In this episode of the Human First AI Marketing podcast, host Mike Montague sits down with Alexander Schlager, founder of Alceberg.ai, to unpack the hidden cybersecurity challenges lurking beneath the surface of AI adoption. From the rise of agentic AI to the evolving threat landscape of autonomous tools and prompt injections, this conversation goes deep into why observability, memory, and human-in-the-loop design are critical for keeping your brand and your customers safe. Whether you’re leading marketing for a startup or managing tech stacks in a mid-sized enterprise, you’ll gain valuable insight into where AI safety, data privacy, and business alignment intersect.
Key themes include the real-world risks of overreliance on AI, why 95% of agent AI pilots are failing today, and how SMBs can get ahead by investing in security, not just speed. Alex shares a pragmatic view on balancing innovation with compliance, the importance of explainable AI models, and why “natural language is the new code” for marketers. You can tune in to learn how to future-proof your AI initiatives with a human-first approach because what’s visible above the surface is only the beginning.
There’s a reason we called this episode Identifying the AIceberg of Cybersecurity. Like the iconic metaphor, the biggest threats in AI aren’t the ones we see above the surface; they’re the ones buried deep in complexity, misunderstanding, and overconfidence. I had the pleasure of diving into this topic with Alexander Schlager, founder of Alceberg.ai, on the Human First AI Marketing podcast. And let me tell you: it was a conversation packed with value for any business leader serious about scaling responsibly with AI.
Whether you’re a tech-savvy marketer or a small business owner exploring new tools, here’s what you need to know:
1. AI Security Is Not the Same as Security AI
Alex explained this beautifully. Many companies are using AI to power traditional security systems, but that’s not the same as securing AI systems themselves. Especially with the rise of agentic AI (AI that acts on its own), new risks emerge that old tools simply weren’t built for.
2. Most Agent AI Pilots Are Failing
MIT reports that 95% of agentic AI pilots fail. Why? Because businesses are jumping in without preparing their data, processes, or guardrails. Before you automate a task, ask yourself: Is your data clean, secure, and structured? Do you have the right oversight mechanisms in place?
3. Human-in-the-Loop Design Builds Trust
AI isn’t magic. It needs feedback. Schlager emphasized building human checkpoints into early agent flows think of it like training a new employee. You don’t give them full autonomy on day one; you coach them and review their work until you’re confident they can operate independently.
4. Observability Is a Strategic Imperative
You can’t monitor everything. Instead, monitor what matters. Iceberg.ai focuses on high-risk events like tool invocation when an AI agent acts on its own in the real world. That’s where the danger lies, and that’s what should trigger your alerts.
5. SMBs Have a Short-Term Advantage
Here’s some good news: small and medium-sized businesses are not yet bogged down by heavy AI regulation. That means you can move faster, but only if you move smart. Investing in safety and trust early protects your brand, your customers, and your future scalability.
6. Watch Out for Overreliance and Techno-Optimism
Too many businesses assume AI is ready for prime time. It’s not. And putting blind faith in tools you don’t fully understand can create compliance nightmares, reputational risk, or worse. Think of AI as a junior partner, not an infallible oracle.
7. Natural Language Is the New Code
Marketing teams are increasingly deploying AI with prompts, not programming. But natural language comes with its own risks. Every prompt is a potential exploit vector, and if you’re not observing usage patterns, you’re flying blind.
8. Toxicity and Illegality Are Easier to Catch Than Misalignment
Toxic content is usually apparent. What’s harder is figuring out whether the AI is doing what the user intended it to do. Alignment matching agent behavior to user intent is emerging as a critical challenge in AI safety.
9. The Bad Guys Have AI Too
From phishing emails to malware generation, attackers are already using AI at scale. The arms race is real. But you don’t need to be paranoid, you just need to be proactive.
Final Thought: Don’t Wait Until It Breaks
If there’s one message Alex and I want to share with every SMB, it’s this: Don’t wait until AI fails you to get serious about cybersecurity. The iceberg is out there, and while it might be invisible at first glance, it’s deadly if ignored.
At Avenue9, we’re here to help you build AI strategies that put trust and safety first because human-first marketing starts with human-safe systems.
Want to future-proof your AI tools and marketing systems? Let’s talk.
Visit us at Avenue9.com or connect with me on LinkedIn.
