Credo AI

06/04/2026

60% of enterprises are scaling AI. Only 4% are governing it.

As AI moves from experimentation to rapid agentic AI adoption, the challenge is no longer model performance, it's operationalizing trust, accountability, and governance at scale.

That's why a new enterprise role is emerging: the Forward Deployed AI Governance Engineer (FDAGE).

FDAGEs transform AI governance from a compliance exercise into an operational capability by:
➡️ Creating visibility across the AI stack
➡️ Building governance operating systems and controls
➡️ Embedding accountability and continuous oversight
➡️ Enabling organizations to scale trusted AI

The future of enterprise AI won't be defined solely by who builds the most capable systems. Creating trust and AI governance at scale requires experts who have battle tested experience building for the leading AI adopters.

Trust isn't a control point. It's a competitive advantage.

Check out our latest blog here and book a strategy call with our Forward Deployed AI Governance Engineers: https://www.credo.ai/blog/why-every-ai-first-enterprise-needs-a-forward-deployed-ai-governance-engineer

06/02/2026

The EU AI Omnibus was adopted today. Most attention is on simplification. The more important story is accountability.

Yes, there are real efforts to reduce complexity. But beneath that narrative is a bigger shift: AI governance is moving toward greater provider accountability, more direct oversight, and increased executive responsibility.

Three questions our latest blog answers:

1. Now that the high-risk deadlines have moved, what do organizations actually need to do, and why is treating the new dates as targets a mistake?
2. What does it really take to meet the AI Act's expected new safeguards on CSAM and NCII, especially for generative AI providers?
3. Why is AI governance becoming a board-level strategic asset for leaders operating in the EU, not just a compliance function?

The new deadlines aren't relief. They're an opportunity to build the governance, controls, and evidence that will withstand scrutiny and create a competitive advantage.

Read it here and in the comments: https://www.credo.ai/blog/from-compliance-function-to-strategic-asset-what-the-eu-ai-omnibus-makes-clear-about-ai-governance-as-a-strategic-asset

05/27/2026

AI agent security isn’t breaking because individual tools are insecure.
It’s breaking because compositions of approved tools create capabilities no one reviewed.

A Model Context Protocol (MCP) server that reads documents may be low risk. Combine it with Slack access and outbound email, and you may have created an exfiltration pipeline.

That’s the AI governance gap most enterprises aren’t modeling yet. Traditional AI security reviews evaluate vendors, APIs, and assets independently. Agentic systems require reviewing the agent + capability set as the unit of risk.

Three practical shifts for security leaders:
1. Tier risk per agent deployment, not per tool
2. Red-team capability compositions, not just components
3. Trigger review when compositions change

The protocol will evolve. The composition problem will remain.

➡️ Check out our latest blog here and in the links to learn more about the hidden risk layer in Agentic AI: https://www.credo.ai/blog/the-hidden-risk-layer-in-agentic-ai-a-credo-ai-security-perspective-on-mcp

05/22/2026

Welcome to Keeping Up with AI, Credo AI’s newsletter for enterprise leaders navigating the rapidly evolving world of agentic AI.

Subscribe to stay ahead of the latest agentic AI governance trends, what’s fueling enterprise AI agent adoption, and where the market is headed.

You’ll also get updates on:
➡️ Credo AI product innovations
➡️ Strategic partnerships
➡️ Practical resources designed to help enterprises build and scale trusted AI with confidence.

Subscribe today: https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=7460807106401570817

05/21/2026

60% of enterprises are scaling AI. Only 4% are governing it at scale. 📊

As agentic AI becomes embedded across hiring, financial services, healthcare, and customer operations, governance is quickly becoming a business-critical priority.

That’s why we created The 2026 Enterprise Buyer’s Guide to AI Governance, a blueprint for enterprise leaders navigating AI risk, compliance, and scale. Our guide was built from insights across 371 AI governance practitioners, analyst research, and Credo AI’s work with Global 2000 enterprises.

Inside our Buyer's Guide:
✅ The 5 must-have AI governance capabilities
✅ 10 key questions to ask every vendor
✅ Real-world enterprise examples from Mastercard, PepsiCo, and Cisco
✅ A framework to build your internal business case for AI governance

➡️ Download The Enterprise Buyer’s Guide to AI Governance here and in the comments: https://www.credo.ai/downloadsopen/the-enterprise-buyers-guide-to-ai-governance

05/21/2026

Credo AI Founder and CEO Navrina Singh in the The Wall Street Journal today: “The market has priced AI’s potential but has not factored in the cost of the vulnerabilities these systems could create at scale, especially with agentic AI."

