Generative AI has Real-time Potential, But is Only at the Starting Gate

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A recent survey found that businesses believe generative AI has massive potential to enable their real-time data analytics efforts.

While one can be forgiven for thinking that generative and operational AI is intelligently powering every transaction, interaction, and event across the business landscape. However, this far from the case. At this point, only five percent of enterprises have implemented generative AI in production at scale.

Still, the same time, there is massive potential for AI to enable delivery or leveraging of real-time data analytics.

That’s the gist of a recent survey by Wavestone, which finds that the combination of data analytics and generative AI are the capabilities most in demand within leading organizations. Eighty-eight percent of executives said that investments in data and analytics are their top priority, and 63% are prioritizing investments in generative AI.

At the core of this transformation is real-time data. Organizations seeking to drive business innovation from data jumped from 60% to 78% over the past five years, while organizations competing on data and analytics increased from 41% to 50%.

See also: Generative AI: A Symphony of Precision Across the Data Lifecycle

There has also been a notable shift in the role of data as a strategic driver of business growth. “Regardless of its novelty, generative AI seems to have catalyzed more positive change in organizations’ data and analytical cultures than in any time since the inception of this survey,” which was first conducted in 2012, the study’s authors, Thomas Davenport and Randy Bean, report.

Organizations are not yet achieving substantial value from generative AI, the study finds. Only five percent have implemented generative AI in production at scale. Challenges are also slowing progress. Almost all (99%) of respondents believe generative AI requires safeguards and guardrails, but only 63% already have them in place.

Top concerns include generative AI’s role in misinformation, ethical bias, job loss, and other risks. Only half have the needed talent to implement AI well.

With great powers comes great responsibility. A clear majority of organizations, 74%, state that data and AI ethics are their top corporate priority. Yet, only 16% say that the industry is doing enough to address data and AI ethical concerns. In addition, only half of executives, 51%, report that their board of directors are well versed in data and AI issues and responsibilities.

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About Joe McKendrick

Joe McKendrick is RTInsights Industry Editor. He is a regular contributor to Forbes on digital, cloud and Big Data topics. He served on the organizing committee for the recent IEEE International Conference on Edge Computing (full bio). Follow him on Twitter @joemckendrick.

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