The potential of generative AI (GenAI) to improve business outcomes is well understood by employers, but a lack of comprehensive governance policies around using it at work is holding back progress, research has found.
A survey of 800 IT and business leaders across the United States, Canada, and Western Europe, found that the vast majority (97 percent) of employers see GenAI as a top five priority. But less than half (44 percent) have well-defined and comprehensive policies relating to its use.
Yet nearly two-thirds (63 percent) said that they have already identified at least one use case for this technology.
The research, published in a report from Enterprise Strategy Group (ESG) and Hitachi Vantara, examined what is driving companies to implement GenAI and what is making leaders cautious.
Survey respondents identified the key use cases driving enterprise investment as process automation and optimisation (37 percent), predictive analytics (36 percent), and fraud detection (35 percent).
The report authors said it’s no surprise that improving operational efficiency was the area most cited, however, less than half (43 percent) have realised benefits up to this point.
Concerns and challenges
Survey respondents pointed to security, infrastructure and data management issues as the main barriers to implementing the technology.
More than four in five (81 percent) respondents reported concerns around ensuring data privacy and compliance when building and using applications that use GenAI, while 77 percent agreed that data quality issues needed to be addressed before accepting the results of GenAI outputs.
Just 37 percent agreed that their infrastructure and data ecosystem is well-prepared for implementing GenAI. However, c-level executives were 1.3 times more likely to say that their infrastructure and data ecosystem is highly prepared, highlighting a notable disconnect.
More than half (61 percent) of respondents agreed most users don’t know how to capitalise on GenAI, with 51 percent reporting a lack of skilled employees with relevant knowledge.
And two-fifths (40 percent) of respondents agreed they are not well-informed regarding planning and execution of GenAI projects.
Jumping on the bandwagon
“Enterprises are clearly jumping on the GenAI bandwagon, which is not surprising, but it’s also clear that the foundation for successful GenAI is not yet fully built to fit the purpose, so its full potential cannot be realised,” said Ayman Abouelwafa, chief technology officer at Hitachi Vantara.
“Unlocking the true power of GenAI requires a strong foundation with a robust and secure infrastructure that can handle the demands of this powerful technology.”
Further survey data revealed that businesses are actively seeking out lower-cost infrastructure options, although privacy and latency are also key considerations.
A large majority (71 percent) of respondents admitted that their company’s infrastructure needs to be modernised before pursuing GenAI projects.
Mike Leone, principal analyst at ESG, said that the need for improved accuracy has meant organisations are prioritising the use of the most relevant and recent data in their large language models. After this, the priorities are to keep up with technology advances, regulation changes and shifting data patterns, he said.
“Managing data with the right infrastructure will not only enable greater levels of accuracy, but also improve reliability as data and business conditions evolve.”
