A recent survey found that businesses believe generative AI has enormous potential to enable their real-time data analytics efforts.
We can certainly believe that generative and operational AI intelligently powers every transaction, interaction and event in the business landscape. However, this is far from the case. Currently, only five percent of companies have implemented generative AI in their large-scale production.
Yet at the same time, AI has enormous potential to enable the delivery or exploitation of real-time data analytics.
This is the gist of a recent investigation by Wavestone, which finds that the combination of data analytics and generative AI is the most in-demand capability within large organizations. Eighty-eight percent of executives said investments in data and analytics are their top priority, and 63% prioritize investments in generative AI.
Real-time data is at the heart of this transformation. Organizations seeking to drive business innovation from data have jumped from 60% to 78% over the past five years, while organizations competing on data and analytics have increased from 41% to 50%.
See also: Generative AI: a symphony of precision throughout the data lifecycle
The role of data as a strategic driver of business growth has also seen a notable evolution. “Regardless of its novelty, generative AI appears to have catalyzed more positive change in organizations’ data and analytics cultures than at any time since this survey began,” which was first conducted in 2012, they said. declared the authors of the study, Thomas Davenport And Randy Beanreport.
According to the study, organizations are yet to realize substantial value from generative AI. Only five percent have implemented generative AI in large-scale production. Challenges also slow progress. Nearly all (99%) of respondents believe that generative AI requires safeguards and guardrails, but only 63% have already put them in place.
Key concerns include the role of generative AI in misinformation, ethical bias, job loss, and other risks. Only half have the talent to implement AI well.
With great powers comes great responsibilities. A clear majority of organizations, 74%, say data and AI ethics are their top priority. Yet only 16% say the industry is doing enough to address ethical concerns around data and AI. Additionally, only half of executives, 51%, say their board is familiar with the issues and responsibilities related to data and AI.
