It has been one year since the launch of ChatGPT — and since then, we’ve seen a Cambrian explosion of new AI tools and platforms. How will AI remake corporate innovation in 2024? InnoLead convened a group of experts to discuss, including Matt Baker, SVP of Strategy at Dell Technologies; David Lee, AVP of New Growth at Cox Communications; Jerry Gupta, SVP of R&D at Swiss Re; and John Sviokla, co-founder at the analyst firm GAI Insights and a co-author of the recent “Corporate Buyers Guide to LLMs.”
Among the topics the group covered:
- How should companies be talking about AI versus Gen AI right now?
- Should this just be the domain of IT? How should other groups be getting involved?
- Pauses / bans / freezes on generative AI use in big companies. Bad idea? Good idea?
- How is AI going to change the work of corporate innovation?
- What’s the case for how generative AI specifically takes over the innovation leader’s agenda over the next year or two?
- How do you get up to speed on the tools and technologies?
- How do you deal with organizational nay-sayers?
“The innovation teams, and sometimes the technical architecture teams, have been able to be the first ones out of the gate” working on generative AI projects, said Lee. “That’s been true for the last year, and certainly true since November [2022]. I think it’s because those are the two places in the organization that have all three pieces that you need to build generative AI tools. You’ve got people who can do back-end and front-end web development, you’ve got people who can mathematically look at data and pull data from various data sources. And then the third thing is, you have people with a sort of business lens. …You [need] all three to sort of get these first prototypes out of the table…to tinker and try stuff out.”
Gupta said that many companies, after a period of hype, are realizing that generative AI may be risky to deploy in certain areas of the business, and are hitting the “pause” button: “I think what we saw initially was a lot of hype, a lot of interest, a lot of excitement. But I think now, we are seeing a little bit of a rational approach, where companies are realizing that the potential risks, at least at this point of time, may outweigh the benefits. …That’s a really broad statement. And that statement is very use-case specific. [For] document retrieval, data extraction — those are pretty low-risk activities, that I think companies should feel fairly comfortable using LLMs for. Things that have a brand impact, could have adverse customer impact, finance — that’s where some of the issues are.”
Gupta said that many companies are still in the “use case generation and prioritization phase…going through the organization, pulling up those 30, 40, 50, 60 use cases, and sort of prioritizing them on the basis of risk and value.”
Baker said that internally surveying at Dell Technologies had unearthed nearly 400 AI-related projects, about half of which leverage generative AI tech. The company has identified a handful of priority use areas, including sales productivity, developer productivity, and content creation, where projects are most likely to be green-lit.
Sviokla said that at firms that want to use generative AI productively, “senior executives who hold the purse strings…need to have actual, hands-on experience…relatively deep experience.”
This event was recorded on LinkedIn on November 16, 2023. To watch the replay, click “play” above.
(Featured image by Igor Omilaev on Unsplash.)
