System sprawl is blocking enterprise AI scale, study finds

A new Forrester Consulting study commissioned by Simpplr says fragmented systems, missing context and security gaps are slowing enterprise AI adoption more than model quality. The findings point to unified digital workplace platforms as a growing fix for IT teams trying to scale AI safely.

Why it matters: - Enterprise AI is running into an operational problem, not a model problem. - Fragmented systems make it harder for AI to find context, deliver accurate answers and operate with the governance companies need. - Security and access control risks are also slowing adoption, which raises the cost and complexity of scaling AI across the business.

What happened: - Business Reporter published an article featuring Randall Kerr, vice president of technology at Simpplr. - Kerr discussed findings from a new study commissioned by Simpplr and conducted by Forrester Consulting. - The 2026 survey covered 310 senior IT decision-makers in North America and the UK. - Forty-five percent of respondents said missing organizational context is the main reason AI fails to meet expectations. - Eighty-five percent said fragmented data sources and knowledge systems must be unified and governed for AI to succeed. - Forty-nine percent cited security and access control risks as their top operational challenge. - Seventy-eight percent said stronger security frameworks are needed before AI can scale safely.

The details: - The study says organizations are dealing with disconnected digital environments across shared drives, HR systems, messaging platforms, helpdesk tools and project management applications. - Those systems often do not integrate effectively, which limits AI performance and makes governance harder. - Kerr said the findings point to an execution gap rather than a knowledge gap. - Kerr said IT leaders already understand that fragmented data undermines AI and that governance frameworks need to mature. - Kerr said the harder question is where to start, especially when the systems creating the problem are deeply embedded, widely used and politically difficult to replace or consolidate. - The report highlights growing interest in AI-powered digital workplace platforms that unify organizational knowledge with governance, identity management and consistent access controls. - Seventy-five percent of IT leaders said they are interested in adopting such platforms. - A quarter of respondents said they have already adopted such platforms. - Respondents tied those platforms to better employee productivity, operational agility and employee experience. - Respondents also said these platforms can help AI systems deliver more accurate and reliable results. - Simpplr describes its product as an AI-powered intranet that unifies the digital workplace and brings people, trusted knowledge, apps and agents into one experience. - Simpplr says its platform uses an EX knowledge graph and enterprise-grade security and governance. - More information is available in the full article.

Between the lines: - The survey suggests many enterprises have already identified the core barrier to AI scale: poor knowledge architecture and weak governance, not lack of enthusiasm. - The interest in unified workplace platforms signals a shift toward infrastructure decisions that treat AI readiness as an enterprise data and access problem. - Security appears to be part of the same bottleneck, since leaders want AI tools that can scale without exposing sensitive information or creating inconsistent permissions.

What’s next: - Businesses trying to scale AI are likely to keep consolidating fragmented systems and tightening governance frameworks. - Demand may grow for platforms that combine search, knowledge management, identity controls and workflow access in one environment. - The pace of adoption will likely depend on whether IT teams can simplify system sprawl without disrupting day-to-day work.