Informatica from Salesforce, together with Deloitte, unveiled the “CDO Insights 2026: Data governance and the trust paradox of data and AI literacy take centre stage”, revealing that while organisations are rapidly accelerating their use of AI, many face challenges with data readiness, data and AI literacy, required to realise the full value of their AI investments.
The study shows that AI has firmly moved from experimentation to execution. Nearly seven in ten organisations (69%) have now embedded generative AI into business practices, up significantly from 48% in 2024 and 45% in 2023. Momentum is also building around more advanced use cases, with 47% of organisations already adopting agentic AI which can act autonomously to achieve defined goals.
However, as adoption rises, data leaders are increasingly concerned about the foundations underpinning these initiatives. According to the report, 91% say data reliability remains a barrier to moving more generative AI initiatives from pilot to production, while 90% are concerned that new AI pilots are progressing without resolving the data reliability issues uncovered by earlier efforts.
This caution from data leaders stands in stark contrast to the broader workforce’s perception, giving rise to what Informatica terms a ‘trust paradox’. While data and AI leaders remain acutely aware of data quality and governance shortcomings, 65% of respondents say that most or all their organisation trusts the data being used in AI efforts.
As a result, data leaders believe targeted training is now critical to closing this gap and enabling AI to scale safely and effectively. More than three quarters (76%) say their company’s visibility and governance has not fully kept pace with employees’ use of AI. At the same time, 75% report that their workforce needs stronger data literacy skills, while 74% say greater AI literacy is required.
The urgency is heightened by the pace of change. Almost a third of organisations (31%) expect to adopt agentic AI by the end of this year, yet a lack of agentic AI experience already ranks among the top three challenges preventing AI agents from reaching production. Without immediate investment in skills and governance, organisations risk falling further behind their own AI ambitions.
Encouragingly, the findings also suggest that upskilling could reduce overreliance on external providers and accelerate innovation. Today, 54% of organisations plan to use vendor-supplied AI agents, compared to 44% that expect to develop them internally. On average, organisations anticipate partnering with eight separate vendors to support AI management priorities in 2026, most commonly to improve data trust. Building stronger internal data and AI capabilities could help organisations become more self-sufficient and move faster.
“The promise of AI is immense, but so are the risks if you don’t have confidence in a reliable data foundation,” said Emilio Valdés, SVP Sales International, Informatica from Salesforce. “Our CDO Insights 2026 report reveals a ‘trust paradox’, although employees generally trust the data used for AI, many are lacking in data and AI literacy skills, and organisations lack underlying AI governance structures for achieving the responsible and ethical outcomes they desire. This poses significant risk exposure and hurts confidence in AI initiatives. For AI to deliver its transformative outcomes and ROI, organisations must prioritise data reliability, invest in rigorous AI governance and upskill their workforce to help ensure their AI-driven decision making is based on trusted, high-quality data and everyone in the organisation knows how to use it responsibly.”
Commenting on the regional implications, Yasser Shawky, Vice President, Emerging Markets (MEA) at Informatica from Salesforce, said, “Across the Middle East, we are seeing increased momentum around AI, driven by national strategies, digital government programmes and large-scale enterprise transformation. Our findings show that ambition is not the challenge, readiness is. To sustain this pace, organisations in the region must ensure that governance, data management and skills development evolve just as quickly as AI adoption itself. Those that invest now in data trust and AI literacy will be far better positioned to turn innovation into lasting competitive advantage.”
Despite the challenges, there is positive news for data leaders. The vast majority (86%) expect their organisation’s investment in data management to increase in 2026, reflecting a growing recognition that data is critical to AI success. “The priority now is to ensure these investments are directed where they deliver the greatest impact. Strengthening data reliability, modernising governance, and embedding AI and data literacy across the workforce should all be top priority,” Shawky concluded.
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