A survey of 2,307 enterprise decision makers and influencers finds nearly all respondents (97%) expect generative artificial intelligence (AI) to have a material impact on improving productivity but only two-thirds (66%) view it as a revolutionary game changer.
Conducted by NTT Data, the survey also finds 83% of respondents work for organizations that have a well-defined GenAI strategy in place, but more than half (51%) have not yet aligned that strategy with their business plans, and only 43% said generative AI technologies are meeting expectations.
Two-thirds (66%) also acknowledge their employees don’t have the generative AI skills needed, with 64% identifying training as a key adoption challenge.
Organizations going forward will soon need to distinguish between generative AI investments that are rapidly becoming table stakes to stay competitive and investments that create a sustainable competitive advantage, says Dan Albright, president of consulting for NTT Data. “There’s still a lack of alignment on strategy,” he says.
The challenge is far too many organizations are making generative AI investments in specific silos, adds Albright. Many organizations would be well-advised to set up a governing body to evaluate the return on investment (ROI) in generative AI technologies, he notes.
The survey also finds that a full 90% of respondents view legacy IT infrastructure as a hindrance for generative AI adoption, with 96% noting that cloud-based solutions are the most practical and cost-effective means to support GenAI applications. Only 44% said they have established the optimal infrastructure to efficiently and cost-effectively scale generative AI in a cloud environment. However, only 45% said they have conducted a detailed analysis or assessment of their future infrastructure needs for generative AI.
Three quarters (75%) also said that generative AI ambitions stand in conflict with and/or are negatively affecting sustainability goals.
A total of 89% of C-suite executives also said they were very concerned about potential security risks of AI deployments, and only 35% said those security risks are adequately understood and being managed.
In general, 70% of respondents said they are optimistic about generative AI and nearly all (99%) plan to make additional investments, with two-thirds (66%) describing those investments as significant.
A full 80% also report their organization has already established an expert or robust internal generative AI team, with the other 20% building or making plans for a generative AI team. Nearly all (97%) have already or plan to, this year, assess the skills and capabilities needed to plan and execute their generative AI strategy.
A total of 82% said it’s very important to have a named C suite executive responsible for generative AI.
At the same time, 82% also noted that government AI regulation is still unclear, which stifles innovation and hinders investment in generative AI.
There is clearly still much work to be done before generative AI is pervasively employed across enterprises but the one thing that is clear is that as more organizations gain hands-on experience with generative AI technologies, they are now on the verge of moving well beyond simple experimentation. The challenge is first identifying the use cases that matter most to business, and then making sure generative AI investments can be realized before any rival might similarly implement them.
