{"id":137431,"date":"2026-03-25T12:31:17","date_gmt":"2026-03-25T12:31:17","guid":{"rendered":"https:\/\/www.intelligentcio.com\/me\/?p=137431"},"modified":"2026-03-25T12:31:18","modified_gmt":"2026-03-25T12:31:18","slug":"only-7-of-enterprises-are-ai-ready-study-finds","status":"publish","type":"post","link":"https:\/\/www.intelligentcio.com\/me\/2026\/03\/25\/only-7-of-enterprises-are-ai-ready-study-finds\/","title":{"rendered":"Only 7% of enterprises are AI-ready, study finds"},"content":{"rendered":"\n

A new study from Cloudera and Harvard Business Review Analytic Services reveals that while enterprises are accelerating AI adoption, most lack the data readiness needed to operationalise it at scale, exposing a widening gap between ambition and execution.<\/em><\/p>\n\n\n\n

Cloudera announced findings from a new global study conducted by Harvard Business Review Analytic Services with Cloudera, revealing that while enterprises recognise AI\u2019s transformative potential, most remain unprepared to operationalise it due to persistent data readiness challenges.<\/p>\n\n\n\n

In the Middle East, where governments and businesses are aggressively driving AI adoption as part of Digital Transformation agendas, the gap between ambition and readiness is particularly pronounced. Despite strong investments in AI technologies, many organisations are still grappling with fragmented data systems, governance challenges and skill shortages, which slow down the translation of AI potential into operational impact.<\/p>\n\n\n\n

The report, Taming the Complexity of AI Data Readiness<\/em>, surveyed more than 230 members of the Harvard Business Review audience, all involved in their organisation\u2019s AI data decisions in October 2025 and revealed a clear imbalance in enterprise AI progress. While organisations are accelerating AI initiatives, their underlying data foundations are not keeping pace. Only 7% say their organisation\u2019s data is completely ready for AI adoption and more than one-quarter (27%) report their data is not very or not at all ready, highlighting a growing gap between AI ambition and operational readiness.<\/p>\n\n\n\n

Data quality perception issues<\/strong><\/p>\n\n\n\n

Despite widespread AI experimentation, foundational data issues remain. Seventy-three percent of respondents say their organisation should prioritise AI data quality more than it currently does and an equal percentage report that their organisation has found the processing and preparing of data for AI to be challenging.<\/p>\n\n\n\n

The top obstacles when it comes to preparing data for AI include:<\/p>\n\n\n\n

\u2022 Siloed data\/difficulty integrating data sources (56%)<\/p>\n\n\n\n

\u2022 Lack of a clear data strategy (44%)<\/p>\n\n\n\n

\u2022 Data quality\/bias issues (41%)<\/p>\n\n\n\n

\u2022 Regulatory constraints on data use (34%)<\/p>\n\n\n\n

Leadership wants a data strategy<\/strong><\/p>\n\n\n\n

Enterprise leaders increasingly recognise that AI is no longer a future initiative; it is a present operational mandate. Yet most organisations are still formalising the data foundations required to scale it responsibly and effectively.<\/p>\n\n\n\n

\u2022 While only 23% say their organisation has an established data strategy for AI adoption, more than half (53%) are actively developing one.<\/p>\n\n\n\n

\u2022 Protecting sensitive data and privacy (59%), data quality (46%) and data governance (41%) rank as the most critical components of those strategies.<\/p>\n\n\n\n

Innovation may capture headlines, but durable competitive advantage depends on modern, governed data architectures capable of operating seamlessly across multi-cloud, data centre, edge and hybrid environments.<\/p>\n\n\n\n

At the same time, expectations for Agentic AI are accelerating, reflecting a shift from experimentation to operational reinvention.<\/p>\n\n\n\n

\u2022 Nearly two-thirds (65%) of respondents expect many of their organisation\u2019s business processes will be augmented or replaced by Agentic AI in the next two years.<\/p>\n\n\n\n

\u2022 Forty-seven percent say their organisation believes Agentic AI can solve its data quality issues.<\/p>\n\n\n\n

As organisations shift from applications to intelligent agents, scalable data pipelines, consistent governance and cloud-like experiences across environments are becoming increasingly essential.<\/p>\n\n\n

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\u201cAcross the Middle East, organisations are accelerating AI adoption as part of broader national Digital Transformation agendas. However, the challenge many enterprises face today lies in ensuring their data environments are ready to support AI at scale.<\/p>\n\n\n\n

\u201cFragmented systems, evolving governance frameworks and the complexity of operating across hybrid and multi-cloud environments continue to slow progress. As AI capabilities advance, particularly with the emergence of agentic systems, organisations will need to prioritise trusted data, strong governance and modern data architectures to translate AI ambition into measurable business impact,\u201d said Ahmad Shakora, Group Vice President, South-META, Cloudera Middle East.<\/p>\n\n\n\n

Today\u2019s enterprises operate in complex, distributed data estates spanning clouds, data centres and edge environments, yet mission-critical data often remains in on-prem environments due to sovereignty, security, cost and compliance requirements. Bridging this divide requires architectures that can securely operationalise AI across hybrid environments without forcing data movement or compromising control.<\/p>\n\n\n\n

Cloudera addresses this challenge by converging public cloud and enterprise data centres to deliver a unified, cloud experience in hybrid environments across the entire data estate. Built on an open-source foundation, it powers AI across more than 25 exabytes of enterprise data worldwide.<\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

A new study from Cloudera and Harvard Business Review Analytic Services reveals that while enterprises are accelerating AI adoption, most lack the data readiness needed to operationalise it at scale, exposing a widening gap between ambition and execution. Cloudera announced findings from a new global study conducted by Harvard Business Review Analytic Services with Cloudera, […]<\/p>\n","protected":false},"author":4189,"featured_media":137434,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[331,430,1493,6,15994,13],"tags":[16702,22080,3355,1050,9460,11528,7453,18400,22251,22252,908,16000,615,3430],"class_list":["post-137431","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-cloud","category-features","category-government","category-insights","category-middle-east","category-top-stories","tag-ai-adoption","tag-ai-readiness","tag-artificial-intelligence","tag-business-intelligence","tag-cloud-data","tag-cloudera","tag-data-governance","tag-data-quality","tag-data-readiness","tag-data-strategy","tag-digital-transformation","tag-enterprise-ai","tag-harvard-business-review-analytic-services","tag-machine-learning"],"acf":[],"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/posts\/137431","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/users\/4189"}],"replies":[{"embeddable":true,"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/comments?post=137431"}],"version-history":[{"count":3,"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/posts\/137431\/revisions"}],"predecessor-version":[{"id":137437,"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/posts\/137431\/revisions\/137437"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/media\/137434"}],"wp:attachment":[{"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/media?parent=137431"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/categories?post=137431"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.intelligentcio.com\/me\/wp-json\/wp\/v2\/tags?post=137431"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}