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ZDNET Key Takeaways
- While many companies appoint CAIOs, others are not so sure.
- Insurance specialist Howden has an AI productivity director.
- This expert ensures collaboration and efficient operation of assets.
There is much debate about who should be responsible for ensure the business gets the most out of generative AI. Some experts suggest the IOC should oversee this crucial rolewhile others believe that responsibility should lie with a data manager.
Beyond these existing roles, other experts defend the Chief AI Officer (CAIO)a newcomer to the C-suite who oversees key considerations including governance, security, and identifying potential use cases.
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ZDNET reported last year that 60% of companies already have a CAIOand 26% plan to make an appointment this year.
Experts say the rise of CAIO illustrates The important role of AI in modern business. Yet not everyone believes that a dedicated CAIO is necessarily the best solution to the challenges associated with implementing AI.
Last year, Kirsty Roth, director of operations and technology at Thomson Reuters, told me that her organization didn’t have CAIO. “No, we’re not very interested in that sort of thing,” she said, suggesting that the inherent role of AI in her company’s processes meant that emerging technologies needed to be considered by the entire staff rather than in isolation.
However, importantly, Roth also recognized that the ever-increasing importance of AI in business operations means that a manager must ensure that demands for emerging technologies are managed effectively: “I guess if you don’t have anyone playing those roles, then you’ll probably have to think about who you have or how you augment your existing managers.
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That sentiment was echoed by Barry Panayi, group chief data officer at insurance company Howden, who told ZDNET that his company had created a dedicated role for a director of AI productivity, a specialist who sits between Panayi’s data organization and the IT department, creating a strong collaborative interface with the rest of the company.
So, what does this specialist do? Here are three reasons why your company needs a Chief AI Productivity Officer.
1. Connect everything
Many people in other business units are confused about the different roles of technology and data teams. When Panayi joined Howden in August last year, he decided to avoid this problem at the pass.
Barry Panayi: “These tools are new enough that we need people to help us adopt them. »
Howden
“The technical director and I are sitting next to each other and we said early on that we need to draw a clear line on this, because if we don’t agree, it’s not going to be easy. And we both thought the same thing,” he said, referring to their solution to this intractable challenge.
“If you buy a tool and people just use it, then technology should own it and operate it, because it needs to be installed on their platforms and hooked up properly,” he said.
“There’s a little bit on the data side, which is building custom models, like for machine learning. And then there’s a little bit in the middle, where you do both, so you can use the ChatGPT API to do LLM processing for something, and then we’ll write code on top of that.”
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Panayi called this divide between IT and data “a build-or-buy decision, with a slice in the middle.” This sparkle is the meeting point where the AI Productivity Manager plays a crucial role.
“I think companies are missing a trick if they don’t have someone making sure people are using things like Copilot, etc. These tools are new enough that we need people to help us adopt them,” he said.
“And right now, I don’t think we can assume that the narrative about people using AI at home to help them book vacations is the same as how it can help them be more productive at work.”
2. Ensure assets are leveraged
Panayi said the role of the Director of AI Productivity at Howden is to ensure that everyone in the company is using enterprise generation AI services effectively.
“I see this as a way to leverage technology and tools. Their immediate concern is making sure our business is doing everything possible to use the tools we pay for, and Copilot, ChatGPT and Anthropic are our three main enterprise licenses,” he said.
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“We realize that right now, Copilot is great if you’re in Office and you need an AI to summarize things. Then you have Claude, who, if you’re an engineer or in finance, can give you detailed insights. And then there’s ChatGPT, which is your kind of brains for hire.”
The company uses other tools and templates for specific projects. Panayi described overseeing the effective use of these enterprise and point solutions as a job and a half, given that Howden employs more than 20,000 people in 55 countries.
“It’s like he’s a magician, showing people who have to deal with thousands of pages of stuff how to quickly get the answers they need,” he said, describing how the productivity director promotes the benefits of AI generation to the company’s brokers.
“These people are not in front of the computer all day. They are in the market, discussing and making decisions.”
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Panayi said that effectively harnessing emerging technologies requires a nuanced approach, which the AI Productivity Manager offers by outlining how AI can be used safely, securely and effectively.
“He has so many examples of people saying that things like a task that used to take them a week can now be accomplished in 20 minutes, with an officer running the operation every Monday,” he said.
3. Focus on competitive advantage
The AI Productivity Manager collaborates with the Howden IT team to ensure employees understand what tools are ready and available for work tasks.
“Allowing everyone to use these tools is not about the data, it’s about the technology. This approach takes a ton of demand off the data team, because managing the demand for generational AI is not my job, fortunately,” he said.
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“I’m not here to promote Copilot and other models – it’s an IT tools decision, which I think sounds obvious when you say it. But I’ve seen too many data teams drown because they were trying to manage the organization’s use of Copilot.”
Panayi said the AI productivity manager’s ability to get everyone using business-generating AI tools means his data team can work on projects that make the most money for the company.
“All of these generational AI efforts are great and powerful, and create a lot of productivity, but I’m focusing more on AI machine learning because I think there’s incredible power there,” he said.
At a time when many organizations and employees have access to similar models and agents, Panayi said your competitive advantage comes from leveraging proprietary data and models.
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“We assess the risks, the potential impact and decide what the price of our products should be,” he said.
“It’s a scientific numbers game, so we can provide scenarios for brokers to apply their knowledge. It’s about providing brokers or underwriters with new information and ideas, and then they will build the product.”