Criminals and members of the public are learning and using AI faster than the police can respond. In the parts of policing that handle domestic abuse, non-consensual intimate images and spiking, that gap is not abstract. It shapes what happens when an officer reaches a victim at three in the morning.

Claire Hammond, temporary Detective Chief Superintendent at the National Centre for Violence Against Women and Girls and Public Protection, argues that AI belongs in these cases precisely because they are the hardest, and that the human must keep every decision.

The conversation sets out a closed AI agent, named M, embedded in the Centre’s digital toolkit and live across 43 forces. Claire makes the case that M’s value is not speed alone but pattern: an officer treating one crime in isolation can be prompted to consider coercive control, stalking, or a wider history of abuse. She is candid that policing was pushed into AI rather than choosing it, and that senior leaders carry more caution than frontline officers who adopt anything that saves time. She holds one line throughout: AI supports the officer, it does not replace the decision maker.

Highlights:

• M is a closed agent, built to answer only from national guidance rather than learn from open data, giving one national response at any hour.

• Deepfake abuse images are now produced at the touch of a button, where they were once cut from a catalogue and pasted by hand.

• AI drafts overnight handover summaries, so an oncoming officer inherits the case rather than a two-line email.

• Disclosure that once meant reading 20 to 30 years of records is condensed for a human to check and decide.

• “Criminals are using AI at such a speed as well. And they’re learning a lot quicker than we are.”

For an account of AI adoption where the stakes are highest and the human stays in charge, this conversation is worth your time.

00:00 Introduction to AI's role in policing and public safety

02:17 Claire Hammond introduces the NCVPP and her role

04:41 The NCVPP's work in AI and police training

06:46 How AI is changing police work and crime detection

08:14 Detecting AI-enabled crimes like deepfakes and fraud

09:24 Examples of AI in case file management and disclosures

11:36 Cultural challenges and trust in AI within police

13:23 Impact of AI on public understanding and safety

17:52 Using AI to support decisions in violence against women and girls cases

20:21 AI's role in identifying coercive control and domestic abuse patterns

21:12 Future plans for expanding AI use in police disclosures and protective orders

24:26 Governance and ethical safeguards for AI in policing

26:50 Building public trust and engagement with AI tools