Enterprises' Lack of Strong Data Foundation Hinders Wide-scale GenAI Adoption
Report says a large majority of executives trust their data, yet only a fraction of them state that data is actually usable.
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[Image source: Pankaj Kirdatt/MITSMR Middle East]
While AI has been around for decades, GenAI solutions like ChatGPT have made this technology more accessible than ever before. ChatGPT is the fastest-growing consumer app ever. Businesses are racing to adopt GenAI to glean its many advantages. However, organizations quickly find their data isn’t ready to reap the value due to a lack of data quality and management.
A recent study by HFS Research shows that one-third of executives believe less than half of their organization’s data is consumable―highlighting just how many organizations aren’t ready for GenAI.
“The biggest challenge in IKEA is having data management practices in place. We don’t have practices for data cleansing, strategy, and governance. We need all that to ensure GenAI is a success,” said Naveen Gupta, global data leader at IKEA.
An improper data foundation can lead to real-world business consequences outside of poor data quality outputs. If bias exists within the data fed into models, such as gender or racial bias, that bias can be quickly replicated at scale within an organization. This could cause reputational damage, have regulatory implications, and concern investors.
Research shows data quality execution across the business needs to improve – more than 95% of executives believe their companies would be more competitive, more innovative, and able to make faster decisions if their data quality were two times better.
The paper, titled Don’t let your GenAI project fail before it begins, provides guidelines for how organizations can take a data-first approach to achieve better business outcomes, with input from real-world use cases.
“Data quality is the cornerstone of any successful AI initiative, particularly in generative AI. Without robust data management practices in place, the full potential of GenAI remains out of reach. Businesses must prioritize data quality and reliability to unlock the transformative power of AI,” said Phil Fersht, CEO & chief analyst of HFS Research.
Data quality is critical to all business transformation, including the successful use of GenAI. “Companies have a long way to go in terms of data quality and management, but a Data First approach will set organizations up for success,” said Kevin Campbell, CEO of Syniti.
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