From Vision to Trust: How to Launch an AI Governance Program

AI is no longer a futuristic edge — it’s a foundational force reshaping how software is built, deployed, and secured. For enterprise teams racing to integrate generative AI into their workflows, a solid governance strategy is no longer optional — it’s mission-critical.

At Snyk, our own AI transformation journey has reinforced one central truth:

Innovation without trust is fragile. And in the age of agentic AI, trust starts with governance.

In this post, we’ll share how we’re building AI governance at Snyk — from vision to execution — and how your organization can do the same.

Start with a clear vision

A successful AI strategy begins with clarity. At Snyk, we defined our north star early:

Use AI to drive operational efficiency, securely and responsibly.

This vision helped align teams and ensured we spoke the same language as we scaled. If you're just getting started, don't skip this step. Socialize your vision broadly and use it to inform every policy, workflow, and stakeholder discussion that follows.

Build your AI governance foundation

Traditional governance models aren’t built for AI’s unique risk profile. To keep pace with emerging threats like model jailbreaks, data poisoning, and insecure LLM integration, we needed a new framework. Our approach centered around the formation of a cross-functional AI advisory board.

Our board includes stakeholders from:

• Legal and compliance

• Information security

• Engineering and product

• Procurement

This team doesn’t just approve tools — they design the guardrails that allow innovation to move fast and safely.

Operationalize AI Trust: Our three-layered model

We created “paved roads” for AI adoption — clear, scalable policies that help teams innovate while staying secure.

1. Classify AI consumption models

Not all AI use is created equal. At Snyk, we track three categories:

• Embedded AI features (e.g., Salesforce, Slack, Atlassian)

• Hosted LLM platforms (e.g., OpenAI, Gemini, Claude)

• Self-hosted/custom LLMs (deployed inside our own infrastructure)

Each has its own risk model based on data sensitivity and system complexity. By defining them clearly, we reduce guesswork and risk.

2. Stop shadow AI before it starts

Shadow AI is the new shadow IT. If policies are too slow or too complex, teams will work around them. Our answer? Make the secure path the easiest one.

That means:

• Clear policies around data classification and LLM use.

• Guardrails for what can and cannot be shared.

• Internal guidance written in plain, developer-friendly language.

3. Activate AI talent you already have

Great AI programs don’t start with hiring — they start with upskilling.

• A small consulting engineering team that prototypes and deploys AI tools across the organization.

• Broad enablement programs to train the rest of the workforce on safe, effective AI usage.

As AI tools become more usable, AI fluency becomes a company-wide competency.

Culture eats policy for breakfast

Governance only works when supported by culture. At Snyk, we’re building a culture of experimentation to ensure AI becomes part of every team’s problem-solving playbook.

Here’s what’s worked for us:

• Democratize access to approved AI tools and APIs.

• Host all-hands trainings to demonstrate real-world AI use cases.

• Create an “AI Champions” network to lead adoption in each business line.

• Build sandboxes where teams can safely test AI against sensitive datasets.

These strategies turn curiosity into confidence — and help us scale AI faster and safer.

Security as an accelerator, not a gatekeeper

As a security company, we understand the risks. But we also know that security must be an enabler of innovation — not an obstacle.

That’s why we’ve embedded AI-native security into our own platform through:

• Snyk Assist: In-product AI guidance for secure development.

• Snyk Agent Fix: Automated remediation of vulnerabilities.

• Snyk Guard: Agentic policy enforcement across the SDLC.

By integrating trust into every layer of our platform, we help developers build fearlessly, with speed and security in sync.

The bottom line: Trust is the true enabler of AI innovation

Adopting AI at scale isn’t just a tech challenge — it’s an organizational transformation. From internal champions to evolving policies, from cultural buy-in to runtime controls, building trust is what unlocks sustainable innovation.

At Snyk, we believe AI innovation begins with trust. And AI trust begins with Snyk.

We’ll continue sharing our journey — and our results — so the broader developer and security community can move fast and stay secure in the age of AI.