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On Thu, 17 Oct, 1:09 PM UTC
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Four out of five businesses are unable to capitalise on AI due to poor data foundations, reports MIT Technology Review Insights, in partnership with Snowflake
95% of organisations face challenges when implementing AIJust 22% of business leaders are 'very ready' to engage with AI78% of businesses are unable to maximise their AI investment due to poor data foundationsBusiness leaders have high hopes that artificial intelligence (AI) investments can drive market-changing innovations to transform everything from customer satisfaction to product innovation. However, a poor data foundation is holding 78% of organisations back from achieving these goals.A new report from MIT Technology Review Insights, in partnership with Snowflake, the AI Data Cloud company, titled 'Data Strategies for AI Leaders' found that while businesses have big ambitions for generative AI -- with 72% looking to increase efficiency or productivity, 55% betting on increased market competitiveness, and 47% aiming to see more innovation in products and services -- the foundational data strategy needs to be improved to maximise AI's potential.Businesses need strong data foundations, powered by modern cloud data platforms, to enable them to harness their own stores of data, and also vast volumes of previously inaccessible data, largely from unstructured data such as videos and images. According to the report, just 22% of business leaders say they are 'very ready' to engage with AI, while 53% are 'somewhat ready'. Higher readiness correlates with fewer challenges related to accessing scalable computing power, data silos and integration issues, and data governance. Despite many business leaders' confidence in the results AI can deliver, they are realising that data is key to how quickly and effectively they can unlock AI's value.Another challenge facing organisations is deploying AI at scale. 95% of those surveyed reported facing hurdles when implementing AI. 59% of respondents cited data governance, security, or privacy as their most prevalent challenge, followed by data quality and timeliness (53%), and costs of resources or investment (48%). Spending and resourcing decisions, including those needed to improve data foundations, are a challenge when it comes to any technology investment. But the cost of generative AI itself is decreasing, with enterprises having begun to build smaller large language models (LLMs) that remain equally capable, and less expensive."Many of today's organisations have big ambitions for generative AI: they are looking to reshape how they operate and what they sell," says Baris Gultekin, Head of AI, Snowflake. "Our joint research shows that as organisations feel increasing urgency to deploy AI applications, they are realising that their data can help them deliver insights from previously untapped sources of information. A strong data foundation is at the core of generative AI capabilities, and business leaders need to move quickly to deal with concerns such as data security and cost, and establish the foundation they need to deliver on the promise of AI."Generative AI's benefits are becoming visible to those companies farther along their data journey, because they invested heavily in data foundations and are now being rewarded by bringing AI onto that data. For any business looking to capitalise on AI, they must first establish a robust data foundation, which covers a broad collection of processes and assets involved in the gathering, aggregation, storage, and accessibility of organisational data. Investment in data foundations across an organisation will enable much more powerful generative AI users, while also reducing governance and security concerns.About SnowflakeSnowflake makes enterprise AI easy, efficient and trusted. Thousands of 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. The era of enterprise AI is here. Learn more at snowflake.com (NYSE:SNOW).
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Businesses are struggling to harness the full power of AI
A new report jointly created by MIT Technology Review Insights and data company Snowflake has confirmed that many businesses are simply failing to harness the power of artificial intelligence. As many as four in five (78%) organizations are unable to fully capitalize on their AI investments according to the study, largely due to inadequate data management. Data governance, security and privacy concerns emerged as the top challenge (59%), followed closely by data quality and timeliness (53%) and the costs associated with AI resources (48%), highlighting the need for a simpler and clearer foundation. It's clear that there are challenges between initial investments and tangible rewards, but companies still appear to be optimistic. Nearly three-quarters (72%) agree that AI would boost efficiency and productivity, with around half believing it will enhance market competitiveness (55%). However almost all (95%) reported facing hurdles when implementing AI. While more than half (53%) of business leaders describing themselves as 'somewhat ready' for artificial intelligence and everything that it entails, only one in five (22%) state that they are 'very ready,' signifying that they have fewer challenges related to accessing scalable computing power, data silos and integration issues, and data governance. Speaking about the "big ambitions" that companies have surrounding GenAI, Snowflake Head of AI Baris Gultekin said: "A strong data foundation is at the core of generative AI capabilities, and business leaders need to move quickly to deal with concerns such as data security and cost, and establish the foundation they need to deliver on the promise of AI." Moving forward, the report calls for modern cloud data platforms that allow companies to better manage and access vast amounts of unstructured data.
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A new report by MIT Technology Review Insights and Snowflake highlights that 78% of businesses are unable to fully leverage their AI investments due to inadequate data management, despite high expectations for AI's potential to drive innovation and efficiency.
A recent report by MIT Technology Review Insights, in partnership with Snowflake, reveals that 78% of businesses are struggling to capitalize on their artificial intelligence (AI) investments due to inadequate data foundations 1. The study, titled 'Data Strategies for AI Leaders,' highlights the disconnect between companies' ambitious AI goals and their ability to implement these technologies effectively.
Despite the challenges, businesses maintain high hopes for AI's potential:
However, the reality falls short of these expectations. Only 22% of business leaders consider themselves 'very ready' to engage with AI, while 53% feel 'somewhat ready' 12.
The report identifies several major hurdles facing organizations as they attempt to deploy AI at scale:
These challenges underscore the critical need for robust data management strategies and infrastructure.
Baris Gultekin, Head of AI at Snowflake, emphasizes the crucial role of data foundations: "A strong data foundation is at the core of generative AI capabilities, and business leaders need to move quickly to deal with concerns such as data security and cost, and establish the foundation they need to deliver on the promise of AI" 2.
Companies with stronger data foundations report fewer challenges related to:
To fully harness the power of AI, businesses must prioritize:
By focusing on these areas, companies can better position themselves to leverage AI technologies, including the ability to harness vast amounts of previously inaccessible unstructured data, such as videos and images 1.
As the AI field progresses, some positive trends are emerging:
These developments may help alleviate some of the resource-related challenges facing businesses as they strive to implement AI solutions.
In conclusion, while the potential of AI remains immense, the report underscores the critical importance of solid data foundations in realizing its benefits. As companies continue to invest in AI, addressing these fundamental data challenges will be key to unlocking the technology's transformative power across industries.
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