April 2026
PYMNTS Data Book

Scaling Enterprise AI: Why Organizational Readiness Now Determines ROI

Enterprise AI may be advancing fast, but most companies are still not built to get the full value from it. This report shows that 71% of senior technology executives say their own organization limits AI performance more than the technology does, while just 15% say their data environments are mostly integrated. The findings reveal a growing gap between confidence in AI readiness and the operational reality inside large enterprises.

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    Enterprise AI appears to be delivering results. The issue now is whether companies can use the technology robustly. This data book shows that the main adoption barriers aren’t the technology itself, but the data, systems and internal structures needed to put it to work at scale.

    Enterprise AI Readiness Gap

    Shifted Bottleneck

    Seventy-one percent of enterprises say their own organization limits their AI performance more than the technology does. Enterprise leaders have moved past the question of whether the technology works with an affirmative answer. Now they’re asking whether their companies are ready to support the technology. This data book shows that questions about organizational readiness outweigh concerns about AI capabilities by a wide margin.

    Enterprise AI Adoption Barriers

    Data quality is the most common obstacle, cited by 63% of executives. But the barriers to AI adoption are manifold. Companies are dealing with several at once, led by data quality, budget limits, governance processes and unclear ownership of AI-fueled processes. That suggests problems with the technology are tied to business operations, not to the technology tool.

    Missing Fix

    Integration with existing technological systems is the single biggest limiting factor, even more than data quality. When executives were asked to name just one barrier, melding with existing systems came out on top. This signals that even strong data can’t drive results if it can’t move across the business through AI-backed processes.

    Enterprise AI Adoption

    Companies have embedded AI most deeply in data and technology teams, but its use is much less mature elsewhere. The technology is most ensconced in data and growth functions. Areas such as HR, strategy, risk and supply chain management remain earlier in the adoption cycle, indicating a broader enterprise-readiness gap.

    AI Confidence Gap

    Ninety-nine percent of enterprises are confident in their data governance, but only 15% say they’ve mostly integrated their data across the company. This is the sharpest disconnect in the report. Leaders say they’re ready from a governance standpoint, but the underlying data environment tells a different story. The gap could slow efforts to scale AI across the enterprise.

    Methodology

    “The Enterprise AI Readiness Gap” is based on findings from the April 2026 edition of The Enterprise AI Benchmark Report. The findings come from a survey of 65 verified senior technology executives at U.S. companies with at least $1 billion in annual revenue in the retail, manufacturing, wholesale, distribution, eCommerce and marketplace sectors. The survey was conducted from Feb. 12–27, 2026, and covered leaders responsible for or most familiar with AI strategy, adoption and operations.

    About

    PYMNTS INTELLIGENCE

    PYMNTS Intelligence is a leading global data and analytics platform that uses proprietary data and methods to provide actionable insights on what’s now and what’s next in payments, commerce and the digital economy. Its team of data scientists includes leading economists, econometricians, survey experts, financial analysts and marketing scientists with deep experience in the application of data to the issues that define the future of the digital transformation of the global economy. This multi-lingual team has conducted original data collection and analysis in more than three dozen global markets for some of the world’s leading publicly traded and privately held firms.

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