AI deepfakes have cost the industry over $200M this year. As CISOs, can we scale detection fast enough, or is regulatory pressure the only way to drive adoption?

Don't rely solely on regulatory bodies to safeguard your organization. Regulations are often reactive—introduced only after significant damage has occurred. They may drive compliance, but compliance alone doesn't equate to security, especially against fast-evolving threats like AI-driven deepfakes.

CISOs must lead with proactive defense strategies. Waiting for regulation is like locking the barn after the horses have bolted. Senior leadership may prioritize regulatory compliance, but that mindset won't protect against sophisticated threat actors exploiting deepfake technology.

Step one is education. It's cost-effective and immediately actionable. Your teams need to understand what deepfakes are, how they’re used in social engineering, and what red flags to watch for. Awareness is the first line of defense—and it scales faster than any regulation.

Step two would be to push for AI-Powered detection tools in your 2026 budget. You'll need to brief senior management on the threat and the need to mitigate that threat.

We can definitely scale detection efforts with better tools and awareness; however, the pace of attack innovation is outpacing our defense strategies. Realistically, regulations will play a vital role in driving widespread adoption of detection standards and preventive controls. We need both — a strong internal defense strategy and clear external efforts to curb attack innovations to stay ahead.

Simple answer would be, Yes, we can scale detection fast — but only if there’s upfront regulatory pressure to drive urgency and investment. Without that, adoption will lag. Because we as a CISO should push for this innovation and policy alignment to keep up with the deepfake threat

Thank you for bringing up such a timely and critical question

Can detection scale fast enough?
Not easily. Deepfake technology is evolving rapidly, and detection tools often lag behind. While AI-based detection is improving, it requires constant updates, sizable resources, and still struggles with accuracy. Smaller organizations especially may find it hard to keep up.

Is regulation the answer?
Regulation can help drive adoption of detection practices by setting standards and encouraging transparency (e.g., requiring disclosure of synthetic content). However, regulation alone isn’t enough—it must be paired with continuous investment in security technology.

What’s the way forward?
A hybrid approach. We need scalable detection tools supported by strong collaboration and real-time intelligence sharing, alongside clear regulatory frameworks that ensure accountability.
In short, detection and regulation must develop together to effectively combat the growing deepfake threat.