Snowflake, the AI Data Cloud company, in collaboration with Enterprise Strategy Group, released the Radical ROI of Generative AI, which found that 92% of respondents reported that their AI investments are already generating ROI, with 98% planning to invest even more on their AI initiatives in 2025.
The research surveyed 1,900 business and IT leaders across nine different countries, including the UK, France and Germany, all of whom are actively using Generative AI for one or more use cases.
Just two-and-a-half years since Generative AI began dominating every technology conversation, early adopters of AI are realising success with both internal and external use cases.
Over half, 55% of respondents prioritised employee-facing solutions to improve productivity and efficiency, while 44% started with customer-facing solutions to elevate customer experience and satisfaction.
“I have spent almost two decades of my career developing AI, and we have finally reached the tipping point where AI is creating real, tangible value for enterprises across the globe,” said Baris Gultekin, Head of AI, Snowflake.
“With over 4,000 customers using Snowflake for AI and ML on a weekly basis, I routinely witness the outsized impact these tools have in driving greater efficiency and productivity for teams and democratising data insights across entire organisations.”
Mohamed Zouari, General Manager for the Middle East, Africa, and Türkiye at Snowflake, said: “With the UAE set to gain $96 billion from AI by 2030 and Saudi Arabia launching a $100 billion AI initiative, AI is fast becoming the blueprint for business growth in the Middle East.
“But without a data strategy, there is no AI strategy. Regional businesses face real challenges, from fragmented data infrastructure gaps to talent shortages. At Snowflake, we are helping organisations lay the secure and scalable data foundations they need to truly capitalise on AI’s potential.”
Despite this, many respondents are facing significant challenges in making this data AI-ready, citing the following as the biggest hurdles for driving AI success.
Higher than expected costs: 96% of early adopters report that one or more components of their gen AI solutions have cost more to date than was initially anticipated, and 78% say that half or more of their gen AI use cases have cost more than expected to get into production.
Breaking down data silos: 64% of early adopters say integrating data across sources is challenging today.
Organising unstructured data: Most data is unstructured, 80%–90% by many estimates. However, only 11% of the early adopters say that more than half their unstructured data is ready to be used in LLM training and tuning.
Integrating governance guardrails: 59% say enforcing data governance is difficult.
Measuring and monitoring data quality: 59% say measuring and monitoring data quality is difficult.
Integrating data prep: 58% say making data AI-ready is a challenge.
Efficiently scaling storage and compute: 54% say it is difficult to meet storage capacity and computing power requirements.
The report reveals that early AI investments are proving to be successful for most enterprises, with 93% indicating that their Generative AI initiatives have been very or mostly successful. Respondents’ AI initiatives resulted in measurable improvements across efficiency, 88%, customer experience, 84%, and accelerated innovation, 84%.
In fact, two-thirds of respondents are already starting to quantify their Generative AI ROI today, finding that for every $1 million spent, they are seeing $1.41 million in returns through cost savings and increased revenue.
As global organisations advance along their AI journeys, respondents are allocating additional resources to their AI initiatives, citing data, 81%, large language models, 78%, supporting software, 83%, infrastructure, 82%, and talent, 76%. This strategic focus underscores a fundamental shift in what businesses prioritise to operate and compete in the future.
Unlocking AI’s true potential requires a robust data foundation. Organisations are increasingly incorporating their proprietary data to maximise AI’s effectiveness, with 80% of respondents choosing to fine-tune models with their own data.
Researchers from Enterprise Strategy Group identified, and conducted deeper research between Nov. 21, 2024, to Jan. 10, 2025, with early adopter organisations, those already augmenting and executing business processes in production, using commercial and open-source models rather than consumer-grade, subscription software such as ChatGPT. Of 3,324 respondents, 1,900, 57% said they are using commercial or open source Generative AI solutions.
Snowflake makes enterprise AI easy, efficient and trusted. More than 11,000 companies around the globe, including hundreds of the world’s largest, use Snowflake’s AI Data Cloud to share data, build applications, and power their business with AI.
