A new survey of 500 UK professors, analysts and corporate researchers has found that AI-assisted research saves the average respondent an estimated four hours per week—equivalent to over five additional working weeks per year per researcher.

The survey, commissioned by AI scientific frontier research platform Corpora.ai, found that when the saving was applied to intellectual property checks alone, this translates into a potential national productivity dividend running into the millions of hours.

UK researchers and R&D teams could collectively reclaim an estimated 600 million working hours per year, possibly generating between £11-20bn of economic value by using AI-powered tools to accelerate prior-art and freedom-to-operate (FTO) searches.

Research hours saved were calculated by taking the average amount of hours per week saved using AI and applying that to the Department for Science, Innovation and Technology figure of 2.8 million people in UK R&D occupations.

The saving of between £11-20bn of economic value was calculated by taking the average pay rate of £21.28 per hour and multiplying that by the amount of hours saved in a year.

The findings come during the UK’s 2025 Autumn Budget week, said to be one of the country’s most highly anticipated and chaotic, amid speculation of tax rises to cover the country’s fiscal shortfall and lagging growth.

At a time when the UK desperately needs to improve economic growth, AI driven research tools could free resources for innovation, deeper analysis and teaching, according to Mel Morris CBE, Corpora.ai co-founder and CEO.

“Prior art patent searches [patent already publicly known] are one of the most time-intensive and costly stages in the innovation process. Our data shows that AI can release millions of hours that could be reinvested in discovery and commercialisation. This is not just about efficiency; it’s about accelerating the UK’s ability to turn ideas into intellectual property and economic growth,” said Morris.

A productivity boost with national implications

The average innovation-to-commercialisation cycle is 7-12 years, according to McKinsey, with over 80% of initiatives failing before market entry, often resulting in a total write-off. Prior-art and FTO checks are an essential but time-intensive precursor to delivering innovation across sectors as diverse as life sciences, materials engineering, energy and aerospace.

These searches can take weeks of manual review across global patent databases and academic literature. The process is slow, expensive and often described as a “hidden IP tax” on innovation.

Keith Cook, CEO of UCR Group said: “The most exciting breakthroughs often stall not because of a lack of ideas, but because of the time and cost of proving those ideas are genuinely new. Prior art and freedom-to-operate checks are vital, but they can consume weeks of effort for every promising line of research.

“By cutting that process down to days or even hours, AI gives scientists and R&D teams the freedom to move faster, take more risks, and bring innovations to market sooner. The implications are enormous – from bioscience to clean tech, the UK’s ability to commercialise discovery is directly linked to how efficiently we can navigate the intellectual property landscape.”

The survey found that 96% of UK researchers surveyed believe AI could be important in reducing this burden, highlighting broad recognition that smarter automation can accelerate the journey from idea to intellectual property. If realised at scale, this efficiency gain could help close the UK’s innovation-productivity gap and support progress towards the government’s ambition to raise R&D spending to 2.4% of GDP.

Despite the clear efficiency gains, trust remains the final barrier to widespread adoption. The survey found that the majority of researchers verify their outputs when reviewing literature (84%), performing prior art searches or patient checks (83%) and data analysis (93%). What’s more, half (50%) cite accuracy as a major concern. For many, transparency of sources is non-negotiable: 94% said clear citations are important for professional research workflows.