Business leaders are turning their focus from experimentation to long-term use cases that transform business performance, workplace culture, compliance, safety and sustainability as almost all of them already have invested in generative AI, and 83% have established “expert” or “robust” generative AI teams, according to NTT Data.
NTT Data commissioned Jigsaw Research to conduct primary research during late September and early October 2024. The team surveyed more than 2,300 leaders from organisations in 34 markets across North America, Europe, Asia-Pacific, Latin America, and Middle East and Africa.
Top use cases for generative AI globally include personalised service recommendations and knowledge management; quality control; and R&D.
In APAC, top use cases include R&D, personalised service recommendations and knowledge management; and process automation.
“As we move beyond experimentation, a tension emerges: move too fast, and we risk unintended circumstances; move too slow and we fall behind,” said Yutaka Sasaki, president and CEO of NTT Data Group. “Getting generative AI right isn’t optional. That’s why we’re providing a blueprint to help our clients harness its potential for lasting success.”
Two-thirds of C-suite respondents globally said generative AI will be a “game changer” over the next two years and will improve productivity and efficiency; sustainability; compliance; business processes; security; and employee experience.
While in APAC, two-thirds of C-suite respondents said the technology will improve productivity and efficiency; sustainability and environmental goals; accelerate innovation; improve security; compliance and process adherence; and strategy and transformation.
A cycle of consolidation and integration of generative AI technologies is beginning that combines experimental, phased and specific approaches.
Focused spending plans will replace scattered experimentation in a relatively short time, with 97% [APAC: 99%] of CEOs anticipating a material impact from this technology.
Also, 83% [APAC: 86%] of respondents said they have a well-defined generative AI strategy in place, but 51% [APAC: 49%] have not yet aligned that strategy with their business plans. This gap limits return on investment and satisfaction with current outcomes.
Nearly all respondents agree that generative AI can spark creativity and improve R&D activities. Given the rapid adoption and advancement of this technology, organisations will have to constantly re-evaluate and evolve their strategies and operating models.
Among global respondents, 90% [APAC: 91%] said legacy infrastructure hinders effective use of generative AI. Also, 96% [APAC: 97%] of CIOs and CTOs said cloud-based solutions are the most practical method for supporting generative AI applications.
Further, 96% [APAC: 97%] of respondents are considering how generative AI can streamline future employee workflows and support processes. However, 67% [APAC: 64%] of respondents said their employees lack the necessary skills to work with it.
About half are planning employee education and training to increase generative AI adoption. Globally, the top obstacles to adoption are users who perceive limited value for a generative AI solution; limited or no awareness of the solution; user resistance to the technology; and concerns about generative AI’s safety and security.
In APAC, the top obstacles to adoption are users who perceive limited value for a generative AI solution; need for user training; concerns about generative AI’s safety and security; and limited or no awareness of the solution.
