LLMs make it cheap for attackers to monitor a compromised account (e.g., email) for months. Instead of quickly selling credentials, they can now act as "persistent threats" against individuals, building a detailed profile and striking at the moment of maximum financial opportunity, like a house sale.

The market for cybercrime tools mirrors the legitimate SaaS industry. Criminals can purchase subscriptions to deepfake services, uncensored language models, and phishing kits, complete with pricing tiers and customer support, making advanced fraud accessible for a low monthly cost.

In modern scam operations, AI often makes the initial contact to test a target's susceptibility. If the person seems gullible, the call is transferred to a human operator. This conserves human resources and dramatically increases the volume and efficiency of scams.

AI has transformed scamming into a highly efficient business. Research shows cybercriminal organizations deploying AI generate 9x the volume and 4x the revenue of their peers. Leveraging generative AI for hyper-personalization, they operate like sophisticated, profitable businesses, effectively weaponizing technology for fraud.

Previously, creating unique, high-quality phishing websites was costly, limiting the scale of fraud. AI makes generating novel, legitimate-looking content nearly free. This allows bad actors to overwhelm detection systems that rely on identifying repeated fraudulent assets, increasing the volume of believable scams.

AI-generated scams are now so convincing that even sophisticated users are fooled. The responsibility has shifted from teaching customers to spot fakes to brands proactively deploying technology to take down threats. Blaming the customer is irrelevant as the brand still loses trust and revenue.

Sophisticated fraud operations function like rational businesses with supply chains, training, and P&Ls. They target areas with the highest potential return on investment, such as crypto, and will pivot to new opportunities as technology like LLMs lowers their operating costs.

The most immediate cybersecurity threat from advanced AI isn't a sophisticated system breach. Instead, it's the ability to use AI to massively scale "old school" fraud like impersonation and phishing attacks, tricking individual people at an unprecedented rate and volume.

While many focus on AI for consumer apps or underwriting, its most significant immediate application has been by fraudsters. AI is driving an 18-20% annual growth in financial fraud by automating scams at an unprecedented scale, making it the most urgent AI-related challenge for the industry.