Deepfakes in the Boardroom: Why Governance Beats AI Detection

Deepfakes in the Boardroom: Why Governance Beats AI Detection

For decades, the famous photo of the Loch Ness Monster was considered proof of the creature's existence. It was a sensation, a mystery that captivated the world. Today we know: It was a hoax, a cleverly staged deception.

But while the Nessie photo was merely a curious story in the newspaper back then, the threat landscape has fundamentally changed. Today, it's not blurry photos we need to worry about, but deceptively realistic video calls from CEOs or voice messages from CFOs that can lead to financial disasters within minutes.

The Uncomfortable Truth About Deepfake Technology

The reality for executives, boards, and supervisory boards is sobering: We cannot win this war purely through technology. Deepfake detection is like a game of cat and mouse where defenders are structurally at a disadvantage. While security teams try to improve detection algorithms, attackers continuously evolve their techniques.

Modern deepfake attacks come without visible artifacts. The days when you could identify manipulated videos by blurry edges, unnatural eye movements, or distorted audio quality are largely over. Current generative AI models produce content that is nearly indistinguishable from authentic recordings, even for trained experts.

Why "IT Will Detect It" Is a Liability Risk

In many companies, I hear the phrase: "Our IT security will detect such attacks." This assessment is not just optimistic, it represents an incalculable liability risk.

Technical detection of deepfakes is a race that never ends. As soon as detection systems improve, attackers adapt their methods. Even more problematic: The false sense of security that technical solutions suggest can lead to organizational vulnerabilities being ignored.

We don't need new tools, we need governance for what counts as truth in an emergency. The question is not whether our software detects a deepfake, but how our organization handles uncertainty when critical decisions are at stake.

Three Pillars of Resilient Processes Against Deepfake Attacks

To effectively protect companies against deepfake-based attacks, it's not enough to invest in the latest detection software. Instead, we need practical, non-bureaucratic governance structures that work when it matters.

1. Mandatory Out-of-Band Verification

For critical transactions, there can be no exceptions, especially not when the supposed CEO is applying pressure. The principle is simple: The verification channel must be different from the original communication channel.

Practical Implementation:

• For payment instructions over 50,000 euros, mandatory confirmation via a second, independent channel (e.g., phone call to a known, registered number, not one displayed in the video call)
• Sensitive strategic decisions are not made solely based on digital communication
• A list of verified contact details for all executives exists and is regularly updated

Out-of-band verification works on the principle: Trust the message, but verify through another channel. Even if an attacker has created a perfect deepfake of the CEO, the attack fails when the employee calls the real, known mobile number of the CEO for confirmation.

2. Stop-the-Line Mandate Without Sanction Risk

The best technology doesn't help if corporate culture fails. Employees must have explicit authorization and mandate to immediately halt processes when suspicious, without fear of negative consequences.

This concept originally comes from manufacturing, particularly the Toyota Production System. There, any employee on the assembly line can stop the entire production if a quality problem is detected. The same principle must apply to security incidents.

Concrete Measures:

• Explicit communication from management: Raising security concerns is rewarded, not punished
• Establishment of a "security veto right" for defined situations
• Regular training where even executives learn to deal constructively with legitimate security inquiries
• Anonymous escalation paths for situations where direct pressure is applied

A culture that sanctions employees for delaying a supposedly "important" process is a culture that opens the door to attackers. Social engineering works so well primarily because people are afraid to question authority.

3. Defined Decision Paths with Audit Trail

Moving away from gut feelings toward documented decisions. For critical processes, it must be traceable: Who approved what, when, and based on what information?

This doesn't mean every detail needs bureaucratic approval. It's about clearly defined critical processes where it must be possible to understand afterward how a decision was made.

Implementation in Practice:

• Definition of critical processes (e.g., payments above thresholds, changes to bank details, release of sensitive data)
• Documentation requirement with timestamp: What information was available? What verification steps were performed?
• Four-eyes principle for particularly critical processes
• Regular audits of decision paths to identify vulnerabilities

The audit trail serves multiple functions: It protects the company in case of damage, it protects employees from unjustified accusations, and it makes clear where processes need optimization.

The Reality Check Question for Every Executive Team

Hand on heart: If tomorrow a deepfake CEO creates stress in a video call and orders an urgent payment, do you rely on your software or on your processes?

Every executive team, board, and CISO should be able to answer this question honestly. The answer shows whether a company is truly resilient or living in false security.

Realistic Scenarios That Are Already Happening Today:

• A "CEO" orders an urgent acquisition payment in a video call that must remain confidential
• A "CFO" sends a voice message instructing account details for an important supplier to be changed
• A "Board member" requests the release of sensitive company data in a supposedly confidential message

In all these cases, technical detection is unreliable. What counts are the processes and the culture.

Practical Steps for Implementation

The good news: Effective protection against deepfake attacks doesn't have to be complicated or expensive. Here are concrete first steps:

Immediate Actions (This Week):

1. Create awareness: Inform management and critical employees about the deepfake threat
2. Identify critical processes: Where could deepfakes cause the most damage?
3. Create emergency contact list: Compile verified contact details of all executives

Medium-term Measures (Next 3 Months):

1. Establish policies: Introduce out-of-band verification for defined transactions
2. Conduct training: Not just technical, but especially cultural
3. Run test scenarios: Simulated deepfake attacks to verify processes

Long-term Structures:

1. Governance framework: Formal integration into risk management
2. Regular audits: Review the effectiveness of measures
3. Continuous adaptation: The threat landscape evolves, defense must keep pace

Conclusion: Governance Beats Technology

The famous Nessie photo reminds us that people have always been susceptible to convincing fakes. The difference is: Today, the fakes are more perfect, faster to produce, and the potential damages are immensely greater.

The solution lies not in better detection software, but in resilient processes and a culture that not only permits critical questioning but actively encourages it.

Companies that rely exclusively on technical solutions are betting on the wrong horse. The future of cybersecurity lies in the intelligent combination of technology, processes, and above all: people who are empowered to say stop when in doubt.

The question is not whether deepfake attacks will target your company. The question is whether your organization is ready when it happens.