To hear the hype from vendors, you’d think business buyers are all in on the genetic AI thing. But like any new technology, big companies tend to tread carefully. Throughout this year, as vendors feverishly announced new AI-powered products, CIOs took notice.
Some companies are actually trying to cut costs, or at least stay balanced, without necessarily looking for new ways to spend money. The big exception is when technology allows companies to operate more efficiently and do more with less.
Generative AI certainly has the potential to do this, but it also has its own costs associated with it, whether it’s a higher cost for these capabilities in a SaaS product or the price to expose a large language model API, if you build your own software internally.
Either way, it’s important for the people implementing the technology to understand if they’re getting a return on their investment. A July Morgan Stanley survey of CIOs at large companies found that many were moving cautiously, with 56% of respondents saying genetic AI had an impact on their investment priorities, but only 4% had actually started major projects. In fact, most were still in the evaluation or proof-of-concept phase. This may be a fast-moving area, but it fits with what we’re also hearing in conversations with CIOs.
That said, just like the consumer use of IT a decade ago, CIOs are under pressure to deliver the kind of experiences people see when they play with ChatGPT online, says Jon Turow, partner at Madrona Ventures.
“I think it’s undeniable that the people in the business, who are the internal customers of the CIO or CTO, have all tried ChatGPT and know how amazing it is. They know where it’s early, and they know where it’s inspired, and for lack of a better word, where they see greatness. And so CIOs are under pressure to deliver that level,” Turow told TechCrunch.
It has created a tension between that desire to please internal customers, especially when some of that pressure could come from the CEO, and a CIO’s natural tendency to tread carefully, even with something as potentially transformative as genetics. Artificial Intelligence. This will require creating some structure and organization around how this will be implemented over time, says Jim Rowan, a director at Deloitte who works with clients on how to build productive AI in all companies in an organized manner.
“A lot of the way we work with companies is to think about what infrastructure they need to be successful. By infrastructure, I don’t necessarily mean the technology, but who the people are, what the processes and governance are…and empowering them to create that,” Rowan said. A big part of this is talking about use cases and how to use the technology to solve a given problem.
This is consistent with how the CIOs we spoke to are approaching the implementation of this in their organizations. Monica Caldas, CIO at insurer Liberty Mutual, started with a proof of concept of a few thousand people and is looking for ways to scale it for her 45,000-employee company.
“We know that genetic AI will continue to play a critical role in almost every part of our company, so we are investing in many use cases to further develop and improve them in the service of supporting our employees and empowering them internally “, he said.
Mike Haney, CIO at Battelle, a science and technology-focused company, is also exploring genetic AI use cases this year. “So we’ve been doing this whole AI push for maybe the last six or nine months, and we’re at the point right now where we’re building specific use cases for every different team and function within the company.” He cautions that it’s early and they’re still exploring ways it can help, but so far the results have been good in terms of offering more efficient ways to get things done.
Kathy Kay, executive vice president and managing director at Principal Financial Group, a financial services firm, says her company started from scratch with a study group. “So all the employees who had an interest or a passion, we allowed them to join, so there were about 100 people. It’s a mix of engineers and entrepreneurs and we’re curating probably 25 use cases now that they’ve passed and three will go into production [soon],” he said.
Juniper Networks CIO Sharon Mandell says her company is participating in an initial pilot program with Microsoft around Copilot for Office 365, and anecdotally, she’s heard a range of comments from people who love it to those who are impressed. less, but he says trying to measure increased productivity remains a challenge, even as Microsoft has begun providing dashboards that at least show the level of adoption and usage.
“The hard thing about it is that you don’t have data on people’s productivity level. So no matter what, you’re kind of using anecdotal information until you really understand these dashboards from Microsoft that show you how people are using them,” he said.
As companies hear about the potential power of genetic AI, it’s only natural that they want to learn more about it and put it to work to help their organizations run more efficiently, but at the same time, executives are right to be somewhat wary. . recognizing that it is still early days and they need to learn through experimentation if this is truly transformative technology.
