Is AI really paying off for companies? CIOs weigh in

Is AI paying off yet?

Yes, it's paying off, but not yet at the scale many expected. The technology has largely proven itself. What's holding organizations back is the challenge of operationalizing AI responsibly. Governance frameworks, security controls, data readiness, regulatory compliance and clear accountability are often lagging behind the pace of innovation.

At the same time, many employees remain uncertain about how AI will affect their roles, which can slow adoption. The biggest success stories are coming from companies that focus not only on the technology, but also on trust, transparency and organizational change.

-- Eric Helmer, executive vice president and CTO, Rimini Street

People are finding incredible value in the LLMs they have access to compared to deep learning models and other tools data scientists use. But it's not playing to the playbook that big tech and frontier labs want.

I was in a room with 50 people -- a council for a software company -- and they were telling us how they used AI. The top use cases were, "They just learn how I work, and they're my personal assistant. They help me write emails and write documents."

That's very low-level work that in the next year or two is going to be standard, and we're not even going to be talking about AI anymore. Whereas we've got companies that have had trillions of dollars invested in them that need to get a return. We're going to be at this pivot point where we've got someone paying $100 a month for a subscription and suddenly being asked to pay $1,000 or $2,000 per seat to give that payback to the investors. It's not going to make sense simply because low-level work is upskilled slightly.

 -- Nikolas Badminton, futurist and keynote speaker

It's paying off if you're doing it right. There are a lot of companies that, when you look at the tokenmaxxing nonsense, probably not. I don't tokenmax in my environment. Everybody gets a limit. What I ask people to do is tell me how much time AI saved you. What's the business value and benefit to this? And if we can't show a business benefit or value, then we don't pursue that use case.

But it is certainly paying off. In a sales team, for instance, we have -- and Anthropic has this as well -- a branding skill. It's the ability for a sales team to sit down with a customer and turn around a fully branded sales deck the next day. That makes a meaningful impact on the sales cycle and the customer experience. Our AI code factory, which we built and many other organizations are building, has agents that can not only write code but also audit it to our standards. It can do the security review and tee that up for us to look at and approve. That makes a meaningful impact.

So, there are places where it's making a big impact, but there are a lot of nonsense use cases where, if you bring in an AI consultant, they'll have AI running your vending machine.

-- Tony Garcia, chief information and security officer, Infineo

I think it is paying off, but I would be careful about what we call a payoff. There's a difference between helping someone finish a task faster and improving the economics of an entire operation. Time saved has value, but I want to know what we did with that time and whether the benefit holds up once we account for checking the work and running the technology.

At DeVry, I look at this through the student experience. If AI reduces the routine work around advising and gives an advisor more time with a student who needs help, that's a useful return. I would want to measure whether we actually created that capacity and improved the service. A faster task by itself does not tell me that.

I am comfortable pursuing those practical gains while being disciplined about larger claims. We still have to show that the work is better and that the full cost makes sense.

-- Chris Campbell, CIO, DeVry University

It's paying off in some cases. Organizations on the bleeding edge are struggling with that. We look to be a fast follower. We know what's happening in the marketplace, and we look for point-based requirements where we can make a net positive impact.

That's not a global answer because some of the investments people have made have been out of line with evaluating an ROI. And not everything has an ROI, so I don't want to suggest that it does -- but if you're strategic in your assessment of what you're trying to get and strategic in your implementation, there is a positive ROI to be had. We have seen a positive ROI.

-- Jim Begley, CTO, ARG

Yes, it's paying off for a relatively small group of companies. For most companies, the answer is still "not at scale." We have plenty of evidence that AI can improve productivity and customer experience and make business processes efficient, but the enterprise-wide financial returns are much harder to realize and demonstrate. It's like AI is everywhere, but ROAI is still under the surface.

The challenge organizations face is that while they can measure AI adoption and experimentation, they lack the discipline to measure value realization.

-- Manish Jain, founder and CEO, Strategic Horizon Research

Yes, but not at the rate that everyone anticipated. AI is certainly creating measurable efficiencies and value in how people work. It's automating tasks, helping to create better work products and better preparing associates for client interactions.

The part every company struggles with is how to translate that into meaningful savings and growth. That is more difficult because it involves understanding how work gets done today and redesigning the work based on the new capabilities introduced by AI.

For example, we've automated much of the policy checking and quote compare processes. Those processes are parts and pieces of many jobs throughout the organization. So, to quantify those time savings, we have to look at what those roles now do with the time they are saving. Are there things they should be doing that they didn't have time to do before? Do we need to redesign the role and replace those tasks with higher-value, client-facing work? Do we need to allocate resources to another process?

Without that work redesign, everyone just becomes more efficient in their current work, but we don't repurpose those hours to something that drives more value for the company and our clients.

-- Matt Watkins, CIO, IMA Financial Group

Yes, it's paying off for a significant portion. Organizations with defined AI strategies are more likely to see a measurable impact than those without them. In our survey, 42% of organizations report department-wide AI adoption with measurable impact. Another 28% have department-wide adoption with no clear impact.

We see creating a formalized AI strategy as an important step towards achieving that value. Among organizations with a dedicated, board-approved AI strategy, just under 60% report department-wide adoption with measurable impact. Among those still drafting a strategy, that drops to 16%.

If you can't create a dedicated AI strategy, at least address it as part of a broader strategy. Organizations with AI goals partially embedded in a broader IT or digital strategy sit in between at 32%.

-- Brian Jackson, principal research director, Info-Tech Research Group

Tim Murphy is a reporter covering IT strategy for Informa TechTarget, with a focus on IT leadership, governance, workforce skills and AI strategy. His enterprise technology coverage has earned multiple Azbee Awards.