Fearing that poor data could confirm effective adoption of artificial intelligence systems, most companies struggle to manage or access quality data despite increasingly pouring more resources into AI tools.
A new study from SoftServe reveals the growing gap between the company's AI ambitions and its data capabilities.
While the rapid deployment of AI Tech has made data an important resource for businesses seeking competitive advantage, the study found a major gap between the goals of business leaders and their ability to use data to deliver technological change.
The “Great Data Divide” report found that while almost all (98%) business and technology leaders believe that data strategies need to be updated to get full benefits for AI, 73% acknowledge that they allocated funds or talent to company trends at the expense of more valuable data and analytics initiatives.
In fact, almost three-fifths (58%) said their companies mostly made strategic business decisions based on inaccurate or inconsistent data, but more (60%) said accessing the data they need when they need it is a real challenge.
Based on a survey of 750 business leaders and technology and data executives, SoftServe's report found that two-thirds of companies (65%) say no one within their organization has a comprehensive understanding of the data collected and how to access it.
The overwhelming majority of business leaders (98%) confessed that they faced “substantial challenges” in improving their company's data strategies. The main barrier is legacy or the use of different technologies by different units (73%), with no integrated ownership of data (75%).
Furthermore, three-quarters of companies that require data overhauls (76%) say they don't fully understand how leadership creates value from the data their businesses collect.
Undeveloped data strategies have had a major impact on corporate AI goals. Only 42% said they could train their Genai models with their own data, while 89% said they struggled to incorporate business data into their AI use.
One of the biggest challenges to stop organizations from moving AI forward is the risk of data exposure (39%), inability to capture or access the appropriate data to build models (39%), compliance issues (36%), and short-term issues of AI governance and skills.
Additionally, many organizations face inconsistencies between AI initiatives and core business goals, allowing 64% of business leaders to frequently deploy AI solutions without establishing viable use cases, while (74%) agreed that companies often jump into AI pilots without clear plans.
However, organizations with high data maturity have been found to deploy AI initiatives more modestly. Although 83% of companies requiring data strategy overhauls frequently or constantly deploys AI solutions without identifying use cases, this figure falls under 60% of data-matured companies.
Softserve Director of Data Science Iurii Milovanov commented: “There is a mutually beneficial relationship between Genai and data. While more powerful data will result in a more robust Genai implementation, business-oriented Genai applications will transform unused data into valuable assets.
The report coincides with the publication of a new study from Snowflake, revealing that 93% of UK companies have achieved increased efficiency by employing generated AI to surpass the global average.
The “Radical ROI of Generated AI” research report, created in collaboration with the Enterprise Strategy Group, examined 1,900 business and IT leaders from nine countries actively using generated AI in a variety of applications.
However, despite the positive embrace of AI technology, challenges remain with only 10% of UK companies achieving higher capabilities compared to 20% worldwide. Additionally, 63% of UK respondents cited time-consuming data management procedures as a critical hurdle higher than the global average of 55%.
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