How CIOs align with CFOs to build RevOps

Generative AI continues to blur the lines between IT and business, demanding a new breed of CIOs. So forward-thinking tech execs are upskilling in finance and building cross-functional relationships to bolster AI-driven revenue operations and corporate transformations.

The first use of generative AI in companies tends to be for productivity improvements and cost cutting. But there are only so many costs that can be cut. Growing revenues, on the other hand, is where you can see an unlimited upside.

CIOs are well positioned to cut costs since they’re usually well acquainted with a company’s digital processes, having helped set them up in the first place. All it takes is an understanding of how gen AI works, its applications, and limitations. But to find ways it can help grow a company’s bottom line, CIOs have to do more to understand a company’s business model and identify opportunities where gen AI can change the playing field. That means using the technology to improve a company’s marketing, sales, customer success, and RevOps: the process of aligning all three operations across the full customer life cycle in a way that drives growth, improves efficiency, and breaks down silos.

To become full partners in revenue operations, CIOs have to build on their relationships with CFOs and other leaders on the business side, upgrade their business skills, and truly understand both the business benefits and limitations of new gen AI technologies.

Revenue leaders embracing AI

The interest is there on the business side. Sales and marketing departments have long been at the forefront of embracing new technologies, and according to data provided by the Alexander Group, a revenue consultancy, 80% of hundreds of survey responses detailed that CROs have formally invested in AI for their marketing teams. That includes many technologies based on machine learning, such as sales forecasting, lead scoring and qualification, pricing optimization, and customer sentiment analysis. But the single biggest AI-enabled tool used this year so far is marketing content generation, a gen AI-powered technology used by 58% of the leaders surveyed. Another 40% say they’re using AI chatbots or virtual sales assistants. In addition, 66% are making investments this year in AI for marketing, 65% for sales, 62% for service, and 52% for RevOps.

“Using the models for content creation is the leading use case on the marketing side and the sales side,” says Mitch Edwards, principal at the Alexander Group. “And hyper-personalization at scale.”

But each company’s revenue operations are different, he adds, and CIOs should understand their companies’ business needs as well as the AI itself.

“You should be on the forefront of the technology, and be the one who translates the business need into how to adjust the tech stack to drive those goals,” he says.

Cross-disciplinary AI groups

Matthews International, a manufacturing industry conglomerate with $2 billion in annual revenues, set up its AI council early last year, soon after ChatGPT launched. The council has people on it from both the IT and the business sides, says company CIO Davor Brkovich, and technologists are needed in order to understand what’s possible and to make sure the AI is governed appropriately.

“But you don’t want to be totally technology focused,” he says. “The point of AI isn’t to create AI, but to solve business problems.”

Brkovich, who also teaches a financial management class for CIOs at Carnegie Mellon University, says, in his experience, the relationship between the CIO and the CFO is the most important relationship a CIO has.

“Strategic planning, revenue enhancement, budgeting — all of those are incredibly important topics that CIOs need to work on with their CFOs,” he says.

And revenue operations is part of that.

For Matthews International, this mostly involves traditional aspects of RevOps, such as customer relationship management, lead generation, and closure.

“We’re mostly still optimizing our sales and marketing processes with CRM tools,” he says. “But we’re certainly looking at AI as an organization across our lines of business.”

The first and most obvious use cases for gen AI are all about improving efficiency, he adds.

“We’ve been doing proof-of-value and different test cases on efficiency opportunities within our organization as it relates to AI,” he says.

Increasing revenues, however, is a more challenging proposition, and the company is just starting to think about the potential opportunities here.

“We’re discussing ways to optimize and maximize revenues from a CRM perspective,” he says. “We’re also having discussions with both the CFO and the lines of business relative to AI, and we have the AI council, which is responsible for making sure we’re doing AI responsibly and governing it securely, and for workshopping opportunities for AI in different lines of business.”

Progress in this area will require tearing down silos, he says, and closer working relationships with sales, marketing, and customer success. So for technology leaders who want to be key players in their companies’ transformations, the first step, he says, is to pivot from focusing on bits and bytes to debits and credits, starting with the finances of the IT organization itself. Then the CIO can use that knowledge to ensure the success of technology initiatives that support business strategy, and then continue to expand their knowledge of finance and business from IT to the company as a whole.

“The most successful CIOs are those who spend time and energy on financial management,” he says. “You can’t have an efficient and effective IT function if you don’t know the finances there. Nor can you help the business if you’re not knowledgeable in the overall finances of the organization.”

Find key business partners

For some technology executives, launching a gen AI project that eventually leads to corporate transformation can start small, with just a couple of key relationships.

“What I’ve always tried to do is go where the energy and value is, and find the one or two willing partners in the business who want to start something and make it big,” says Christopher Paquette, chief digital transformation officer at Allstate Insurance. Years ago, when mobile was the big technological wave, this meant finding people on the business side who were enthusiastic about building a mobile app.

“Now, with generative AI, ask who are those one or two executives who are really leaning into this,” he says. “Partner with them and create value from it.”

Being able to speak their language is critical, too, and the place to start, he says, is with the core economics of the business.

“How does it make money and what are the levers you want to pull?” he asks. “If you’re coming from a technical background, and you don’t know the industry, learn it. Take a class. Spend time with executives. Do a tour so you can understand the business.”

