Companies look to sell off assets to pay for AI investments

CIOs worried about where the money for new AI initiatives will come from may have some help on the way, with some companies apparently selling off non-core assets to pay for new AI projects.

Nine of 10 CIOs surveyed by Gartner late last year expressed concerns that managing AI costs was limiting their ability to get value from AI. But some companies, particularly in the IT sector, now appear to be reevaluating their business models and will consider selling non-core lines of business and products to fund AI projects, says James Brundage, global and Americas technology sector leader at EY, an IT and tax advisory firm.

AI is both a huge potential gamechanger for many companies and a huge expense to get right, he says. Until now, many companies have cut costs in other areas, laid off staff, or raided the budgets of other departments to pay for AI projects.

“When we’re talking with clients right now, one thing that they’re looking at doing is divesting of non-core assets to generate that capital,” he adds.  “If you look at ’23 and 2024 you had a lot of budget increases, you had a bunch of layoffs over the last couple of years, and not something that’s sustainable.”

The divestiture trend is most pronounced in the IT sector, Brundage says, because of the need for funding while companies build the technology, infrastructure, and applications to enable AI.

However, other sectors will face the same funding needs as they transform to an AI-first operating model, he adds.

The interest in funding AI projects isn’t slowing down. A survey from the Data & AI Leadership Exchange, an organization focused on AI and data education efforts, found that 98% of senior data leaders at Fortune 1000 companies expect to increase their AI spending in 2025, up from 82% in 2024. Over 90% of those surveyed said investments in AI and data were top priorities.

Meanwhile, several EY clients have talked with the advisory firm about divesting non-core assets to raise more money for emerging technologies including AI, Brundage adds.

New interest in divestment

In a report released in September, 59% of IT CEOs surveyed by EY said they intended to pursue a divestment, spin-off, or IPO in the following 12 months. EY, in a recent blog post focused on top opportunities for IT companies in 2025, recommends money raised from these activities be used on AI projects.

With a political shift in the US that may be more friendly to mergers and acquisitions, 2025 “may be a moment for tech companies to free up capital for high-growth opportunities like AI through optimization of their portfolio via targeted strategic divestitures,” Brundage and his blog coauthors write.

Divestitures can also help companies zero in on their potential and market relevance, the blog authors note. “In addition to raising capital, we find divestitures tend to create more focused, agile and streamlined operations which are better suited to sustainable AI investing,” according to Brundage and his colleagues.

While Brundage didn’t offer examples of EY clients that are considering divestiture to fund AI projects, some companies have already taken the plunge.

In May, electronic design automation firm Synopsys announced a sale of its security testing software business for $2.1 billion. The sale allows the company to focus on AI-driven engineering, the company said.

Also in May, information management and cloud firm OpenText sold off its application modernization and connectivity business for $2.28 billion. The company used the sale to reduce debt and to focus on innovation in cloud, security, and AI markets, it said.

Alternative funding options

While Brundage sees a trend developing, other IT market observers are skeptical that companies will divest non-core assets specifically to pay for AI projects.

Companies will need to invest in AI to stay relevant, but funding may come from a variety of areas, says Christian Hed, CMO at Dstny, a provider of cloud-based business communications solutions.

“I’m not convinced that AI costs are the primary driver for divestment in other areas,” he says. “Divesting in legacy revenue is often driven by the desire to eliminate technical debt, increase the multiple by enhancing the percentage of quality revenue, and allow resources to focus on generating the right type of revenue, among other factors.”

In addition, beyond allowing companies to invest in AI, divestiture could allow them to improve competitiveness and efficiency, to focus on other innovation, and to unload underperforming units, Hed says.

Instead of selling off assets, some organizations are using private equity funding to increase investments in AI, adds Claire Milligan, CEO of cloud cost optimization firm Aimably. In some cases, companies are turning to “creative” funding options, including private credit and so-called continuation funds to pay for AI projects that have not yet generated revenue growth, she says.

“In private markets, investments in AI projects are seductive to equity investors as a justification for cash infusion to their holdings without the need to sell off assets,” Milligan says. “By capitalizing these projects as research and development, investors open the door to new sources of funding for existing portfolio companies, such as private credit or a transition to new fund vintages, without requiring investors to demonstrate value creation success to public markets.”

The danger to investors and companies, however, is a continued lack of revenue from many AI projects, she adds. “Reinvestment activities into existing portfolio companies are necessary as these companies’ revenue performance has been lacking,” Milligan says. “If portfolio companies cannot reduce these projects to revenue engines, more recent fund vintages have a strong potential to deliver poor returns.”