I’m thrilled to sit down with Dominic Jainy, a renowned IT professional whose expertise spans artificial intelligence, machine learning, and blockchain. With a keen eye on how these cutting-edge technologies intersect with cybersecurity, Dominic has been at the forefront of analyzing emerging threats like AI-powered ransomware. Today, we’ll dive into the evolving landscape of ransomware, the role of AI in amplifying these dangers, the looming impact of quantum computing, and the strategies needed to stay ahead of cybercriminals in this high-stakes game.
Can you walk us through what ransomware really is and why it’s more than just a technical problem for businesses?
Absolutely. Ransomware is essentially malicious software that encrypts a victim’s data, holding it hostage until a ransom is paid. But it’s not just about locked files—it’s a multi-layered attack. Beyond data loss, it disrupts operations, erodes customer trust, and can cost millions in downtime and recovery. More than that, it’s psychological warfare. Attackers exploit fear and urgency, pressuring victims into paying by threatening to leak sensitive data or permanently destroy it. It’s a business model built on intimidation as much as technology.
How did ransomware transform from isolated attacks into what you’ve described as a systemic threat?
Over the years, ransomware has shifted from random, opportunistic strikes to highly targeted, coordinated campaigns. Early on, it was about hitting whoever clicked a bad link. Now, attackers use sophisticated tools to go after critical infrastructure—think hospitals, energy grids, or government systems—where the stakes are sky-high. This makes it a systemic threat because a single breach can cascade into societal impacts, like delayed medical care or disrupted supply chains. It’s no longer just a company’s problem; it’s a risk to entire economies and public safety.
What’s driving the dramatic increase in ransom payments, with averages now over $1 million in 2025?
Several factors are at play here. First, attackers are targeting larger organizations with deeper pockets, knowing they can demand higher ransoms. The average hitting $1.13 million reflects this shift. But the total recovery cost—often exceeding $10 million—includes not just the ransom but also downtime, legal fees, system restoration, and reputational damage. Plus, the U.S., which sees about half of global attacks, is a prime target due to its wealth of high-value entities and sometimes inconsistent cybersecurity practices. Attackers know where the money is.
In what ways is AI reshaping the ransomware landscape and making attacks more dangerous?
AI is a game-changer for attackers. It powers polymorphic malware, which can rewrite itself on the fly to dodge traditional antivirus software. AI also enables deepfakes—fake audio or video of executives—that trick employees into transferring funds or granting access. Beyond that, AI-driven automation helps attackers scout networks, identify critical assets, and spread laterally at lightning speed. What used to take days or weeks can now unfold in minutes, leaving defenders scrambling to catch up.
You’ve mentioned adversaries seeking asymmetry in cyberattacks. Can you unpack what that means in this context?
Asymmetry in cyberattacks refers to attackers gaining a disproportionate advantage over defenders with minimal effort. AI tools allow a small group of cybercriminals to scale their operations massively—think generating thousands of malware variants or automating network infiltration—without needing a huge team or resources. Defenders, on the other hand, must protect sprawling systems, patch every vulnerability, and respond to evolving threats in real time. This imbalance makes it incredibly hard to keep pace, as attackers can strike faster and adapt quicker with less overhead.
Why do you believe the stakes of ransomware are so much higher today compared to a few years ago?
The stakes are higher because the targets have changed. A ransomware attack on a hospital can delay surgeries or block access to patient records, literally putting lives at risk. An attack on an energy company or logistics hub can disrupt power or food supply chains, triggering economic fallout. These aren’t just corporate headaches; they create ripple effects that hit communities and entire industries. The potential for widespread harm—beyond just financial loss—makes today’s ransomware a far graver threat.
Looking ahead, how does quantum computing pose a risk to current encryption methods used to protect data?
Quantum computing could shatter the encryption standards we rely on today, like RSA or AES, by solving complex mathematical problems at unprecedented speeds. One alarming strategy is “harvest-now, decrypt-later,” where attackers steal encrypted data now, store it, and wait for quantum tech to mature enough to crack it. This means sensitive data—like government secrets or financial records—could be exposed years down the line. While we’re not there yet, experts predict quantum breakthroughs could impact encryption within a decade, so we need to start transitioning to post-quantum cryptography now.
On the defense side, why is it critical to move beyond traditional signature-based approaches to combat ransomware?
Signature-based defenses rely on recognizing known malware patterns, but with AI-powered, polymorphic ransomware, those patterns change constantly. That’s why we need behavioral AI and anomaly detection—tools that spot unusual activity, like unauthorized file encryption or odd network traffic, even if the malware is brand new. Autonomous response systems take it further by reacting in real time, isolating threats before they spread. These proactive approaches are essential because waiting to identify a specific threat is often too late in today’s fast-moving attack landscape.
What’s your forecast for the future of ransomware in the AI and quantum era?
I see ransomware becoming even more precise and devastating as AI continues to evolve, enabling hyper-targeted attacks with greater psychological and financial impact. Quantum computing will likely add another layer of urgency, forcing a global race to secure data against future decryption threats. On the flip side, I expect defenders to lean harder into AI for predictive and autonomous defenses, but only if organizations invest now. The gap between attackers and defenders will widen for those who lag behind, while those who adapt could turn the tide. It’s a battlefield of innovation, and the next few years will show who’s ready to fight.