We've seen this story play out before: a shiny new tech trend pops up, and suddenly, everyone's clamoring to jump on the bandwagon. It happens to consumers, and it happens in business. AI is no different. Snyk's Secure Adoption in the GenAI Era report surveyed tech professionals across roles—from executives to developers—and found that while many feel their companies are ready for AI coding tools, they're also worried about the security risks these tools might bring.

It's smart to have concerns and plan for risks. But the data shows a gap: many organisations aren't taking basic prep steps, like running proof-of-concept (POC) evaluations or giving developers proper training. Interestingly, people who've spent more time working with AI tools tend to be more cautious about adopting them quickly—they've seen the limitations firsthand, whether it's errors or the infamous "hallucinations" that sometimes occur.

Confidence in AI adoption is great, but rushing in without preparation can cause big problems. Here's how your organisation can stay confident and grounded when implementing AI.

Conduct thorough proof of concept (POC) evaluations

Snyk's research shows fewer than 20% of companies run POCs before adopting AI tools. That's a big miss. Without testing tools in a controlled environment, companies risk adopting systems that might be insecure, non-compliant, or just plain ineffective.

Running a POC lets you assess how a tool fits into your workflow and helps identify weak spots before they become costly mistakes. It's not just about finding flaws—it's about building trust in the tools you're adopting.

Provide comprehensive developer training

You can't expect developers to use AI tools securely if they haven't been properly trained. Lack of training increases the chance of mistakes that could lead to security breaches or system failures.

Invest in education. Teach your teams not only how to use these tools but also their limitations. Cover best practices for integration, security risks to watch out for, and even ethical considerations. The more knowledgeable your developers are, the better equipped they'll be to collaborate with security teams and handle AI responsibly.

Foster collaboration between security and development teams

If your AppSec and dev teams aren't working hand-in-hand, you're asking for trouble. Snyk's report shows AppSec practitioners tend to be more cautious about AI adoption, so getting their input early on can help identify risks before they turn into full-blown problems.

When these teams collaborate, they can balance innovation with security. Developers bring the practical know-how, while security teams provide the risk perspective. Together, they can ensure AI solutions are both effective and safe.

Establish clear policies and guidelines

A lack of clear guidelines around AI use can lead to everything from accidental data leaks to compliance issues. Snyk's findings highlight that many organisations don't have strong policies in place—and that's a recipe for trouble.

Create policies that cover the essentials: data handling, access controls, and ethical use. Make them living documents that get updated as technology and regulations evolve. Clarity here will save you headaches later.

Maintain realistic expectations and continuous monitoring

It's easy to get swept up in the hype around generative AI, but let's be real—it's not a magic fix for everything. AI tools can (and do) make mistakes, so don't rely on them as standalone solutions. Use them to enhance human expertise, not replace it.

Regular monitoring and performance reviews will help you catch issues early, adapt to changes, and keep everything running smoothly. By pairing realistic expectations with continuous oversight, you can get the most out of AI without unnecessary risks.

Confidence in AI is a good thing—just make sure it's well-placed. By taking these steps, you can harness the power of AI responsibly and effectively, without letting overconfidence get in the way.