SAS AI Navigator Tackles Enterprise AI Sprawl

Companies Have a New Problem: AI Sprawl

AI adoption is moving rapidly inside businesses. Employees are using generative AI tools, developers are experimenting with different models, teams are building AI agents and companies are deploying AI applications into production.

The problem is that organizations may not always have a complete picture of which AI systems are actually being used.

SAS is addressing this problem with SAS AI Navigator, a new SaaS AI-governance solution that is now available through Microsoft Marketplace. The platform is designed to create a centralized inventory of an organization's AI use cases, models and tools, including LLMs, AI agents and open-source or SAS models. SAS

This matters because enterprise AI is becoming increasingly fragmented. One employee might use ChatGPT, another team could use Claude or Microsoft Copilot, developers may deploy an open-source model, while another department could build an internal AI agent. Without centralized visibility, security and compliance teams can struggle to understand what AI is being used and where.

SAS AI Navigator is designed to give organizations a unified view of these AI assets and connect them with internal policies and external regulations. SAS says the platform focuses on AI use cases where business impact occurs and can govern the models and agents supporting those use cases. SAS

The platform also supports AI governance throughout the lifecycle, helping organizations manage AI from experimentation through deployment and ongoing use. This is important because governance cannot stop when an AI model is first approved. Models can change, applications can expand and agents can gain new capabilities over time.

SAS says customers can access AI Navigator through Microsoft Marketplace, and the company is offering customers six months of free access. SAS

The bigger trend is the emergence of AI governance as its own enterprise software category.

Businesses previously focused on selecting the best AI model. Now they also need to answer basic questions: What AI do we have? Where is it being used? Which model or agent powers it? What policies apply? Who is responsible for it? And does its use meet regulatory requirements?

For Indian startups, enterprises and technology teams, this becomes increasingly important as AI adoption grows across departments.

The new enterprise AI workflow may look like:

Discover AI → Inventory it → Assess risk → Apply policies → Monitor → Govern

AI sprawl may be a new problem, but tools such as AI Navigator show that companies are beginning to build a new layer of infrastructure around it: knowing exactly what AI they have and keeping it under control.