UK leaders back data streaming engineers for faster AI

Confluent has published research showing that 83% of UK business leaders believe their organisations could adopt AI faster if they had dedicated data streaming engineers. The findings are based on a survey of 200 senior executives at private sector businesses in the UK.

The study suggests a growing view among business leaders that specialists who handle data in real time are becoming essential as companies try to move AI projects from trial stages into wider operational use.

More than half of respondents, 56%, strongly agreed that every data-driven organisation should have at least one data streaming engineer. Overall, 94% agreed that all data-driven organisations should employ such specialists, while 85% expected to expand their data streaming engineering teams.

Leaders also linked these roles to decision-making beyond AI deployment. In the survey, 83% said dedicated data engineers would help them make better-informed decisions faster, and 88% said organisations that hired them would be better placed to adopt, use and manage AI.

Real-time focus

The findings reflect a distinction Confluent drew between traditional data engineering and work centred on data as it is created and moves across systems. This role focuses on managing the continuous flow and processing of data so businesses can use current information rather than relying only on historical records.

That issue has become more prominent as companies seek to use AI tools in day-to-day operations, where responses and recommendations may depend on information that changes quickly. In that context, data quality and timeliness are becoming a management concern as well as a technical one.

Richard Jones, vice president Northern Europe at Confluent, outlined the distinction in the company's assessment of the research.

"While traditional data engineers focus on storing, cleaning and preparing historical data, data streaming engineers operate in the present tense, ensuring data is continuously available, trusted and actionable the moment it's created," Jones said.

He also pointed to the risks executives associate with AI systems that rely on incomplete or outdated information.

"The risk is when that reliance turns into blind trust. AI can only work with the data it's given, and when that data is incomplete or out of date, the consequences can be serious. That's why it's so encouraging to see businesses investing heavily in data. If leaders want AI to make informed decisions, it needs an accurate, real-time view of what's really happening across the business. Without that, AI can sound knowledgeable, but it won't be truly intelligent," Jones said.

Hiring pressure

The survey suggests demand for these engineers may rise as businesses reassess the skills needed to support AI. While many organisations have already invested in data infrastructure and analytics teams, the results indicate that executives see a gap in staff focused specifically on streaming and continuously updated data.

That matters because many AI systems are only as useful as the data they receive. If company information sits in separate systems or reaches models too late, leaders may struggle to rely on outputs for decisions in areas such as operations, customer service, supply chains and financial planning.

For employers, the results may add to competition for data specialists in a labour market that has already seen sustained demand for engineers, analysts and AI staff. The figures suggest business leaders are interested not only in hiring for experimental AI work, but also in the underlying data roles needed to support it in production.

Executive view

The research was commissioned by Confluent and carried out by market research agency 3Gem in the second half of 2025. It surveyed 200 UK business leaders, including owners, founders, chief executive officers, managing directors and other C-suite executives at private sector enterprises.

The results offer a snapshot of executive sentiment rather than a direct measure of technology adoption. But they indicate that senior leaders increasingly see real-time data management as tied to the pace of AI deployment. They also suggest companies are beginning to treat data streaming engineering as a defined role rather than a function folded into broader data teams.

Among those surveyed, 88% said organisations that hire data streaming engineers will be better placed to adopt, use and manage AI.