How to solve agent sprawl

For anyone working in IT and familiar with SaaS sprawl, the idea we’ll soon end up with agent sprawl may set off alarm bells.

<![CDATA[ <article> <p>For anyone working in IT and familiar with SaaS sprawl, the idea we’ll soon end up with agent sprawl may set off alarm bells. Agent sprawl refers to the rapid, uncoordinated deployment of AI agents across departments, each built on different models, governed by different rules, and often disconnected from core <a href="https://www.techradar.com/best/best-small-business-software">business</a> workflows. </p><p>But while SaaS sprawl caught enterprises off guard, this time organizations have no excuse, and need to put measures in place now to avoid repeating the same mistakes. However, right now, most organizations are building agents in isolation and optimizing for local <a href="https://www.techradar.com/best/best-productivity-apps">productivity</a> rather than enterprise value.</p><p>Thankfully, with the right control layer funneling every agent through the same governance and <a href="https://www.techradar.com/news/best-internet-security-suites">security</a> standards within an organization, the agent-powered future can be far safer, scalable and simple.  </p><h2 id="agent-sprawl-is-inevitable">Agent sprawl is inevitable </h2><p>Just like SaaS before it, agent sprawl is already happening. Each department within organizations is experimenting with different agent technologies to address specific challenges or work more efficiently.</p><p>A sales team may deploy a <a href="https://www.techradar.com/best/the-best-crm-software">CRM</a>-based AI assistant to qualify leads, while developers build their own coding agents, and marketing adopts a separate content generation tool. Each delivers local value, but none are aligned or connected to the other, creating a familiar-looking sprawl.</p><p>This fragmentation introduces a range of challenges that will only increase over time. With no single owner responsible for how agents are deployed or monitored, there’s a lack of governance and oversight. Security risks increase as agents gain access to sensitive systems without consistent controls.</p><p>Teams may unknowingly duplicate efforts, solving the same problems in parallel with different tools. At the same time, many agents are deployed without clear links to business outcomes or understanding the wider context, making it difficult to measure return on investment and distinguish meaningful innovation from experimentation. Lots of <a href="https://www.techradar.com/best/best-ai-tools">AI tools</a> may be exciting, but deliver far more style than substance. </p><p>Is sprawl inevitable? Yes, probably. So the question now becomes, how do we control it? </p><h2 id="the-role-of-orchestration">The role of orchestration</h2><p>Having an orchestration layer can bring order to this complexity by creating consistency in how agents are governed, secured and deployed across the business. For SaaS applications, orchestration provides visibility into what tools already exist and gives a clear view of enterprise workflows.</p><p>With agents, it outlines what agents are already available and how they operate, while also controlling how they access data, tools and existing technology. Orchestration is the critical element that turns agents from experiments into scalable business <a href="https://www.techradar.com/best/best-infrastructure-management-service">infrastructure</a>, for example, assigning agents to business workflows and measuring their performance against real outcomes.</p><p>Too often, we see enterprises experimenting with different agents that have no connection to the core business processes and goals, meaning they fail to deliver any ROI. For example, some portions of a business simply do not require AI technology and will unlikely see benefits in the same way as another department. Orchestration can unearth and filter out agents that are unnecessary, saving businesses money.  </p><h2 id="building-trust-in-ai-driven-enterprise">Building trust in AI-driven enterprise </h2><p>Rather than trusting individual agents, organizations should focus on trusting the system that governs them.</p><p>This is where orchestration becomes a trust layer, ensuring every agent operates within clearly defined boundaries with consistent oversight and accountability. Instead of individual teams managing risk in siloes, organizations can centralize control while still enabling innovation across different departments and business functions.</p><p>In the same way orchestration brought order to SaaS sprawl, it can do the same for the next wave of enterprise AI. It brings the same ease, security and integration with existing SaaS tools, while ensuring only high-value agents make it into production, supporting innovation and keeping within the business goals and purpose.</p><p>As agents become embedded across every function, orchestration will shift from a technical layer to a core enterprise capability. The winners will be those who can control, connect and trust their agents at scale.</p><p><em></em><a href="https://www.techradar.com/pro/best-ai-website-builder"><em>We've featured the best AI website builder.</em></a></p><p><em>This article was produced as part of </em><a href="https://www.techradar.com/pro/perspectives" target="_blank"><em>TechRadar Pro Perspectives</em></a><em>, our channel to feature the best and brightest minds in the technology industry today.</em></p><p><em>The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. 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