Everyone is navigating AI security in real time — even Google

Even Google, one of the most sophisticated AI organizations on the planet, is figuring out AI security as it goes. A recent TechCrunch analysis makes the case that no company, regardless of resources or technical depth, has fully solved the challenge of securing AI systems. Everyone is operating in real time, learning from incidents as they happen.

The Details

The core finding is straightforward: AI security is not a solved problem, and the organizations building these systems are discovering vulnerabilities, failure modes, and unintended behaviors through deployment rather than through pre-release testing alone.

This applies across the board, from startups to hyperscalers. Even Google, with its deep security research teams and years of AI development experience, continues to encounter novel security issues tied specifically to AI behavior.

Key themes from the analysis include:

• Prompt injection and adversarial input attacks remain difficult to fully defend against
• AI systems can be manipulated in ways that traditional software security frameworks were never designed to address
• The speed of AI deployment is outpacing the development of mature security standards and best practices
• Organizations are often discovering what "secure AI" means only after something goes wrong

The honest takeaway is that the industry is in a transition period, and acknowledging that is the first step toward managing it responsibly.

Why This Matters for Service Providers

If Google is still navigating AI security in real time, your clients are certainly not immune to risk. MSPs and telecom resellers deploying AI tools, including AI voice agents, automated workflows, and customer-facing AI systems, are inheriting security unknowns that even their vendors have not fully mapped.

The practical implication: you cannot assume that an AI product being sold to you has been fully hardened. Security due diligence on AI tools now needs to be part of your standard vendor evaluation process, not an afterthought.

This also creates a real service opportunity. Clients are looking for guidance on AI risk, and MSPs that can speak intelligently to AI-specific security considerations will differentiate themselves. If you are building out an AI voice or automation practice, pairing it with a clear security posture is increasingly a sales advantage. Resources like MSP Revenue Stacking: Voice, Security, and AI as Your Three Growth Pillars outline how to position these services together effectively.

Compliance considerations are also evolving alongside security risks. If you are deploying AI in customer communication contexts, staying current on regulatory requirements matters now more than ever; see our STIR/SHAKEN, TCPA, and AI Calls compliance guide for a current overview.

Looking Ahead

Expect AI security standards to mature over the next 12 to 24 months as incidents accumulate and regulators respond. Service providers who build security evaluation into their AI vendor selection process now will be better positioned than those who wait for the industry to fully sort it out.

For the full story, read the original article on TechCrunch AI.