“Be careful with AI, regulators don’t trust it!”

That line still gets thrown around in boardrooms and investment committees, and for good reason: the headlines focus on deepfakes, hallucinations, or lawsuits against opaque systems. However, when it comes to finance, compliance, and ESG reporting, the real story is very different.

The frameworks being enforced in 2025, from the EU AI Act to SFDR and CSRD, aren’t designed to hold AI at arm’s length. They’re designed with the assumption that firms will need technology, automation, and yes, AI, to cope with the workload.

Regulators don’t fear AI; they’re demanding it. And firms still treating automation as optional are already falling behind.

The Reporting Problem Is Too Big for Humans Alone

SFDR and CSRD alone now require hundreds of indicators covering everything from emissions and biodiversity impact to diversity metrics and supply-chain risk. Layer on top of that EU Taxonomy mapping, TCFD disclosure, and voluntary frameworks like SBTi or Net Zero trackers, and the reporting workload balloons to something no analyst team can realistically manage without help.

That’s the point. Regulators know that manual, human-only approaches break down under this weight. They lead to delays, errors, inconsistent outputs, and “checkbox reporting” that adds no real transparency. What regulators want instead is accuracy, timeliness, and comparability. Audit trails that prove how numbers were sourced. Standardised disclosures that reduce greenwashing. The only way to achieve that at scale is with automated systems; tools that can parse documents, track controversies, and map data to frameworks quickly and consistently.

In other words, the problem is too big for humans alone, and regulators are no longer pretending otherwise.

What Regulators Actually Want

The fear narrative comes from a misunderstanding. Regulators aren’t afraid of AI, they’re afraid of bad AI. The EU AI Act makes this clear. High-risk systems (which includes AI used in compliance, finance, and ESG) aren’t banned; they’re regulated. Providers must:

• Conduct and document risk assessments

• Run adversarial tests to catch weaknesses

• Log incidents and maintain audit trails

• Mitigate bias in training data

• Provide transparency around energy use and efficiency

That’s not a rejection of AI; It’s a framework for making sure AI is reliable.

And if you zoom out, the same pattern shows up across other regulations. SFDR doesn’t say “don’t use AI to compile reports”, it says, “be able to explain and verify your disclosures.” CSRD doesn’t warn firms away from automation, it demands timeliness and comparability, the very things automation provides. Even the FCA’s approach recognises AI as an inevitability, focusing instead on guardrails like governance and accountability.

The message is consistent: regulators expect firms to use AI, but they expect it to be explainable, auditable, and safe.

The Real Risk Is Standing Still

Too many firms are still holding back, convinced that waiting out the hype will keep them safe. They treat manual processes as the “compliance comfort zone,” believing regulators will view them as more trustworthy than automated alternatives.

But the opposite is true. Manual reporting is slow, error-prone, and often untraceable. You can’t prove where every number came from when it’s the product of multiple analysts copy & pasting across spreadsheets. You can’t guarantee consistency when reports take months to build, and you definitely can’t scale disclosures across multiple frameworks when everything is done by hand.

In other words, manual processes are a regulatory risk in themselves. The firms refusing to adopt AI aren’t protecting themselves; they’re exposing themselves. Meanwhile, their competitors are using AI not only to stay compliant but to generate insights faster, respond to investor queries in real time, and get ahead of the controversies that cause reputational damage. The divide between “wait and see” firms and early adopters is already widening.

Final Word

The age of “AI as a nice-to-have” is over. In regulated finance, it’s no longer about whether you use AI; it’s about whether you can prove that your AI is reliable, auditable, and working as intended.

Regulators don’t fear AI; they’re demanding it. The firms that understand this now will spend 2025 setting the standard. The ones that don’t will spend 2026 scrambling to catch up, or explaining to regulators why their manual processes failed them.