Cloudera

Cloudera Evolve London: 91% of organisations say data unfit for AI purposes

Cloudera research finds only 9% of organisations have fully AI-ready data, with siloed data and security major barriers to enterprise AI success, as well as gender bias in AI development

The huge majority of organisations do not have data usable for artificial intelligence (AI), according to research from big data supplier Cloudera.

Findings presented in a worldwide report, The evolution of AI: The state of enterprise AI and data architecture, reveal that only 9% of IT leaders surveyed said all their data is available and usable for AI, and 38% reported that most of their data is accessible.

The survey, commissioned by Cloudera and carried out by market research consultancy Researchscape, polled 1,574 IT leaders from EMEA, the US and Asia-Pacific working at companies with more than 1,000 employees. The research was done in July 2025, and its findings were published this week to coincide with the London version of the supplier’s Evolve25 event.

At the same event, Cloudera also published UK research, bespoke for the conference, that suggested a lack of diverse gender representation in senior AI roles will lead to biased AI outputs.

The UK survey of 100 female IT decision-makers, carried out by market research firm Sapio, found that more than two-thirds (68%) are worried about a lack of female representation in senior AI roles. More than half (56%) believe this lack of representation will lead to biased AI outputs, with 57% saying that AI is inherently biased since the CEOs of AI companies are predominantly male. 

Mary Wells, chief marketing officer at Cloudera, said: “Gender inequality remains a significant challenge in the technology sector. While there has been progress, we still face substantial barriers.

Artificial Intelligence is a catalyst for positive change, with the potential to reshape businesses, industries and economies. However, without diverse groups participating in AI development and strategy from the beginning, we risk perpetuating old biases.” 

Some 82% of the respondents believed a gender imbalance still exists in the technology sector, with four in five (80%) saying gender equality is a perfunctory tick-box exercise at their company.

Artificial Intelligence is a catalyst for positive change, with the potential to reshape businesses, industries and economies. However, without diverse groups participating in AI development and strategy from the beginning, we risk perpetuating old biases
Mary Wells, Cloudera

The biggest challenges holding female IT leaders back from senior AI roles were found to be gender bias in recruitment and promotions (68%), limited upskilling opportunities (66%) and, in line with the findings of the global research, data that isn’t AI-ready (60%).

With respect to the global data readiness for AI research, Sergio Gago, chief technology officer at Cloudera, said: “In the last 12 months, AI has shifted from a strategic priority to an urgent mandate, actively reshaping operations and redefining the rules of competition.

“But our survey shows that challenges around security, compliance and data utilisation remain. Organisations need access to all of their data, wherever it resides and in any form, to govern it securely and unlock real-time and predictive insights.”

The majority of those surveyed (86%) declared themselves to be “data driven”. But they also face substantial difficulties when it comes to supporting AI workloads.

Data integration was cited by 37% as the biggest problem. Also thorny are storage performance (17%), computer power (17%), lack of automation (17%) and latency (12%). Some 61% of respondents said siloed data had frustrated their ability to run AI activities at scale.

Perhaps unsurprisingly, securing data used in AI systems emerged as a pain point for those surveyed. Although 77% expressed confidence in their organisation’s ability to secure data used for AI, the research found significant concerns in relation to data leakage during model training (50%), unauthorised data access (48%), insecure third-party AI tools (43%), lack of visibility or explainability in model outputs (39%), and model manipulation or poisoning (35%).

Nevertheless, the speed of AI adoption is rapid, according to the research, with 21% saying AI is already fully integrated into their business processes, 54% saying AI is significantly integrated, and 21% saying it is somewhat integrated. 

Some 70% of respondents said they have already achieved significant success with AI initiatives.

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