Whether it’s powering search engines, personalising your social feeds, writing music or helping detect early-stage cancers, Artificial Intelligence (AI) is transforming our lives.

But as its capabilities increase the challenge isn’t just keeping up with AI, it’s ensuring the tech is ethical, transparent and accountable, and nowhere is this more urgent than for compliance and anti-money laundering (AML).

Much of the recent debate around AI has focused on its disruptive presence in creative industries. These concerns are valid.

As artists and campaigners like Sir Elton John have warned, if governments exempt tech firms from copyright laws, the impact could be devastating for emerging talent and creative livelihoods alike.

But the dilemmas facing the creative fields mirror those emerging across more regulated sectors.

Misused

AI, when misused or misunderstood, can be just as disruptive in compliance as it is in the arts. And that’s exactly why we need to talk about how it’s being applied in AML.

The property sector is one area where AI is already having a tangible impact. From intelligent data processing to customer onboarding and risk detection, AI can make compliance faster, more efficient, and more accurate.

In AML, AI is being used to automate labour-intensive tasks like transaction monitoring and customer due diligence.

It can analyse massive volumes of data in seconds, detect complex patterns of suspicious behaviour, and reduce the number of false positives that often overwhelm compliance teams.

The benefits are clear. AI enables streamlined operations and reduces costs, it enhances detection capabilities by identifying suspicious activity invisible to manual or rules-based systems and it cuts down false positives, allowing firms to focus on genuine risks.

Also, thanks to machine learning, it can evolve with emerging money laundering tactics—something static systems cannot do.

But while these are the upsides, we must also acknowledge the risks. By its very nature, AI is a learning tool, which means its effectiveness depends entirely on the data it is trained on.

If that data is biased, outdated or incomplete, the system’s decisions will be the same, which creates compliance risks rather than solving them.

The lack of transparency in many AI models also poses a significant problem. If you can’t explain how a decision was made, how can you prove to regulators that your process is sound?

And let’s not forget the privacy question. The more customer data that is fed into AI systems, the greater the risk of data breaches or unauthorised access.

This is not hypothetical—recent breaches involving well-known UK retailers show just how real the threat is.

Therefore, the key to successful AI deployment in AML isn’t choosing between humans and machines. It’s creating a partnership between the two.

AI is excellent at processing and identifying patterns at scale, but it cannot offer proper judgment, ethical reasoning, or any kind of contextual understanding.

Whereas human compliance experts struggle to analyse data at scale, they can offer all those things that AI cannot.

Therefore, the most effective AML strategies will use both strategies to their strengths. They do not replace people with AI, they empower people through AI.

Trustworthy

Therefore, any regulated firms looking to integrate AI into their processes must be comfortable that the data powering their AI is accurate and trustworthy, that the outputs have an explainable and auditable audit trail and that there is human insight at each stage.

At SmartSearch, our goal has always been to develop technology that enhances compliance, not complicates it, and we have spent more than 20 years building digital solutions for regulated businesses.

Our latest innovation, SmartDoc, uses biometric verification, facial matching, and advanced AI fraud detection to deliver an advanced identity validation solution that is secure and transparent with explainable results.

We believe that the future of AI in AML lies in building ethical, balanced systems that combine technological innovation with human expertise. It’s not enough for AI to be powerful, it must be transparent, explainable, and built with regulatory compliance in mind.

Phil Cotler is CEO of SmartSearch.