- Data and AI skills training is essential to get the most out of AI, reports claim
- Managers are concerned about data quality, security and lack of agent expertise
- Budgets may be increasing, and companies are spending on upskilling employees
European AI adoption is on the rise, but new Informatica research suggests there’s still a long way to go to build proper trust in the technology.
The majority (96%) of data leaders say their employees need more training to use AI responsibly, with data skills (82%) proving to be a higher priority than AI skills (71%) per se.
The report reveals a so-called ‘paradox of trust’, where employees trust AI tools and the data behind them, despite not having actually developed the skills to use it responsibly.
AI is in full swing, but it is held back by a paradox of trust
By the end of the first quarter of 2026, four out of five (79%) European companies expect to have introduced generative AI into their workflows, with almost as many (68%) also starting to pilot agent AI.
Top use cases include improving decision-making, boosting collaboration, optimizing internal processes and improving the customer experience.
But despite this all-in approach, there is a distinct lack of thought for the bigger picture beyond actual implementation. Three-quarters (77%) of European companies admit AI visibility and control has not kept pace with employee usage, and most (55%) buy AI agents rather than build their own.
More broadly, the data managers surveyed are also concerned about data quality, security, lack of expertise, particularly around agent AI, observability and security.
However, that may be changing, with employee upskilling, privacy and security and governance all considered equally important in future investment (with 23% predicting a significant increase in how much they will spend on AI).
“For AI to deliver its transformative results and ROI, organizations must prioritize data reliability, invest in rigorous AI governance and upskill their workforce to ensure their AI-driven decision-making is based on reliable, high-quality data and everyone in the organization knows how to use it responsibly,” summarized Chief Product Officer Krish Vitaldevara.
Looking ahead, it is clear that how quickly the tools are implemented is not the only measure of success, and how confidently you can rely on them is also imperative. With AI now deployed at scale, successful companies will tackle these broader factors to improve reliability and quality.
Follow TechRadar on Google News and add us as a preferred source to get our expert news, reviews and opinions in your feeds. Be sure to click the Follow button!
And of course you can too follow TechRadar on TikTok for news, reviews, video unboxings, and get regular updates from us on WhatsApp also.
