Young adults in Britain are being targeted by scammers at dramatically higher rates than older generations, and artificial intelligence is making those attacks far more convincing. A survey of 15,000 adults across Europe, including 3,000 in the UK, found that Britons aged 25 to 34 were three times as likely to be scammed as those over 65. Among the 25 to 34 age group, 61% said they had been personally targeted by a scam, compared with just 20% of those over 65.

The gap is particularly striking because younger people often underestimate their own risk. Among 18 to 24-year-olds, 59% reported being targeted by scams, yet 28% in that age group said the person they worried most about online was a grandparent, compared with only 9% who said they worried most about themselves. This disconnect between perceived and actual risk creates a dangerous blind spot.

How Are AI and Deepfakes Making Scams More Convincing?

Artificial intelligence is fundamentally changing how fraud works. Deepfakes, which are AI-generated or AI-manipulated videos, audio, or images that convincingly imitate real people, are now being weaponized in scam campaigns. The technology can clone someone's voice, make a familiar face say something surprising, or turn a public figure into a fraudulent spokesperson.

Among younger Britons aged 18 to 24, 20% said they had encountered deepfake videos used in scam contexts, and 12% said they had received AI-generated voice calls impersonating someone they knew. A quarter of all UK respondents said they would struggle to tell the difference between a real video call and a deepfake. This vulnerability is particularly concerning because familiar voices and faces naturally encourage trust, while authority, fear, and urgency can bypass skepticism entirely.

The problem is compounded by the speed and scale at which AI enables fraud. As one counter-fraud advisor noted, fake investment schemes can now be generated in minutes, phishing messages are flawless, and voice clones are convincing enough to fool your own family.

What Types of Scams Are Targeting Younger Britons?

The scams affecting younger adults differ markedly from those targeting older generations. Social media and messaging services are major routes for contact, accounting for 41% of scam encounters among UK under-25s, compared with just 7% through email. Instagram and TikTok each accounted for 11% of scam encounters among younger users.

Among UK scam victims aged 25 to 34, 21% said they had fallen for fake investment scams, including fraudulent crypto schemes, bogus trading platforms, and NFT-related offers. That was double the 11% recorded among victims aged 18 to 24, with the average loss per fake investment scam reaching £414. The research also identified fake giveaways, fraudulent influencer promotions, and gaming scams among the common forms of fraud affecting younger people.

Device theft is another significant vulnerability. Among UK consumers whose accounts were hacked, 32% said the breach began with a stolen smartphone. This points to a broader pattern where younger adults, who manage more of their finances and identities online, face compounding risks from multiple attack vectors.

Steps to Protect Yourself Against AI-Powered Deepfake Scams

• Pause Before Acting: When you encounter suspicious media that creates pressure to act, stop and take time to verify before reacting, paying, replying, or sharing anything.
• Verify Through Known Channels: Contact the supposed speaker separately through a phone number, email address, or account you already trust, rather than using contact information provided in the suspicious message.
• Check for Context Clues: Be cautious when a new number or unverified account urgently requests money, credentials, cryptocurrency, gift cards, or sensitive data, or when a supposed relative or executive bypasses normal procedures.
• Examine the Requested Action: Scrutinize what the message is asking you to do. Secrecy, rushed transfers, login links, or cryptocurrency payments may expose the scam even when the media looks polished.
• Search for Independent Confirmation: Find the earliest account, post, or message you can verify, then search for independent confirmation from credible, unrelated sources before acting on any claim.
• Use Personal or Procedural Checks: Ask a private question only the real person would know, use a family safe word, or follow workplace approval rules to verify identity.

A 2026 peer-reviewed study found that people's ability to distinguish real from AI-generated faces and voices did not reliably transfer between the two formats, and confidence in one's judgment did not always match accuracy. This means that even if you think you can spot a deepfake, you may be overconfident in your ability to do so.

Why Are Regulators Now Treating AI Fraud as a Critical Threat?

The scale and sophistication of AI-driven fraud has prompted regulators worldwide to act. In India, both the Reserve Bank of India (RBI) and the Securities and Exchange Board of India (SEBI) have tightened cybersecurity rules as AI-driven fraud, deepfakes, and attacks on critical financial infrastructure become more sophisticated. The RBI released a new comprehensive cybersecurity framework for banks and financial institutions and has flagged the possibility of a "kill switch" mechanism allowing users to stop all financial transactions from their accounts during fraud.

SEBI introduced an IT Resilience Index (ITRI) for market infrastructure institutions, entities such as clearing corporations and exchanges that enable trading in financial markets. The framework will come into effect from early 2027 and includes an "early warning system" and continuous monitoring to flag risks early. SEBI also said it will be "shortly" issuing guidelines for responsible use of AI and machine learning in the market.

"The challenge is that AI materially changes the threat equation. Traditional cybersecurity frameworks were largely designed around identifiable vulnerabilities, human-led attacks, and periodic assessments. AI can dramatically increase the speed, scale, and sophistication of attacks, from automated vulnerability discovery and highly personalised phishing to deepfakes, identity fraud, and increasingly autonomous cyberattacks," explained Himanshu Bagai, partner at Saikrishna & Associates.

Himanshu Bagai, Partner at Saikrishna & Associates

In the UK, 49% of respondents said AI was making scams more convincing and harder to detect, ahead of respondents in France, Spain, and Germany. Another 38% said the technology was advancing faster than the tools available to stop it. This perception gap reflects a real challenge: defenders must protect against threats that evolve faster than traditional security measures can adapt.

What Happens After Someone Falls for a Deepfake Scam?

The psychological impact of being scammed extends beyond financial loss. In the UK, 42% of scam victims said they blamed themselves, almost the same as the 43% who blamed the scammer. Britain was the only market in the survey where self-blame and anger at the criminal were nearly level. Among UK adults aged 25 to 34 who had experienced a scam, 44% said they blamed themselves, 37% said they felt panicked, and 34% said they felt stupid or naive. Nearly one in five in that group said they would be too ashamed to tell anyone.

This shame and self-blame can prevent victims from seeking help or reporting fraud to authorities. Among scammed 18 to 24-year-olds, 10% said they told an AI chatbot about the experience, close to the 11% who told nobody. The research also found evidence that some younger adults are being drawn into criminal activity themselves. Among UK 18 to 24-year-olds, 42% said they had been approached to let someone use their bank account to move money in return for payment, a practice known as money muling. Some 5.6% said they had agreed to do so, rising to 7% among 25 to 34-year-olds. Money muling can expose participants to criminal penalties as well as financial loss.

If you have already sent money or disclosed credentials to a scammer, contact your financial institution immediately, secure any exposed accounts, and change compromised passwords. If your face or voice was used in a deepfake, report the content, preserve evidence, alert affected contacts, and notify appropriate authorities when necessary.

The fundamental challenge is that deepfakes are social-engineering tools. A convincing face or cloned voice can support impersonation fraud, credential theft, account compromise, unauthorized payments, manipulation, and reputational damage. The FBI has warned that AI-generated voice messages are used in impersonation campaigns seeking data or funds. When seeing and hearing are no longer enough, verification becomes the new front line against AI-driven threats.

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