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Real world GenAI use cases: How CIOs are putting AI to work
As CIOs look to implement GenAI, the number of potential use cases and vendor options can overwhelm them. Discover the tools that real CIOs are using across their organizations.
CIOs and other IT leaders face a common challenge: how to make generative AI more than just a buzzword.
As AI tools flood the market, CIOs can struggle to know which ones make sense for their organizations -- and which just add complexity. To cut through the noise, we asked CIOs and other tech leaders which generative AI (GenAI) tools their companies use and for what use cases. Their answers offer practical insights into what's working and how organizations are navigating AI adoption.
The following responses offer a valuable roadmap for CIOs wrestling with how to integrate AI into their IT strategies.
Does your company use GenAI tools? If so, which tools and how do you use them?
"Glean has been a big benefit for us. We're using that for summarizing knowledge and content in the service of customer support, and it's really working. Think about how bad enterprise search has been over our whole career. We finally have enterprise search that works, and it doesn't just give you the highlighted passage of a nine-year-old PowerPoint deck -- it actually summarizes and gives you an answer, which is amazing."
-- Graeme Thompson, CIO of Informatica
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"We use Microsoft Copilot ubiquitously at our company, and we use a couple of smaller niche tools for predictive sales. Our platforms, though, when we look at the heavy-duty workflows, include Pinkfish, which is our tactical, generative and agentic tool. Then we use Microsoft Copilot Studio and ServiceNow as platforms, and there's a little bit of Salesforce AI.
There are many layers to it. Some of the products that you already have -- let's say, Salesforce -- have an AI plugin. Other products you might use, like ServiceNow, also have an AI plugin. So, you've got to differentiate between what is a natural extension of the products you have and their AI plugins, versus what's a pure play AI product that is used ubiquitously across the top of everything. If you ask many CIOs this question, they might say 'Oh, I can use Salesforce AI, or I can use Workday AI for recruitment.' They're just generative plugins to their natural product set.
The real question is, how many of them are independent platforms that work with other platforms?"
-- Joe Locandro, CIO of Rimini Street
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"It's never been a trickier time to be an employee at a large company, but on the flip side, it's never been a better time to be a solopreneur. Why? Because I can't tell you how many conversations I had with named agent bots this morning as I was researching and writing my Substack. This would have required a 10-person team five years ago and 100-person company 25 years ago.
I'm on the $200 per month version of ChatGPT Pro. When you look at $200 a month through the lens of a Netflix subscription or even a Microsoft Office subscription, it can sound expensive. However, compared to having a secretary, payroll analyst and an accounts receivable department, it's a bargain.
I created custom GPTs or project folders with constitutional AIs. All that means is it's a vanilla GPT Pro -- which is like Megamind -- and I say, 'Your name is Beatrice. You're an accounts receivable expert. You understand tax law and you don't equivocate. You keep me on the right side of the law, politely and graciously with my clients.' It's almost like you're doing a Broadway show, and you're giving somebody the definition of their character for the script.
When I receive X, Y and Z, such as correspondence from the IRS, I toss it into those domain-specific agents and get back a world-class perspective on what it means. So, that's the reason I name them and make them domain-specific -- it's easier for me to think about who's on first and who's on second, rather than using one chat box for everything. It's like, 'That's a Bernie problem, that's a Toby problem and that's a Gladys problem.'"
-- Mike Bechtel, futurist, professor and entrepreneur
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"We use GenAI tools across engineering, support and knowledge management -- coding copilots, internal AI assistants for troubleshooting, and retrieval-augmented systems for documentation and case resolution.
But what's changed in the last year isn't the tools -- it's the governance layer we've had to build around them. Early on, we learned that plugging a large language model into enterprise data without guardrails creates confident, fast and sometimes dangerously wrong answers. So, the real work has been designing human-in-the-loop checkpoints, explainability requirements and clear accountability boundaries for when AI-generated outputs touch customers or production systems."
-- Nik Kale, principal engineer at Cisco Systems
Tim Murphy is site editor for Informa TechTarget's IT Strategy group.
