AI Has Changed Ransomware. It’s Time We Changed How We Train People

AI is helping attackers launch cyberattacks that are faster, more convincing, and harder to identify than ever before.

And with the rise of generative AI, attackers are creating highly convincing phishing messages, deepfake impersonations, and automating ransomware attacks while posing as trusted workflows. But the worst part is that your firewall may not even recognize an attack.

Ransomware attacks involve deception—bad actors using persuasive tactics to lull people into believing that what they’re seeing is real. And with AI multiplying and accelerating productivity, attackers are making unintended use of AI-powered tools at an unprecedented pace to launch attacks at scale, targeting individuals and comp anies for ransom.

There’s always a weakest link that bad actors are waiting to exploit. And so, the question is: how can your enterprise become resilient enough to withstand malicious attacks?

How Cybercriminals Are Weaponizing AI

Attackers are now using AI to gain the same edge that it gives any legitimate user: speed, scale, and personalization. And with just a few tweaks, the very tools built to boost productivity are being repurposed to scale deception.

Here’s what that looks like in practice:

Using LLMs to generate believable phishing

Large language models — including open-source variants — are helping attackers craft phishing emails that sound eerily natural. These messages aren’t filled with broken grammar or the usual red flags. Instead, they’re polished, personalized, and deeply contextual.

Think about it: You get an email requesting invoice verification. It references the exact vendor you recently dealt with. There are no typos, no formatting issues. And it doesn’t feel like phishing, because it’s not trying to feel that way.

This is AI-powered phishing. Built with precision, tuned to context, and nearly impossible to catch by gut instinct alone.

Key risk indicators:

• Very contextualized phishing emails mimicking internal communication.
• Utilization of real names, departments, and project data.
• Minimal linguistic errors increase believability.

Deepfake Audio and Video

Deepfake technology is allowing attackers to impersonate executives — not just by name, but by face and voice. It can be a voice note from your “CEO” asking you to urgently transfer funds or maybe a video call from your “VP” instructing you to approve a payment.

And in real-time, under pressure, the brain doesn’t get a second chance to verify what it hears or sees.

Attackers count on that.

Key risk indicators:

• Real-time video or voice impersonation of known leaders
• Urgent or emotionally charged requests
• Sophisticated mimicry of tone, accent, and phrasing

Personalized Attacks at Unprecedented Scale

AI tools can help scrape publicly available data, from LinkedIn profiles to company blogs to old breaches on the dark web. This information allows attackers to build highly detailed personal profiles in minutes and use them to craft messages that feel like they’re meant for you.

It’s not just spear phishing anymore. It’s precision phishing, deployed at scale.

Key risk indicators:

• Campaigns tailored by role, location, or department
• Inclusion of private or semi-private information
• Use of multiple channels: email, SMS, chat, even WhatsApp

Automating Payload Variations to Evade Detection

AI has the ability to change the payloads, file hashes, and even the delivery mechanisms. Each instance is changed a little at a time to avoid detection by static or signature-based security tools. And so, what would otherwise have taken hours of trial-and-error by talented hackers can now happen in mere seconds using automation.

Key risk indicators:

• Polymorphic malware with changing signatures
• Increased frequency of zero-day-like variants
• Greater bypass rate against traditional AV and EDR systems

AI-Driven Social Engineering Bots in Real-Time Conversations

Cybercriminals are using advanced AI-enabled chatbots in messaging platforms, pretending to be coworkers, support teams, or third-party vendors. These bots can engage in conversation to elicit human responses and eventually manipulate users into clicking links, giving away credentials, or installing malware.

So, unlike old-school phishing, these attacks unfold interactively — making them very difficult to detect because they can be psychologically convincing.

Key risk indicators:

• Real-time chats mimicking internal team members or vendors
• Use of corporate lingo and familiar writing patterns
• Gradual trust-building before initiating malicious actions

What used to take hours of manual work is now just a prompt away.

Why the Human Layer Is Still the Weakest Link

Even with AI in the mix, attacks still require one thing: human interaction. The most advanced ransomware still needs someone to click, approve, or share.

