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Poor data foundations stunting generative AI potential, study reveals
Tue, 5th Mar 2024

A lack of robust data foundations is preventing businesses from achieving their full potential with generative AI (GenAI), according to a study by global expert in enterprise data management, Syniti, and HFS Research. This report aims to provide insight into how companies can augment their data quality and reliability to take full advantage of GenAI.

Emerging GenAI solutions, like the rapidly adopted ChatGPT, are more accessible than ever. In just two months, ChatGPT accumulated 100 million monthly active users, marking it as the fastest-growing consumer app ever. Inspired by this growth, many businesses are hustling to adopt GenAI, but, quite often, their data lacks the quality and accessible management required to maximise this technology's value.

The HFS research shows that one-third of executives believe less than half of their organisational data is consumable. This staggering statistic suggests that many companies may not be prepared for GenAI. Furthermore, the absence of a proper data foundation not only leads to poor quality data outputs but could also trigger significant business ramifications if bias towards aspects like gender or race is present in the data input.

Global data leader at IKEA, Naveen Gupta, spoke about the company's challenges, stating, "The biggest challenge we're facing in IKEA is having data management practices in place. We don't have practices for data cleansing, strategy and governance. We need all of that to make sure GenAI is a success."

This bias, if perpetuated, can be replicated at an organisational scale, which could damage a company's reputation, fall foul of regulatory standards and alarm investors. Syniti supports businesses counter these potential issues by adopting a 'Data First' approach, helping to ensure the infrastructure is in place to deliver usable, reliable data to fuel GenAI models.

"Data quality is the cornerstone of any successful AI initiative, particularly in the realm of generative AI," said Phil Fersht, CEO and chief analyst at HFS Research. He stressed that without a proper data foundation in place, "the full potential of GenAI remains out of reach. It's imperative for businesses to prioritise data quality and reliability to unlock the transformative power of AI."

Syniti CEO Kevin Campbell reinforced this message, arguing that while "GenAI's potential can't be overstated," companies need to approach this wisely. "Data quality is critical to all business transformation, including successful use of Generative AI, and it's shocking how many organisations still don't properly prepare their data ahead of these initiatives. Companies have a long way to go in terms of data quality and management, but a Data First approach will set organisations up for success."

A robust data foundation is therefore not only vital for successful GenAI application, but also for overall business success. As enterprises continue to realise the value of GenAI, strategies for data management and the emphasis on data quality will likely become more pertinent.