliance teams face a growing challenge in separating meaningful developments from the noise. Effective horizon scanning is no longer just about identifying what is changing, but understanding what matters, how it affects the business and what action needs to follow. The AI in Risk and Compliance 2026 report – co-authored by RegTech Analyst and Parker & Lawrence Research – delved into how firms can overcome regulatory noise today.
As part of the research for the report, Parker & Lawrence Research interviewed market leaders in the space to discuss the importance of overcoming the noise to build horizon scanning for actionable intelligence.
On this occasion, the firm spoke with James Mackonochie, global executive head of product at CUBE, aprovider of AI-powered horizon scanning and regulatory intelligence for financial institutions and other regulated organisations.
This interview was part of the wider AI in Risk and Compliance 2026 report conducted by RegTech Analyst and Parker Lawrence Research. To download the full report, click here.
Compliance teams have long framed regulatory change as a problem of sheer volume. A single publication might affect only one product, legal entity, jurisdiction or control. Another could simply restate an existing position without altering a firm’s obligations. A third may appear trivial on the surface yet change a requirement that runs through several policies and business processes.
Effective horizon scanning therefore depends on more than finding documents. Firms must understand what has changed, whether it applies to them, who is responsible for responding, and how each decision links back to an authoritative source.
Generative AI has made summarising regulatory text far easier, but it has also raised the stakes. A persuasive answer built on incomplete coverage, outdated context or unverified sources can quickly find its way into policies and controls.
Parker & Lawrence’s 2026 research found that 57% of respondents rated AI-related risk in compliance management as high or greater, suggesting that traceability and firm-specific relevance now matter as much as summary quality.
Many change-management teams still work from document-level alerts. Specialists open each publication, judge its significance, compare it with earlier text, identify affected obligations and then distribute tasks via email, spreadsheets, GRC tools and business teams. Global institutions monitor overlapping issuers in several languages, often assessing the same item more than once.
Broad keyword searches create noise, while unfamiliar terminology can obscure genuinely relevant change. Generic AI assistants may shorten reading time, but without a persistent view of a firm’s footprint, they risk producing an excellent summary of the wrong item.
CUBE aims to close this gap with a regulatory intelligence layer. The RegTech firm captures publications from more than 10,000 issuing bodies across 250 countries and territories in 100 languages, translating, classifying and mapping content into a common schema linked to primary sources. More than 250 regulatory, risk, research and editorial specialists support the technology.
A customer-specific “passport” records each organisation’s footprint, departments, products and services. A background agent assesses new developments against this profile and recommends priorities, with users able to view the reasoning, inspect sources and amend outputs.
Teams can launch impact assessments and workflow actions in RegFlow directly from RegInsight items, while Priorities Coworker creates a timestamped record of what was reviewed and against which obligations.
Early testing suggests CUBE’s agentic coworkers cut horizon scanning noise by around 60% compared with standard AI-powered tools.
Parker & Lawrence argues that CUBE’s strongest asset is its data foundation, but cautions that buyers should probe recall, precision, missed-change controls, multilingual consistency and governance when passport data is incomplete. As AI interfaces become easy to imitate, trusted data and an unbroken route from source to action may prove the real differentiators.
Read the original post from Parker & Lawrence Research here.
Copyright © 2026 RegTech Analyst
Copyright © 2026 RegTech Analyst
