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Google Can’t Figure Out AI Security Either

Even Google, a company that poured over $6 billion into cybersecurity infrastructure in 2024 according to Alphabet’s annual report, is making it up as it goes when it comes to AI security. The biggest tech company on earth doesn’t have a playbook. Neither does anyone else. That fact should change how you think about protecting your business right now.

What’s Actually Happening

Google’s AI security stumbles aren’t a secret anymore. In 2025, researchers at ETH Zurich demonstrated that Google’s Gemini could be manipulated through prompt injection attacks to pull user data out of connected Google Workspace tools, according to the researchers’ published findings. Google patched it. More holes showed up. That cycle repeated. It’s still repeating.

This isn’t a Google problem. It’s an AI problem. The entire industry is running experiments at production scale. Your data is part of the experiment.

According to IBM’s 2024 Cost of a Data Breach Report, the average cost of a data breach hit $4.88 million, a 10% jump from the year before and the highest figure ever recorded at that time. AI involvement in attacks, both as a weapon for bad actors and as a vulnerable surface, is pushing that number higher. And in 2026, AI models are woven into almost every enterprise software stack. The attack surface grew by orders of magnitude while most companies were still writing AI acceptable use policies.

Why This Should Scare You More Than the Headlines Do

Here’s my contrarian take: most people are worried about the wrong thing.

Everyone is talking about AI replacing jobs. I’m watching AI create entirely new categories of security failure. And the companies selling you AI tools are not ahead of this. They’re reacting, same as you.

Google runs Project Zero, one of the most respected vulnerability research teams on the planet. Their published work shows that large language models introduce attack vectors that traditional security models weren’t built to handle. Prompt injection is the clearest example. A bad actor hides instructions inside data that an AI reads. The AI follows those instructions. The user never knows it happened.

OWASP, the organization that sets the standard for software security awareness, listed prompt injection as the number one risk for large language model applications in their published Top 10 for LLM Applications, according to OWASP’s official documentation. That designation puts it above data poisoning, supply chain attacks, and every other AI risk on the list. It’s sitting at the top because it’s both common and dangerous.

Think about what that means in practice. You connect an AI assistant to your email. A bad actor sends a message with hidden instructions buried inside plain text. The AI reads it, follows the hidden instructions, and forwards your inbox to an external address. You never see it happen. This has been demonstrated in controlled settings dozens of times. Security teams across the industry expect to see it used broadly throughout 2026.

The poor man’s mindset says, “I’ll wait for someone to solve this before I use AI tools.” That mindset costs you a year of productivity while your competitors move ahead. The rich man’s mindset says, “I understand the risks, I build controls around them, and I use the tools anyway.” That’s the actual play.

If you’re creating content or marketing assets using a tool like InVideo AI, you’re not taking some exotic security risk. The calculus is simple. You control what data goes in. You keep sensitive business information out of consumer AI tools. You use tools with clear data retention policies. Basic hygiene, not panic.

What This Means for You

I’d do three things immediately if I were running a small or midsize business right now.

First, map every AI tool your team uses and read its data retention policy. Most people have no idea their AI writing assistant stores every prompt they type for 30 to 90 days. That data sits on a server you don’t control. If your team is putting client names, deal terms, or internal strategy into a consumer AI tool, you’ve already had a data incident. You just don’t know it yet.

Second, treat AI outputs like unverified input from a stranger. Every developer knows to treat web form submissions as untrusted. Almost nobody applies that same principle to AI. If an AI reads external content and gives you a recommendation or takes an action, that output could have been shaped by someone who knew the AI would read that content. Verify before you act. Every time.

Third, build your security stack without overpaying. If you’re watching the budget, check AppSumo for lifetime deals on privacy and security tools. Small teams can get serious coverage without enterprise pricing. The tools exist. Most business owners just haven’t gone looking for them.

According to a 2024 report from the World Economic Forum’s Global Cybersecurity Outlook, the gap between organizations with formal cybersecurity governance and those without is widening fast, with governed organizations recovering from incidents in roughly half the time. The companies that built the policies first are spending less on cleanup. The sequence matters more than the tools.

The big tech companies won’t save you here. They’re publishing trust and safety pages while their engineers race to close holes their last update opened. That’s not cynicism. That’s the product cycle. Expect it and plan accordingly.

The Bottom Line

Google can’t secure AI for you. Neither can Microsoft, OpenAI, or any other vendor. They’re all building the plane while it’s in the air. The companies that come out ahead won’t be the ones who waited for perfect security. They’ll be the ones who moved fast with clear eyes, understood the real risks, and built smart habits before the first major incident hit their industry. That window is still open. It won’t be for long.

Frequently Asked Questions

What is AI security and why does it matter in 2026?

AI security means protecting AI systems from being manipulated, exploited, or used to expose sensitive data. In 2026, most business software includes some form of AI, which means the old cybersecurity approaches alone don’t cover everything that can go wrong.

Can even large companies like Google get hit through AI vulnerabilities?

Yes. Researchers have demonstrated successful attacks on Google’s AI systems multiple times, including prompt injection exploits targeting Gemini. Size doesn’t equal safety when the underlying technology is still being understood by everyone, including the companies that built it.

What is prompt injection and should I be worried about it?

Prompt injection is when hidden instructions get embedded in text that an AI reads, causing the AI to take actions the user never approved. If your business uses AI tools that read external content like emails, documents, or web pages, this is a real and present concern. OWASP calls it the top risk for AI applications.

How can small businesses protect themselves from AI security risks?

Start by auditing every AI tool your team uses and checking its data retention policy. Keep sensitive client and business information out of consumer AI tools entirely. Formal governance policies cut incident recovery time significantly, according to the World Economic Forum’s 2024 Cybersecurity Outlook research.

Is AI still worth using given the security risks?

Yes, without question. Businesses avoiding AI aren’t avoiding risk. They’re trading one set of risks for another, specifically the risk of falling behind competitors who are moving faster. Smart usage with clear data policies and basic hygiene is the practical path, not abstinence.

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