One of the emerging cybersecurity threats that worries me most from a compliance standpoint is the rise of AI-driven data exfiltration and misuse inside cloud ecosystems. The technology itself isn’t new — attackers have always tried to steal or manipulate data — but the way it’s happening now is far more sophisticated. With generative AI and automation tools, malicious actors can blend in with legitimate users, mimic behavior patterns, and exfiltrate sensitive data through approved applications without triggering traditional alerts. From a compliance perspective, that’s a nightmare. You can have all the right tools and policies in place, yet still fail to detect or prove a breach fast enough to meet your regulatory obligations.

What makes this threat especially dangerous is how it intersects with frameworks like SOC 2, GDPR, and HIPAA. These standards are designed to protect data, but they rely heavily on visibility and documentation — two things that become incredibly hard to maintain when threats are automated and behaviorally masked. An AI-powered attack can happen inside your sanctioned SaaS environment, using legitimate credentials, and by the time it’s detected, your audit trail might already be compromised. The risk isn’t just a breach; it’s non-compliance, which means reputational damage, lost trust, and in some industries, financial penalties.

The best way to tackle this is through proactive governance and layered detection. At GAM Tech, we’re putting a lot of focus on tightening access controls, implementing continuous monitoring, and building automated compliance checks into our workflows. The goal is to make compliance a living process — not an annual checkbox exercise. Every new AI or cloud integration goes through a compliance impact review before it’s deployed. We also invest in employee education, because people remain the biggest vulnerability and the first line of defense.

If there’s one lesson I’d share, it’s that compliance and cybersecurity can’t be treated as separate disciplines anymore. The next wave of threats will test how well organizations align the two. The companies that win will be those that view compliance not as red tape, but as a strategic framework for resilience. In a world where AI can write code and mimic users, your best defense is knowing — and proving — exactly what’s happening in your environment, at all times.

One cybersecurity threat that concerns me from a compliance angle is how generative AI is being used in social engineering and data theft. In the past year, AI-generated phishing emails, voice impersonations, and deepfake messages have become much more advanced. These attacks are no longer easy to spot because they are context-aware, personalized, and often look just like real business communications targeting everyday operations.

From a compliance standpoint, this poses a serious challenge because traditional controls such as awareness training and static data protection policies are no longer sufficient. In my experience, insurance and finance organizations are under more pressure to improve their AI governance, identity checks, and incident response plans. In one case, a simulated phishing test with AI-generated messages led to three times more employees clicking compared to standard phishing tests. This shows just how convincing these attacks have become.

This threat is especially serious because it affects both compliance and trust. Regulators are putting more focus on accountability for data handling and preventing breaches, but most compliance systems were not built to handle AI-based attacks. If just one identity is compromised, it can cause huge data leaks and damage a company’s reputation, which are problems that can’t be fixed by technical solutions alone.

To address this, I think companies need to move beyond simple compliance checklists and adopt ongoing assurance models. This means using AI defensively to spot unusual activity, check identity signals, and watch for changes in behavior as they happen. Compliance should be more than just paperwork; it should be a flexible system that keeps up with new threats.

From a compliance perspective, social engineering is always the most concerning threat because compliance is not a guarantee against these threats. Master manipulators use human emotion to gain access to networks every day. We all provide extensive training to our employees on how to detect and avoid social engineering, but it’s never enough. Constant reminders must be in place to never trust any email that is remotely out of the ordinary, even from a trusted source.

What makes social engineering particularly concerning is that these threats are now powered by AI. This allows attackers to send out wave after wave of massive attacks, and to create deepfake videos specific to executives and staff to extort them or breach their systems. The good news is that AI is also in use to counter these tactics. It’s a fascinating time to be in tech.

I would say one emerging threat that is not yet properly regulated is the use of AI in hacking attempts. We’ve known about phishing for years, mainly utilizing emails or text messages as an attack vector. Now we have vishing (AI voice replications) and deep fake videos that leave individuals with a high level of uncertainty. I think we will see more regulation around the use of these tactics and tools, but the incredible level of realistic replication is something to be very aware of. It is crucial to practice a “zero trust” mindset, stay aware and informed, and to continuously train your teams to exercise caution.

