An announcement of execs’ top risks for 2024 highlighted fast-paced adoption of AI, generatively generally speaking.
Orgs are seeking out practical applications for generative AI, and company risk-managers are adjusting to the enthusiasm, according to one member of the team behind the findings.
“The scale at which ChatGPT rose to 100 million users was unprecedented. And it really caught most of corporate America by surprise. There were very few companies who had been experimenting, who had roadmaps, and who had been deploying the technology,” Christine Livingston, managing director and leader of AI and IoT at Protiviti, told reporters in Manhattan this week, upon announcement of the global consulting firm’s release of findings from the 12th annual survey, “Executive Perspectives on Top Risks for 2024 and 2034.”
“For the most part, corporate America was a little bit flat-footed. And we’ve seen 2023 as really being the year of catchup, where companies are trying to figure out: What is this technology, [and] how should I be using it?” said Livingston.
The risks revealed. The survey, conducted by the global consulting firm Protiviti and the NC State University’s Enterprise Risk Management (ERM) Initiative, polled more than 1,100 board members and C-suite executives from organizations worldwide and industrywide. Respondents were asked to rate a scary list of 36 macroeconomic, strategic, and operational risks on a sliding scale of 1 to 10, for the coming year and the coming decade.
The top 3 for 2024:
- Economic conditions, including inflationary pressures
- Ability to attract, develop, and retain top talent, manage shifts in labor expectations, and address succession challenges
- Cyberthreats
Despite the individual callouts, Mark Beasley, ERM Initiative director at NC State, advised survey readers to not assess the risks in isolation.
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“Generally, one is going to connect with another, and we’re going have a bigger event that we need to be prepared to navigate,” Beasley said during the press conference.
One event that Livingston said companies are preparing to travel through: the introduction of large language models (LLMs).
Livingston noted that orgs looking to catch up and find practical applications are frequently adding model-intelligence onto their internal knowledge bases, to act as a kind of “one-stop shop” for teams that need answers to their questions.
Another pro-services firm Deloitte recently noted how the materials company Eastman used generative AI to create outputs for sales members based on years of post-call documents.
“Live, in a sales interaction, they can ask questions of this digital guide on the side: this maybe-not-walking-but-talking consigliere,” Mike Bechtel, chief futurist at Deloitte, told IT Brew, citing advice requests like upsell suggestions or how to overcome objections.
An October Gartner poll found that almost one-half (45%) of exec-leader respondents are in a piloting phase for gen AI. IBM discovered a similar enterprise enthusiasm with AI, and that 96% of respondents “who have or plan to deploy generative AI are actively engaged in shaping new ethical and governance frameworks.”
Companies are increasingly seeking professionals who understand how the LLMs handle inputs and outputs, said Livingston, and enterprise architects with specific AI knowledge will be in high demand as companies seek speedy deployments.
‘“You’re starting to see actually a little bit less focus on the data scientists who can actually build a model and a little bit more focused on the engineering and the architecture surrounding it,” Livingston told IT Brew after the presentation.