At Allstate, for example, customer retention is one of its biggest revenue drivers, and all of that is dependent on having the best possible customer experience, which is an area where gen AI can make a difference.

Gen AI turns IT from cost center to revenue generator

In some cases, an internal IT project, when led by business-savvy tech execs, can become a revenue opportunity in itself. That’s exactly what Bill Fandrich, EVP of technology and operations, is doing at Blue Cross Blue Shield Michigan, the state’s largest HMO with more than 10,000 employees and $36 billion in annual revenues.

But the company also has two gen AI projects already in production bringing in revenues, and a third about to go live, but they’re in a different category.

Blue Cross Blue Shield Michigan is taking gen AI systems it built to improve security, efficiency, and customer service, and turning them into products and services it can sell to other Blue Cross Blue Shield organizations.

“We quickly learned we needed to build models internally in a dedicated environment or a cloud environment that’s 100% secured and controlled,” he says. “We have a HITRUST certified health care environment and we bring in publicly-available models.” The models then get additional training and controls within that environment, he adds.

The first gen AI model, called SecureGPT, was designed to help with cybersecurity, he says.

“We have a unique security solution that addresses every facet of what we’re required to do for our customers and members, including integration with our existing security systems for authentication and role-based access,” he says. “And there are audit trails for everything.”

In addition to selling this product to other Blue Cross Blue Shield organizations, Fandrich says, he’s also using it internally.

The second model was trained on contracts and developed with the help of an outside vendor.

“There are hundreds of thousands of contracts constantly in a state of change that support our business,” he says. “This solution can read, interpret, analyze, and build taxonomies.”

Both systems were released earlier this year and are commercially available via a subsidiary, which provides services to other Blue Cross Blue Shield companies. And they’re already bringing hundreds of thousands of dollars in new revenues.

A third gen AI product, BenefitsGPT, isn’t yet commercially available, but is currently being tested by three other Blue Cross Blue Shield organizations.

“Everyone knows how challenging it is in healthcare to get the right information about what’s covered or how much it costs,” he says. “This brings in intelligence from all the data, and from unstructured documents, so for an individual, we can answer the questions they need answered.”

The income streams from these new projects are small compared to the total size of Blue Cross Blue Shield Michigan, he says. But that could change. “I expect we can generate a significant amount of new revenue by helping other health plans transform themselves,” he says.

And that’s just the start. In the health insurance industry, there are plenty of opportunities for transformation if you know where to look. For example, gen AI can help staff understand the unique needs of individual patients. “It opens up new revenue opportunities and also brings access to things the individual needs at that particular point in their life,” he adds.

It’s too early in the process for him to talk about specifics, though, but these kinds of projects can be truly transformative. And it’s more of a business transformation than a technological one, requiring a team with multi-dimensional skills sets.

Fandrich says he’s had a business-centric attitude toward technology since he joined the organization seven years ago, with a focus on how to work with the business side differently, and bring in the domain knowledge needed to build successful solutions.

With gen AI, he says, things are moving faster than ever before. “And I think we all know the only thing we can guarantee is that the pace of change is only getting faster,” he says. “What we traditionally called change management is now unbelievably bigger.” And that means IT executives need business and financial skills more than ever.

“The macroeconomic challenges and opportunities of generative AI dramatically change the economics of companies,” he says. And that means the roles of the IT organization and the roles of the business units are starting to blur.

“The power of generative AI is its transformative nature,” he adds. “You can’t do that purely from the technology or the business — you need the marrying of the two.”

The future of the CIO

CIOs who transition IT from being a cost center to being a driver of innovation, transformation, and new revenues, can become the leaders that the new economy needs.

“We used to say that business runs technology,” says David Kadio-Morokro, EY Americas financial services innovation leader. “You tell me what you want, and I’ll code it and support you.” Now it’s switched, he says.

“I really believe technology drives the business, because it’s going to impact business strategy and how the business survives,” he adds, and gen AI will force companies to rethink the value of their organizations to customers.

“Developing and envisioning an AI-driven strategy is absolutely part of the equation,” he says. “And the CIO has this role of enabling these components, and they need to be part of the conversation and be able to drive that vision for the organization.”

The CIO is also in a position to help the CFO evolve, too. CFOs are traditionally risk averse and expect certainty and accuracy from their technology. Not only is gen AI still a new and experimental technology that’s evolving quickly but is, by its very nature, probabilistic and nondeterministic.

“The CFO may have to be a little bit more comfortable with ambiguity and things being experimental,” says John King, partner at Lotis Blue Consulting. “A lot of these tools are still cutting edge, and it may be a little unsettling for the CFO.”

There’s also a lot of wild information out there about what gen AI can do, some of which might be true, but some isn’t, he says.

“As a CIO, you’re helping them understand what the technology can really do,” he adds. “And you want to have some guardrails so you’re not doing things that don’t make sense.”

He recommends that CIOs just entering on this journey should start small.

“Get your feet wet in something that’s well understood,” he says. “It’s a mistake to try to go too far, too fast.”

You don’t want to get out too far ahead of the technology, he adds, but, at the same time, you don’t want to miss opportunities.

“A CFO would just say to wait and see what the risks are,” he says. “But then you’re just playing catch-up. You might wind up losing revenue opportunities when you do that.”

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