Shared by Bradley Olson at The Wall Street Journal, Navrina went on to highlight, "Capital is racing toward AI at full speed, but none of that is priced into a single one of these valuations.”

As the AI boom accelerates and leading AI companies approach public markets, trustworthy AI governance is becoming the foundation for moving fast and scaling trusted AI systems in the agentic era.

➡️ For more, check out the latest WSJ coverage here and in the comments:

Silicon Valley’s hottest startups are competing fiercely as big tech companies contend with fickle investors and hard choices.

05/20/2026

Is our agent being attacked, exploited, or manipulated? -> CISO's concern
Is the agent performing as expected? -> Head of AI Platform's concern
Is our data handled lawfully and responsibly? -> Chief Privacy Officer's concern

These are real questions that require actionable insights for senior leaders. We've released the Agentic AI Field Guide for enterprise leaders to bring clarity to some of the most warranted questions of this agentic era. The one size fits all answers no longer fit your business at scale, depending on what Agentic AI governance needs matter to you most.

➡️ Download our field guide here and in the comments:

Governance built for the speed of autonomous AI. Inside: six structural components, five readiness tests, and the regulatory frameworks taking effect in 2026.

05/19/2026

The traditional product design loop has long followed a familiar pattern:
Figma mockups → engineering review → screenshots back to design → iterate. But Agentic AI is fundamentally reshaping that workflow.

The engineering teams that will win in this agentic era are building self-documenting, architecturally constrained systems that are consistent, reliable, and governable by design.

At Credo AI, we’re building for external developers to build trusted AI governance on top of our platform.

In our latest engineering blog, we share how we leveraged a design system to build Govern AI Assistant (GAIA), our AI Governance Agent, extending the four-layer substrate of an AI-first design system: governance, knowledge, transformation, and verification.

➡️ Check out our blog here and in the comments to learn more: https://www.credo.ai/blog/how-gaia-broke-our-design-enginering-handoff-and-what-we-built-instead---part-2

05/14/2026

Agentic AI adoption is accelerating faster than most enterprises are prepared for.

Databricks’ State of AI Agents 2026 report found a 327% increase in multi-agent workflow usage in just four months. At the same time, Gartner warned that 40% of agentic AI projects risk cancellation by 2027 without proper AI governance.

This is the defining AI inflection point: the shift from assistive AI to autonomous systems acting on behalf of the enterprise. That changes the governance equation entirely.

Boards, regulators, and customers will increasingly expect measurable trust artifacts that demonstrate:
➡️ What each AI system is authorized to do
➡️ Its sanctioned purpose and risk classification
➡️ Who approved it and under what controls
➡️ Whether decisions and actions are traceable

The emerging category of agentic AI governance is about establishing organizational control over autonomous AI systems, ensuring they operate within defined boundaries, accountability structures, and business intent.

Enterprise leaders should be asking:
➡️ Do we have a system of record for every AI use case?
➡️ Can we classify and govern risk consistently across agents?
➡️ Are approval workflows and accountability mechanisms traceable?

We created an Agentic AI Field Guide for enterprise leaders outlining what this agentic AI era demands, where adjacent tooling falls short, and where the market is headed.

🔗 Download our Field Guide here and let us know what you think in the comments:

Governance built for the speed of autonomous AI. Inside: six structural components, five readiness tests, and the regulatory frameworks taking effect in 2026.

05/13/2026

Announcing the general availability of Govern AI Assistant (GAIA), Credo AI’s AI Governance Agent.

AI governance teams no longer have capacity for manual review. They need intelligent triage and automation at the speed of agentic AI.

Our Govern AI Assistant (GAIA) automates the mundane tasks that slow governance teams down: intake, questionnaires, risk identification, control mapping.

All with cited suggestions, confidence scores, and full human review at every decision point.

Agent-powered AI governance is the breakthrough to AI adoption. Request your demo of GAIA today.

➡️ Read more here: https://www.credo.ai/blog/announcing-general-availability-of-govern-ai-assistant-gaia-credo-ais-ai-governance-agent