Up to 86% of generative AI early adopters have reported revenue increases of over 6%, according to a new global study. The survey, commissioned by Google Cloud and carried out by the National Research Group, consulted 2,500 C-Suite leaders from enterprises generating more than $10m in revenue. The poll also found that 61% of executives are leveraging gen AI with at least one application in production, with such projects delivering tangible improvements in productivity, security, business growth, and user experience. Such results, argued Google Cloud, underscore the tangible return on investment (ROI) that gen AI is delivering across various industries.
“Generative AI is not just a technological innovation; it’s a strategic differentiator,” said Google Cloud global generative AI go-to-market vice president, Oliver Parker. “Our research shows that early adopters of gen AI are reaping significant rewards, from increased revenue to better customer service to improved productivity. Organisations investing in gen AI today are the ones that will be best positioned to succeed in the coming decade.”
Survey reports tangible returns on gen AI investment
About 45% of executives have seen employee productivity at least double due to gen AI implementations. Additionally, 56% of respondents report strengthened organisational security, with improved abilities to identify threats and quicker resolution times for security issues. Regarding business growth, 77% of those surveyed noticed improvements in customer acquisition and leads due to gen AI solutions. Regarding user experience, 85% of executives have observed increased user engagement in projects involving generative AI, with 80% reporting improved satisfaction.
The research also details the critical role of C-Suite support in transitioning from piloting to full-scale production of gen AI, a process 84% of executives say their organisations have completed in under six months. However, 39% of enterprises overall have yet to implement the technology in production. This lag is more pronounced in regulated industries such as financial services and manufacturing, and in the EMEA region, where organisations are less likely to have been leveraging gen AI in production for more than a year.
C-Suite support also appears to be proving essential, with 91% of those with robust executive backing reporting increased revenues of 6% or more. Furthermore, organisations that extensively utilise and invest in generative AI, known as “Gen AI Leaders,” were reported to have distinguished themselves by effectively aligning their AI strategies with broader business goals. 76% of these leaders have done so, according to the survey, outperforming the global average of 69%. Additionally, 54% of leaders have invested in dedicated generative AI teams, and 86% plan to allocate at least half of their future AI budgets to generative AI, compared to 67% on average.
“By connecting financial business drivers with technology drivers, organisations can ensure that AI strategies are not just innovative but also closely intertwined with core business goals,” said Google Cloud strategic industries Carrie Tharp. “This strategic alignment is key to escaping the dreaded ‘pilot purgatory’ and accelerating towards tangible business impacts, leveraging AI to transform operations, enhance customer experiences, and unlock new avenues for growth.”
‘Reinvestment cycle’ sparked
The study also found that the early success of gen AI is sparking a reinvestment cycle, driving further innovation and growth. Nearly half of the respondents (49%) plan to reinvest their gains from gen AI to further improve operating profit margins.
The areas of focus for reinvestment are diverse, starting with aligning business and technology to support change management for user adoption of AI. Additionally, investments are being made in upskilling the workforce and attracting new talent with AI expertise.
Finally, there is a significant emphasis on investing in data quality and knowledge management to ensure that gen AI applications are built on a solid foundation of accurate and reliable data.
However, generative AI faces growing uncertainties, including ethical concerns about deepfakes and bias, uncertain regulatory landscapes, and security risks such as potential misuse in cyber attacks. The impact on employment, with fears of job displacement balanced against new opportunities, adds to the concerns. Technological limitations also challenge AI’s reliability and effectiveness, with one recent survey finding that over 70% of companies need to overhaul their stack to even deploy gen AI.
Read more: European GenAI spend could exceed $30 billion by 2027
