GenAI adoption hindered by data disruption

Syniti and HFS Research report shares insights on how to increase data quality and reliability to help unleash full potential of GenAI.

  • 3 months ago Posted in

Syniti has published the results of a study developed with HFS Research to help organizations understand the value they can derive from their generative AI (GenAI) investments. The paper, titled “Don’t let your GenAI project fail before it begins,” provides four guidelines for how organizations can take a Data First approach to achieve better business outcomes, with input from real-world use cases.

While AI has been around for decades, generative AI solutions like ChatGPT have made this technology more accessible than ever before. ChatGPT has seen lightning-fast adoption, racking up 100 million monthly active users in its first two months, making it the fastest-growing consumer app ever. Since then, businesses have raced to adopt GenAI to glean its many advantages. However, organizations are quickly finding their data isn’t ready to reap the value due to lack of data quality and management. In fact, recent HFS research shows that one-third of executives believe less than half of their organization’s data is actually consumable―highlighting just how many organizations aren’t ready for GenAI.

An improper data foundation can lead to real-world business consequences outside of just 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. Syniti supports enterprises with a Data First approach, helping to ensure the right infrastructure is in place to break down silos and deliver trusted, usable data to fuel GenAI models.

Naveen Gupta, global data leader, IKEA, said: “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.”

Phil Fersht, CEO & chief analyst, HFS Research, said, “Data quality is the cornerstone of any successful AI initiative, particularly in the realm of generative AI. Our joint report with Syniti sheds light on a critical issue facing organizations today: the inadequacy of their data foundation. Without robust data management practices in place, the full potential of GenAI remains out of reach. It's imperative for businesses to prioritize data quality and reliability to unlock the transformative power of AI."

Kevin Campbell, CEO, Syniti, said: “GenAI’s potential can’t be overstated, but companies need to approach this technology with the wisdom and respect it deserves. Data quality is critical to all business transformation, including successful use of Generative AI, and it’s shocking how many organizations 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 organizations up for success.”

More than 69% of executives expect to spearhead their organisation’s AI efforts.
Hewlett Packard Enterprise and NVIDIA has introduced NVIDIA AI Computing by HPE, a portfolio of...
New research reveals North America leads in AI-driven product innovation but Europe seeks to make...
Enterprise IT and operations leaders are realizing positive results from early AI deployments,...
Consumer demands shift business leaders' focus to predictive, emotionally intelligent and...
Unveils Aryaka AI> Initiative across entire Unified SASE as a Service offering.
Edwin AI is the powerful ITOps team companion that drives rapid issue resolution and predictive...
Empowering customers to accelerate the application, quality iteration, and productionization of...