That’s why your people remain the number one target. And attackers that use AI make exploiting them much easier. Because it knows how to mimic trust, trigger urgency, and appear legitimate. Employees are being asked to make security decisions — faster, more frequently, and under increasing pressure.

Let’s be honest: no one is immune. Not IT, not HR, not Finance.

According to a 2024 Statista report, there were 317.59 million ransomware attempts. And many of these attempts began with a socially engineered email that successfully bypassed both technical and human scrutiny.

The takeaway is simple: you might have a modern tech stack in place. But if an employee thinks a fake voice is real, or clicks a link that looks legitimate, your security posture crumbles in an instant.

How Traditional Training Fails to Stop AI-Driven Threats

Traditional training and awareness methodologies are not good because they were built for old-school email scams and outdated phishing tactics, not the AI-powered threats we’re dealing with in 2025.

So would a webinar once a year work? Or will static e-learning modules improve cyber resilience? It’s not going to cut it anymore because it’s not contextualized according to the landscape. And today’s attackers are increasingly using AI to create real-time, personalized threats. So defending against that requires a lot more than a slide deck.

Here’s where traditional training is falling short:

• Too much repetition, not enough real-world practice. Slides and bullet points won’t teach someone how to spot a deepfake call from a voice-cloned CEO. People need to experience these tactics firsthand to recognize them.
• Training once a year instead of continuous reinforcement. Threats evolve every week. If your training only happens once a year, you’re already behind.
• Generic lessons that ignore the actual risk people face in their roles. A marketing intern doesn’t face the same threats as the CFO. So why are they getting the same training?
• No behavior-based or adaptive learning. If someone is receiving phishing emails nearly everyday, their training content should adapt to your needs.
• No exposure to AI-crafted deception. Deepfakes. Synthetic emails. Spoofed voices. You can’t expect people to defend against something they’ve never seen or heard before.

If we want people to stay sharp and prepared, security awareness really needs to evolve. And it should start now.

So what could you potentially do for your enterprise?

How Threatcop Builds AI-Resilient Human Defenses

Securing your systems is not enough anymore. You need to reduce your attack surface by working to decrease human error, testing potential entry points into your organization.

At Threatcop, we’ve developed a highly-reliable AAPE Framework that’s embedded into our people security management approach to harden the human layer by focusing on awareness, adaptability, proactivity, and evaluation.

(AAPE stands for Assess, Aware, Protect, Empower — a practical framework designed to reduce human cyber risk at every stage.)

This framework comes to life through four powerful solutions, where each one is a core pillar of human-layer cybersecurity.

Threatcop Security Awareness Training (TSAT)

Awareness against the real-world AI threats, such as deepfake impersonation, voice phishing, etc., to equip your employees to develop instincts. This TSAT isn’t just training; it’s a vivid mental rehearsal for high-stakes decisions.

Threatcop Learning Management System (TLMS)

Interactive, gamified content (quizzes, comics, infographics) specific to how people learn best. TLMS makes sure that security awareness doesn’t become background noise; it becomes part of the workflow.

Threatcop Phishing Incident Response (TPIR)

What if an employee suspects something but doesn’t know what to do? TPIR creates a clear path: one-click reports, an environment for centralized alerts, and a faster SOC response, and this essentially cuts down on the time from suspicion to action.

Threatcop DMARC Solution (TDMARC)

Many AI-based phishing attacks succeed because email spoofing still works. TDMARC helps authenticate your domain (using SPF, DKIM, DMARC) so attackers can’t pretend to be you. It keeps your brand and your team protected.

Parting Thoughts

The true question isn’t if AI will be utilized in cyberattacks; it already is. The real question is, when will your people be prepared for it when it comes to their inbox, video call, or phone line?

Consider the actions your employees perform every day: link clicks, file sharing, and requesting approvals. All those have become possible attack surfaces. And this is the reason why People Security Management does not help the cause of an organisation; rather, it is an imperative that is strategic to the organisation.

When employees are trained to spot AI-driven deception, they become your most responsive, resilient, and resourceful line of defense.

Ready to strengthen your cybersecurity posture? Schedule a demo with our cybersecurity experts to discover how Threatcop’s AAPE-driven approach equips your workforce to detect and disrupt AI-powered threats before they escalate.