Barriers to AI adoption in enterprise content management

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Despite strong interest, AI adoption in ECM is stalled by key barriers: security, regulation, internal skill gaps, and integration challenges.

February 9, 20267 mins

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The promise of AI in enterprise content management (ECM) is undeniable. Yet despite the enthusiasm, most organizations find themselves at an impasse. They want to move forward with AI-driven capabilities, but practical, high-impact concerns continue to slow progress.

Findings from our recent customer survey reveal an interesting contradiction.* Ninety-eight percent of leaders globally say they are satisfied with their current document management systems (DMS) and ECM platforms. They credit these systems with improving scalability, workflow, and security. However, beneath this satisfaction lie critical pain points. More than 90% of leaders cite issues such as insufficient integration, data quality problems, and limited support for specialized tasks.

At the same time, interest in AI is extremely strong. Ninety-three percent of leaders using AI functions say their current capabilities meet or exceed expectations, especially across analytics, workflow automation, and summarization. Yet adoption remains limited because of several interconnected barriers, including security requirements, regulatory constraints, internal readiness gaps, and technical blockers related to integration and data maturity. Understanding how these issues overlap is essential for any organization aiming to modernize its content management ecosystem.

Data security as a non-negotiable foundation

Security and protection emerge as top concerns whenever AI enters the conversation.

Even though many organizations already use AI for intelligent extraction and predictive analytics, leaders remain cautious about how these capabilities interact with sensitive information. The challenge is adopting AI while maintaining confidentiality, privacy, and governance without compromise.

Organizations want AI to unlock efficiency and insight, but they also expect compliance to remain uncompromised. This is reflected in investment intent. Ninety-seven percent of global leaders say they are likely to invest in new DMS or ECM solutions if those platforms are driven by security and data needs.

Security must be a fundamental part of any AI-enabled ECM solution. In practice, being ready for AI and being prepared for enterprise-level security are inseparable priorities. Organizations that recognize this link are preparing themselves to move forward with confidence.

Regulatory restrictions are the industry reality

Regulation does more than influence the adoption of AI. In many sectors, it defines the boundaries of what is acceptable. The healthcare and banking, financial services, and insurance (BFSI) sectors illustrate this clearly.

In healthcare, security and protection consistently rank among the highest priorities. This reflects the responsibility of managing patient information governed by strict frameworks such as HIPAA. For these organizations, AI adoption is fundamentally tied to compliance.

Security and protection stand at the top of the healthcare sector’s priority list

Regulatory restrictions are the industry reality

BFSI organizations navigate a different but equally challenging environment. Their adoption of AI is often limited by vendor offerings still in pilot stages, features that do not align with BFSI workflows, or solutions that fail to meet specific regulatory expectations. This points to a disconnect between AI’s theoretical capabilities and what regulated industries require.

It is important to note that regulation does not reduce interest in AI. Leaders in these industries already recognize the value, and now the real question for them is how to utilize AI responsibly without increasing compliance risk.

Platforms that simplify rather than complicate compliance and embed governance and security into their architecture will be best positioned to support AI adoption in regulated sectors.

Internal expertise as the hidden constraint

Internal readiness often receives less attention than security or regulation, yet it remains one of the most influential barriers to AI adoption. The survey indicates that 32% of leaders aim to enhance their AI utilization but lack the necessary technical expertise to do so effectively.

This challenge appears in several ways. Many decision-makers report poor integration, inconsistent analytics, and insufficient vendor support. These problems slow down daily operations and create friction when new technologies are introduced.

Differences between roles are also important. IT decision-makers often say that AI features perform better than expected. Business decision-makers struggle more with digitizing and searching physical documents, a fundamental issue that must be addressed before AI can deliver meaningful value.

In BFSI, even organizations already using AI for search and natural language processing note that vendor limitations and feature gaps restrict their ability to expand the broader use of AI.

Across all regions, interest in AI is strong; however, without the right support structures, technical knowledge, and effective change management, many desired capabilities remain out of reach. Organizations require platforms that simplify AI adoption, automate manual tasks, elevate data quality, and integrate seamlessly into existing workflows. In other words, they need AI that supports the organization they have today, not the ideal version that would exist with unlimited resources.

Why AI has become essential rather than optional

Despite the barriers, the survey shows strong alignment across decision-makers. AI-driven capabilities now rank as the most compelling features in next-generation ECM platforms. Workflow automation powered by AI agents stands out as the top motivator, followed by AI-enhanced reporting, analytics, and summarization.

Decision-makers are prioritizing DMS/ECM solutions that offer AI-driven features

Why AI has become essential rather than optional

This indicates a shift in expectations. Leaders want platforms that address long-standing challenges such as complex data ecosystems, inconsistent workflows, and reliance on manual processes. AI is now seen as essential for:

Scalable and efficient document processing
More accurate and automated classification
Deeper insights into content usage and performance
Stronger and more reliable governance and compliance

Healthcare decision-makers, in particular, believe that AI will reshape the way their organizations manage and utilize content.

This shift reflects real operational pressure. Manual processes can no longer keep pace with the demands of modern enterprises.

The strategic role of consolidation

Right now, content often lives in multiple places—LOB apps, shared drives, email, legacy DMs—making it hard to know where the ‘official’ version is. Consolidation would eliminate duplicate storage and redundant searches.

APAC BFSI ITDM

The survey reveals a strong desire to consolidate multiple DMS and ECM systems into a single platform. Leaders believe consolidation reduces duplication, strengthens security, improves efficiency, and simplifies access. All of these benefits create a stronger foundation for the adoption of AI.

However, consolidation varies in complexity depending on the department. IT, Finance, and HR are easier to consolidate. Legal and Compliance remain the most challenging due to specialized workflows and strict documentation requirements.

Regional patterns also appear. Organizations in the United States (16%) are more likely to consolidate all departments at once, while APAC organizations show the strongest willingness to invest in modernization and consolidation, with 70% citing that they are very willing to consolidate, and 28% somewhat willing.

This matters for AI because fragmented ecosystems create integration and data-quality issues that become more difficult when AI is added on top. Consolidation creates a cleaner, more unified environment that supports the effective deployment of AI.

The path forward

The ECM landscape is evolving quickly, and AI is driving much of that change. The survey makes one point clear. Organizations are not held back by a lack of interest. They are held back by practical concerns that must be addressed directly.

Organizations that want to progress must strengthen several critical areas, including security and data protection, regulatory and compliance readiness, internal expertise and infrastructure, as well as technical issues related to integration and data quality.

At the same time, expectations for next-generation ECM platforms are becoming clearer. Decision-makers want AI-driven workflow automation, advanced reporting and analytics, predictive insights, automated classification and summarization, stronger integration, and security and governance that are built directly into the platform.

AI has become a core expectation for the future of DMS and ECM. Organizations that simplify their environments, enhance data readiness, and select platforms with robust AI and security foundations will be better positioned to overcome adoption barriers.

Ready to explore how secure AI-enabled content management can support your organization? Discover Iron Mountain’s InSight® DXP solutions designed to help you overcome adoption challenges while maintaining the security, governance, and compliance your enterprise requires.

_{*Findings from Iron Mountain Customer Survey, August 2025}