The Default Document AI Decision Is Starting to Crack

For years, most organizations didn't actively choose their document AI solutions. They inherited them. Hyperscale computing providers dominated the tech stack, and organizations defaulted to using whatever document AI tools, like OCR and form extraction, were bundled into the agreement. This approach made procurement simple and allowed internal AI teams to prototype quickly. It was convenient and “good enough” for early experimentation. However, as document AI projects move from pilot to production, this default thinking is now under pressure.

This shift reflects a broader trend in the market, as highlighted by IDC’s new research on Intelligent Document Processing (IDP), sponsored by Tungsten Automation. Buyers are actively reassessing their document AI providers, with many decision-makers prioritizing accuracy, governance, and time-to-value as key drivers for change.

This blog draws on key insights from IDC’s latest report to examine how buyers view specialized IDP vendors, hyperscale computing providers, and internal-build projects, and how those choices shape risk, cost, and access to trusted AI-ready data in business-critical workflows.

How Hyperscale Computing Providers Ended Up Owning Document AI  

IDC’s survey of 1,262 mid-market and enterprise organizations shows how strongly hyperscale providers captured the first wave of IDP.

74% of organizations polled currently use a hyperscale computing provider as their primary IDP solution.

Many enterprises treated IDP as a byproduct of a broader cloud strategy, bundling it into large infrastructure agreements and centralizing ownership under the same IT and procurement stakeholders.

The IDC report notes, however, that at least 30% of IDP end-user organizations already use more than one solution, suggesting that for many, the hyperscaler default isn't fully meeting their needs.

Together, these data points suggest that while document AI often entered the enterprise through the existing hyperscaler stack, that default does not meet every requirement, and many teams are looking to augment where solutions fall short.

Why the Default is Being Challenged: What Buyers Really Want from Document IDP

IDC’s data shows that 63% of organizations are actively reconsidering their current IDP setup, with respondents saying they are likely (if not very likely) to change their IDP solution approach within the next 12 months.

This statistic indicates that many organizations originally deployed IDP when it was viewed as a simple capture-and-extraction tool. However, as AI capabilities have advanced, they now need it to operate as a critical document and data intelligence layer that impacts customers, regulators, and financial outcomes. In short, organizations are raising their expectations for what document AI solutions must deliver.

With that in mind, IDC identified four themes guiding future deployment decisions:

Accuracy and Quality 

42% of respondents cite accuracy and quality of outputs as a top factor in their deployment decisions.

When document AI informs loan decisions, claims handling, clinical workflows, or compliance reporting, organizations depend on consistent accuracy across messy, variable real-world documents. Controlled demos rarely match those commonplace scenarios, so buyers now judge providers on how consistently they perform on their own documents, at production scale.

Time-to-Value

32% of respondents highlight time-to-value as a primary measure of solution performance.

Businesses cannot wait through long build cycles, extensive prompt engineering, or continuous retraining before they see ROI. They want strong, out-of-the-box capabilities that get them into production quickly and fit inside existing delivery cadences and resource constraints.

Customization and Model Adaptability

Buyers prioritize model adaptability, with 31% of respondents naming it as a key measure.

As use cases expand, “last leg” tuning is vital for zeroing in on the details of a customer’s use case and maintaining consistency. More specifically, organizations are looking for platforms that let them adjust models for specific document types or business rules via low/no-code configuration tools or even natural language prompts within a conversational AI interface.

Data Residency and Compliance

31% of organizations identify data residency and compliance as critical requirements for deployment decisions.

As document AI becomes a core part of enterprise strategy, organizations are scrutinizing human-in-the-loop (HITL) controls, exception handling, validation workflows, and auditability. Plus, they must be able to consistently enforce regional compliance constraints. Providers that demonstrate clear, practical governance controls at this level are far more likely to be shortlisted and scaled into high-risk workflows.

Why Specialized IDP Vendors are Gaining Ground

IDC's findings indicate that many buyers see specialization in pure-play vendors as better aligned with production-grade IDP requirements.

For example, when it comes to out-of-the-box accuracy, 37% of respondents perceived pure-play IDP vendors as stronger, compared with 28% favoring hyperscale platform providers.

That gap widens among IT and data professionals who are closer to implementation projects and long-term maintenance. Perceptions are similar on customization and tuning.

39% of respondents say pure-play solutions are easier to customize than hyperscale computing providers' solutions (28%).

This advantage is important for long-running, high-volume workflows where last-mile tuning and continuous improvement define long-term success.

Governance and compliance are more evenly matched, with 33% of respondents favoring pure-play vendors versus 30% for hyperscale computing providers.

However, IDC notes that pure-play vendors are perceived to lead in operational governance areas such as HITL, exception handling, and validation workflows. These are precisely the control points that determine whether IDP can be trusted in regulated and high-risk processes, such as loan approvals and claims handling.

Even in areas historically seen as hyperscaler strengths, such as cloud and data stack integration, the gap is narrowing. Specialized IDP vendors now sit close to parity in customer perception, helped by tighter integration strategies and partnerships with major cloud platforms.

These findings reflect a broader shift in what organizations now expect from document AI. It is no longer enough to capture and extract data. Organizations must understand and transform unstructured information into trusted, AI-ready data and orchestrated action across downstream agents, systems, and workflows. Specialized IDP vendors are perceived as better positioned to deliver that.

Rethinking Your Organization’s “Default” IDP Decisions

The default document AI decision is moving off autopilot. Specialized IDP vendors now match hyperscale computing providers on integration and scalability, while maintaining a clear edge on accuracy, governance, and customization in complex, document-heavy use cases.

The organizations that will get the most from document AI are those that evaluate their options against production criteria, not procurement convenience. At the heart of that evaluation is a simple question: which solution reliably turns unstructured documents into trusted data that AI agents and workflows can act on. TotalAgility® from Tungsten Automation is built precisely for these demands.

To see the full data set and guidance behind these trends, including industry-specific predictions and detailed buyer perceptions, download the IDC InfoBrief “Shifting Intelligent Document Processing Solution Deployments in the AI Era.”