One cybersecurity threat which has unfortunately gained traction in recent years is AI-powered impersonation and content manipulation. While social engineering and impersonation have been a cornerstone of cyber criminal activity for some time, with the recent advancement in AI features and lower barrier to usage, bad actors have leveraged AI functionality to drastically cut down the time it takes to impersonate a trusted contact as well as increasing the likelihood that their target will fall for their tricks. This becomes an issue from a compliance perspective, when trusted security measures such as email security, security awareness training, and multi-factor authentication struggle to keep up with the sophistication of cyber threats. Hackers are now using AI-generated deepfake images, audio, and even MFA input pages to circumvent these security tools. Companies seeking to remediate this risk should ensure their cybersecurity strategy has multiple layers of protection at the data, user, endpoint, and network levels. That way, should a threat slip through one of your defenses, it should get flagged and quarantined by another.

The main security threat I monitor involves supply chain attacks which target open source and third-party dependencies. The process of ensuring software integrity through compliance has become increasingly difficult because one compromised package can spread through multiple systems without detection.

Our .NET Core project required us to implement private NuGet feeds and TeamCity dependency audits through enhanced CI/CD pipeline security measures. The initial investment of time proves essential because untested code entering production systems leads to major legal and compliance issues that affect regulated industries.

If we are going to require various laws, standards, and frameworks in our supply chain contracts, are we going to have enough TRAINED security, audit, compliance, and investigation personnel to enforce compliance?

The growing number of unsecured IoT devices and hardware components in corporate environments represents a significant compliance challenge that keeps me up at night. We’ve seen firsthand how nation-state actors like the GRU successfully compromised seemingly innocent office equipment like VoIP phones and printers to gain network access, completely bypassing traditional security controls. Most compliance frameworks haven’t adequately addressed hardware-level vulnerabilities, creating dangerous blind spots for organizations that believe they’re meeting security requirements. This is particularly concerning as critical infrastructure increasingly relies on connected hardware with potential backdoors or remote access capabilities that could be exploited.

AI-enhanced phishing is emerging as one of the most concerning cybersecurity threats from a compliance standpoint.

As technology advances, so do the tactics of cybercriminals. Today’s AI-powered phishing attempts have reached unprecedented levels of sophistication, creating scenarios where even vigilant individuals struggle to distinguish between legitimate communications and fraudulent ones. What makes these attacks particularly troubling is their ability to mimic familiar senders with messaging that appears authentic, or even leverage deepfake video technology to create convincing impersonations.

From a compliance perspective, this creates substantial challenges. Organizations must now implement more robust security protocols to meet data protection regulations while facing increasingly deceptive threats. Traditional compliance frameworks weren’t designed with such advanced deception technologies in mind. Effective detection now requires both human vigilance and cutting-edge security tools working in tandem.

The rapid evolution of these AI-enhanced techniques means compliance officers and security teams must constantly adapt their approaches to ensure regulatory requirements are met while protecting sensitive information from increasingly sophisticated attacks.

One emerging cybersecurity threat I’m deeply concerned about is the rise of AI-powered identity spoofing — models capable of replicating real humans’ biometrics, voices, and behaviors with near-perfect fidelity.

As systems move toward proof-of-personhood and AI agents begin to transact autonomously, the compliance layer around identity, data provenance, and consent becomes existential. Without verifiable human identity and clear audit trails for AI actions, we’ll face massive regulatory and reputational risks — from AML violations to synthetic-identity fraud.

What also worries me is that governments will use this threat as a justification to push for centralized identity systems — ones that create new single points of failure, concentrate data, and ultimately don’t solve the core problem of digital trust. The real solution lies in decentralized, privacy-preserving identity that empowers individuals instead of surveilling them.