A survey of 2,200 C-suite and senior executives published today finds large enterprises plan to invest an average of $47.5 million in generative artificial intelligence this financial year.
Conducted by Oxford Economics on behalf of Cognizant, the survey also finds 70% of respondents believe their organization is not moving fast enough.
Overall, more than three-quarters of respondents (76%) said their organization is looking to leverage generative AI to create new revenue streams, while 58% are incorporating revenue increases into their business cases enabled by generative AI.
Additionally, 82% suggested that that same delay in execution could place them at a competitive disadvantage, the survey finds.
The survey indicates that adoption of generative AI is now widespread in the enterprise, says Naveen Sharma, senior vice president and global head of AI and analytics business at Cognizant. “There has seen a sharp trajectory in the last 21 months,” he says.
However, only 26% of respondents said their organization has implemented cross-enterprise use cases and 43% said they plan to work with external consultants to develop a plan for generative AI.
Part of those plans include upskilling existing workers (54%) and seeking to transition displaced workers to new roles (44%). That will be necessary because as generative AI continues to evolve many tasks currently handled by humans will be performed by AI agents that humans are orchestrating, notes Sharma. In fact, at this juncture culture and process issues are likely to be just as big a challenge as the core generative AI technologies themselves, he adds.
AI is a Priority
Much of the funding for generative AI, however, includes IT budget dollars that were previously allocated, as well as contributions from other business units. However, the survey makes it clear generative AI is a priority.
Less clear is how long it might be before material return on investment (ROI) in the generative AI proof-of-concept (PoC) projects that today permeate many enterprises. Given the costs required to deploy these projects in a production environment, many organizations will need to prioritize which projects will be allowed to go forward first. Organizations will also need to track key performance indicators (KPIs) to enable them to show a meaningful ROI for these projects, says Sharma.
Exactly how long a generative AI project might provide an organization with a competitive edge is going to vary widely but most organizations should assume that rivals will follow their lead quickly. They should assume that rivals are working on similar initiatives to their own. The only question is to what degree are those efforts being funded.
Overall, Cognizant is predicting generative AI will add $1.043 trillion to the U.S. gross domestic product (GDP) by 2032. That level of impact makes it apparent that eventually every job in some way will be impacted by generative AI. The challenge and the opportunity now is to proactively manage that transition over the next several years rather than simply waiting for the all-but-inevitable to eventually occur in a way that has a more negative than potentially positive outcome.
