Agentic AI projects are rapidly moving from experimentation to being deployed in enterprises everywhere. Autonomous agents that can reason, plan, and act promise significant revenue growth and productivity gains. At the same time, they expose organizations to new operational and security risks that many teams are not prepared to manage.
The data is sobering. Recent studies have shown that up to 95% of generative AI projects fail to deliver measurable business value, and Gartner predicts that over 40% of agentic AI initiatives will be canceled by 2027. Most failures trace back to the same root causes: unclear ROI, governance and security gaps, and fragile integrations that don’t scale beyond proof-of-concept.
As organizations evaluate vendors and platforms to enable agentic AI, the difference between success and failure often hinges on whether the vendor truly understands how autonomous agents behave in real enterprise environments and how adversaries will exploit them. In this blog, we’ll break down what the right agentic AI enablement partner delivers, and what’s missing in many of today’s solutions.
What to Look for in an AI Gateway Partner
A strong agentic AI enablement partner doesn’t just help teams experiment faster. It provides the foundation needed to move safely and confidently from prototype to production without sacrificing security, governance, or operational control.
Core Functionality: From Prototype to Production Without Rebuilds
Agentic AI systems are non-deterministic by nature. You rarely get predictable behavior on the first iteration, which makes rapid experimentation essential. And it’s hard to see how things work in a sandbox environment devoid of the apps and data that need to be accessed. Enterprises need a way to connect AI agents to real applications and data; securely, consistently, and without massive engineering overhead. The right solution enables organizations to:
- Make existing applications and APIs agent-ready in minutes, not months
- Avoid custom code and fragile point integrations
- Move from pilot to production without rebuilding infrastructure from scratch
In practice, this means transforming internal, external, and SaaS applications into dynamically discoverable, agent-accessible resources while preserving enterprise-grade security and controls like authentication, authorization, monitoring, and guardrails.
Advanced Features: Guardrails for Autonomous Behavior
Unlike traditional software, agentic AI doesn’t just respond, it acts. That makes guardrails essential, not optional. The right solution provides policy-driven controls that constrain what agents can access, how frequently they can act, and how much risk they can introduce. Key capabilities include:
- Real-time monitoring and visibility into agent, user, and application interactions
- Policy-driven guardrails that prevent agents from abusing APIs, driving excessive spend, or accessing unauthorized systems
- Risk-aware enforcement, where anomalous or high-risk behavior can be throttled, blocked, or escalated to human review
Integration & Compatibility: APIs as the Control Plane
Every action an agent takes, such as querying data, triggering workflows, or invoking tools, flows through APIs. Working with a vendor that has extensive knowledge of APIs and business logic offers many downstream benefits. For example, Cequence can automatically generate API specs that can then be used to AI-enable applications, a significant time savings over creating the specs and confirming their operation manually.
Performance & Scalability: Designed for Enterprise Reality
Enterprise agent traffic doesn’t always scale gradually. It spikes, shifts, and changes as use cases expand and contract. Choose a vendor whose design infrastructure that can handle sudden surges in agent activity and support diverse deployment models, including cloud, private cloud, on-premises, and hybrid environments.
It’s also important to look at how the solution is deployed. Some organizations may find a SaaS model acceptable, while others require an on-premises solution. This flexibility is critical for long-term viability. Solutions locked into a single deployment model or rigid architecture often fail as enterprise IT strategies evolve.
Compliance & Governance: Security Built In, Not Bolted On
One of the most common causes of agentic AI failure is the attempt to build fast and “add security later.” Look for solutions that reverse this pattern by embedding foundational security into the architecture itself:
- Authentication and authorization capabilities that integrate with enterprise IdP
- Built-in guardrails to constrain agentic behavior
- Full audit trails of agent actions
Also important is support for Human-in-the-Loop controls, allowing automated systems to escalate decisions when uncertainty or risk thresholds are reached. Instead of treating security and governance as downstream concerns, a good solution embeds them directly into the enablement layer from day one.
What’s Missing in Other AI Gateway Solutions
Many agentic AI offerings prioritize speed to prototype over readiness for production. As a result, organizations often suffer from blind spots and missing security controls, forcing a choice between delaying production deployment or risking security incidents. Common gaps include:
- Limited visibility into user and agent behavior and API usage
- Reactive security controls that detect issues only after damage is done
- Lack of governance, making it impossible to explain or defend AI-driven actions
- Custom integrations that don’t scale, creating long-term technical debt
- No protection against rogue MCP servers or evolving protocols
The result is a familiar pattern: promising pilots that stall in production, growing security anxiety, and fragmented AI initiatives spread across teams with little oversight.
Customer Impact: From Experimentation to Sustainable Adoption
Enterprises using the Cequence AI Gateway have been able to move agentic AI projects from prototype to production without re-architecting their workflows. Existing projects that had been underway for most of a year and then stalled were accelerated into production in days with the AI Gateway. Since security, authentication, authorization, and guardrails are built in, organizations can prove their agentic AI projects work as planned and move into production with the click of a button while maintaining the controls enterprises expect. The result is not just faster deployment, but agentic AI that remains usable and secure while it’s being evaluated and as it scales.
Key Takeaways: Why Cequence is the Best AI Gateway Partner
The difference between successful and failed agentic AI initiatives isn’t ambition, it’s the infrastructure and expertise surrounding it. The right solution provider combines deep API knowledge with enterprise-grade security, flexible deployment options, and measurable time-to-value. In a market where failure is more common than success, these capabilities separate platforms that merely enable experimentation from those that support real business outcomes.
Final Words
Agentic AI is ready to deliver real productivity gains, but only if it’s deployed on a foundation built for enterprise reality. If you’re ready to move beyond pilots and adopt agentic AI with confidence, now is the time to evaluate AI enablement partners for enterprise readiness. Learn how Cequence helps enterprises deploy agentic AI safely, at scale, and without sacrificing control – request a demo today.
