The AI hype train has officially left the station, and it’s crowded. Every day, We see new “AI Mentors” and “Generative AI Specialists” appearing on LinkedIn. Some even boast “20 years of business and AI experience“- a fascinating claim, considering that the specific models they are “mentoring” on have barely been public for three years.
As someone who has spent over a decade in cybersecurity and the last five years deep-coding and researching Artificial Intelligence, this isn’t just a marketing pet peeve for me. It’s a professional red flag.
The Rise of the “Weekend Course” Expert
I recently came across a profile: “AI Mentor with 20 years of experience.” A quick look behind the curtain revealed a website only four months old and a professional background strictly in retail marketing. The “expert” status was backed by a single weekend crash course from a local provider.
Don’t get me wrong – learning to use ChatGPT for better marketing copy is great. But there is a dangerous chasm between being a Power User and being an AI Strategist.
The Eurostar Lesson: When AI Ships Without Governance
We recently witnessed a textbook example of what happens when AI implementation is handled as a “creative project” rather than a technical one. Eurostar’s AI chatbot just became the perfect case study for why the EU AI Act exists.
Security researchers at Pen Test Partners found they could bypass the chatbot’s guardrails, extract its system prompt, and inject arbitrary HTML. The cause? A fundamental architectural flaw: the backend blindly trusted whatever the frontend told it.
The technical failures were elementary:
- Client-side Guardrails: Critical security decisions were made in the browser, not on the server.
- No Cryptographic Binding: There was no verification between messages and their security status.
- Blind Trust: Chat history was accepted without verification, and raw HTML was rendered directly from LLM outputs.
The real failure, however, wasn’t technical—it was a failure of oversight. No one asked “what could go wrong” before going live. When the researchers tried to responsibly disclose these vulnerabilities, Eurostar responded not with gratitude, but with accusations of blackmail. This is the defensive reflex of a company that realizes it has deployed customer-facing AI with zero audit trails and zero governance.
The Danger of “Creative” AI Implementation
When a marketing-focused consultant “implements” AI in a company, they usually focus on the “wow” factor: generating images, automating emails, or summarizing meetings. What they often miss are the structural integrity and security protocols.
If your “mentor” doesn’t understand the difference between a client-side and server-side guardrail, they aren’t just giving you tips; they are handing you a liability. We saw this recently with the Eurostar AI chatbot debacle. Security researchers bypassed its guardrails in minutes because the backend blindly trusted the frontend. This is exactly what happens when AI is shipped without governance.
Why Cybersecurity is the Real Foundation of AI
In my 10+ years in cybersec, I’ve learned that any new technology is just a new attack vector. When you “integrate” AI, you are opening doors.
- Data Leaks: A “creative” mentor might tell you to upload your customer database to a public LLM for analysis. To them, it’s “efficiency.” To a security professional, it’s a GDPR catastrophe and a breach of trade secrets.
- Shadow AI: Without technical oversight, employees start using unvetted plugins and tools, creating a “Shadow IT” landscape that is impossible to audit.
- The EU AI Act: By August 2026, the EU AI Act will be in full force. It requires risk assessments, technical documentation, and human oversight. A marketing “expert” cannot sign off on your technical compliance.
How to Vet Your AI Consultant (The 5-Minute Audit)
Before you hire an AI Mentor, stop looking at their “20 years of business” slogans and ask these five questions:
- Technical Pedigree: Do they have a background in Computer Science, Engineering, or Data Science? Or did they just “pivot” from marketing six months ago?
- Security Protocols: Can they explain how they prevent Prompt Injection or data leakage within your specific infrastructure?
- Governance Knowledge: Are they familiar with the technical requirements of the EU AI Act and ISO/IEC 42001?
- Vendor Certifications: Do they hold legitimate engineering certifications from Microsoft (Azure AI), Google Cloud, or AWS, or just “certificates of attendance” from local workshops?
- Audit Trails: Can they show you how they log and audit AI decisions to survive a regulatory inquiry?
Final Thought
AI governance isn’t bureaucracy; it’s the difference between a minor efficiency gain and a headline-making data breach.
If your AI strategy doesn’t start with security, it’s not a strategy – it’s a gamble.
Don’t let a “Power User” handle your enterprise architecture.