Andrew Chin has spent nearly three decades working at AllianceBernstein, along the way taking leadership positions involving the management of $829 billion in assets, overseeing quantitative research, and spending time with clients.
This diverse expertise made Chin a perfect candidate when the asset manager created the chief AI officer (CAIO) role a year ago.
“It’s easier for me to imagine reimagining our workflows with AI,” says Chin, who previously served as chief risk officer and chief data scientist. AllianceBernstein CEO Seth Bernstein and chief operating officer Karl Sprules asked him to step into the CAIO role to focus all of his energy on AI.
AllianceBernstein’s CAIO hire is certainly on trend: 60% of organizations have already established a CAIO and an additional 26% intend to do so in 2026, according to a recent international survey of 3,739 senior IT decision-makers conducted by Amazon Web Services.
While some debate whether the role belongs within the C-suite, especially as studies show that chief information officers have asserted more control over AI-related strategies across the internal business, CAIOs say their work is critical. They are frequently mandated to develop and execute a strategy that encompasses data management, AI governance, and workflow change management, while also developing partnerships with large AI companies like OpenAI and Anthropic and assessing pitches from software providers like Salesforce and ServiceNow.
But what CAIOs don’t fully agree on is whom they should report to. There’s a wide range of options, including the CIO, CEO, chief technology officer, and chief operating officer. This decision varies greatly, based on the company’s AI maturity journey, how much the technology is transforming product development, and to what level it affects workflows from the CEO to the frontline worker.
Chin reports to the COO, because he was adamant that the CAIO cannot report to a technology C-suite leader. “For AI, the focus has to be on the outcomes, not on the tools,” he says.
Intuit has taken a different approach. Ashok Srivastava, who spent nearly eight years as SVP and chief data officer but became CAIO last month, reports to CTO Alex Balazs. The pair work closely together to develop a road map for how the business software provider will invest in building AI-native products.
“I think Alex looks to me to understand the ways to utilize AI to give the maximum customer benefit,” says Srivastava.
Both leaders, alongside Intuit CEO Sasan Goodarzi and EVP and general manager Marianna Tessel, played a key role in steering the development and deployment of four AI-powered agents that Intuit recently rolled out for Quickbooks Online. Goodarzi told Coins2Day that the launch was “the most significant we’ve ever had in our history, because it’s end-to-end.”
Srivastava says the project developed quickly because of a decision that he and other senior leaders at the company made to create smaller, more nimble teams and reduce onerous meetings. “Just let them write code and experiment with customers,” says Srivastava of Intuit’s product development approach.
He also lauded Intuit’s investment in GenOS, a proprietary generative AI operating system that was built on AWS, as critical infrastructure that allowed the project to move forward in an efficient manner.
Howie Xu, the CAIO at cybersecurity software provider Gen Digital, says his scope is focused on three core areas, including how AI enhances the functionality of Gen Digital’s product, new opportunities for AI to be central to that product design, and how teams can use AI to be more productive.
“You don’t really need a chief AI officer if you are only talking about AI making some changes for productivity,” says Xu. “I don’t need to tell people, ‘Use ChatGPT.’ That’s a given.”
As it pertains to workflow changes, Xu operates under the assumption that every engineer at Gen Digital is already using AI-powered code editor Cursor and similar tools. That speeds up work and means that the old rules requiring product managers to schedule biweekly or bimonthly check-ins with engineers didn’t make much sense. Gen Digital is changing its approach: For one project now in development, product managers are meeting with the engineers in as little as two days.
“AI is going to do coding blazingly fast; sometimes it’s good, sometimes it’s less good, depending on the context,” says Xu. “How do you get 2x, 5x, or 10x productivity out of it? You have to have someone look at things more strategically, step back and zoom out, and reshape how a company does things.”
Fetch has had a CAIO for less than two months. Gowtham Gundu was recruited from Google—where he had worked for more than 18 years and most recently served as a director of engineering—to oversee the mobile shopping rewards app’s AI and machine learning strategy. Gundu says his goals for the role include laying out AI governance for the entire company, exploring partnerships, and developing go-to-market strategies for both internal and external applications of AI.
“My initial conversation with Wes [Schroll], our CEO, really got me excited about this role,” says Gundu. “There are so many aspects of this core business that require AI to be able to scale.”
Rajesh Arora, the chief data and analytics officer at Principal Financial Group, says some of his work overlaps with that of his boss, CIO Kathy Kay. They share the responsibility of ongoing conversations with existing software vendors like Salesforce and Oracle, though Arora takes the lead in exploring technologies from AI startups and hyperscalers like OpenAI.
Arora also leads the integration of data, analytics, and AI across all of the insurance and investment management company’s business divisions, coordinating closely with division presidents, as well as Principal’s shared services model across marketing and sales, to ensure that all data from different software systems are funneled into a centralized ecosystem.
He also coordinates upskilling efforts with the HR team, including an ongoing project to offer a specific education plan for 130 of Principal’s top executives. Globally, all employees will take training courses on data, AI, and learning how to prompt. The training launched in August at offices in North America and Europe, soon to be followed by Latin America and Asia-Pacific in September.
“It’s a pretty aggressive plan,” says Arora. “This is not going to be once and done. We’re going to continue to enhance our posture as new things come into play and as we make progress towards the maturity of our data and AI journey.”
