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ZDNET’s key takeaways
- Boards are starting to ask tougher questions about money sunk into AI.
- Interrogations into the value of AI projects are an opportunity to re-focus.
- Concentrate on capacity building, strong partnerships, and co-development.
The amount of money that organizations invest in AI shows no signs of abating. Worldwide spending on AI is forecast to reach $2.52 trillion in 2026, a 44% year-over-year increase, according to tech analyst Gartner.
However, there’s a twist in the tale. With AI slipping into the abyss in Gartner’s Hype Cycle for Emerging Technologies, boards are starting to ask tougher questions about the money spent on AI explorations, and digital and business professionals will be expected to turn dollars and cents into tangible benefits.
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ZDNET reported last year that several areas of AI have slipped into the Trough of Disillusionment, where interest in a technology wanes because explorations fail to deliver promised returns. That’s exactly where generative AI finds itself right now, with hype fading and business leaders questioning the ROI.
Many organizations have barely found a way to make the most of the technology. Now, interest in gen AI appears to be waning, and the bubble surrounding the emerging technology could be about to burst. Sounds like bad news, right?
Yet John-David Lovelock, chief forecaster and distinguished VP analyst at Gartner, told ZDNET in a one-to-one interview that the slide should be seen as a sign of hope. Slipping into the trough allows everyone to think much more carefully about their investments in gen AI. In short, business and digital professionals should embrace the opportunity.
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“They probably should be looking for AI to slip into the ditch,” he said. “The trough is all about expectations being at their lowest. And the problems we have seen with AI in the last two years are connected to these over-the-top moonshot projects.”
With MIT research suggesting that 95% of gen AI projects fail to deliver value, Lovelock said a new approach is required to ensure AI investments are focused on the right targets. He suggested the following three areas should be priorities through 2026.
1. Focus on capacity building
Gartner reports that a massive build-out of AI infrastructure will characterize emerging tech investments through 2026.
Building AI foundations alone will drive a 49% increase in spending on AI-optimized servers, accounting for 17% of AI spending this year. AI infrastructure, meanwhile, will add $401 billion in spending in 2026, as technology providers build out their foundations.
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Lovelock said this investment by IT companies will be crucial, even as AI drops into the Trough of Disillusionment. “They are building the capacity needed to run all the AI that’s coming,” he said.
“This area is where we have the hyperscalers, tech providers, and even software companies buying AI-optimized servers to build data centers that provide the capacity to train new models, train agents, and run agents.”
Lovelock gave the example of a finance organization that’s looking to find the capacity to run a model that automates credit card approvals.
The organization has several choices — it could run its own standalone data center; work with a big-name cloud provider like AWS, Microsoft, or Google; focus on a platform provider that manages compute; or make an API call to a large language model from a specialist like OpenAI.
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The key to success, said Lovelock, is deciding how the provider’s capacity-building approach suits your organization’s resources and priorities.
“You need to ask, ‘How deeply do I need to own this technology? How much can I deal with it as a commodity? And how much of our approach is about differentiating AI that we must own, operate, and create?'”
2. Create strong partnerships
Finding suitable answers to those kinds of questions will involve building close relationships with technology providers.
Lovelock suggested that these partnerships will be crucial for business and digital professionals who want to improve AI ROI through 2026.
“This year, most people should be looking for the technology coming from their established partner stack,” he said. “It’s only the leaders, the visionaries, who should be looking to self-develop AI solutions or push the envelope.”
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With AI in the Trough of Disillusionment throughout 2026, it will most often be sold to companies by their incumbent software providers rather than bought for a moonshot project.
Rather than spending time and money on developing bespoke solutions, Lovelock agreed that most companies should focus this year on making good bets on solid tech partners across the digital and data stack.
“That’s exactly right,” he said. “It’s about finding your technology partners to take you on your path, whether that’s simple use of AI or you’re going to push toward being an autonomous business.”
3. Avoid random explorations
With gen AI sliding into the Trough of Disillusionment, Gartner suggests professionals should avoid broad-brush explorations into emerging tech and instead focus on ensuring that the best of their moonshot projects reach the stars.
So, how can digital leaders and their business peers ensure that exploratory projects turn into valuable initiatives? Lovelock suggested focusing on three areas: “Partners, data, and processes.”
Another crucial element, he added, is bringing along internal stakeholders for the ride from the moon to the stars.
“Success is all about line-of-business functions as well,” he said. “How well are you focused on defined business outcomes? How well can your partners help you with meeting these requirements? What level of investiture do they have?”
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Lovelock said the best relationships will ensure you and your supplier benefit from turning moonshots into valuable production services.
“If you’re doing time-and-materials billing, your provider has no skin in the game. If you’re doing value-based pricing, they have some. If you’re doing outcome-based pricing, they have more. If you’re doing co-development, that’s great,” he said.
“The best approach is about tying their reward to your outcome. Now, that is not easily accomplished. It’s a difficult approach to sell across the organization. It’s also a very deep and tricky relationship to maintain over time. But when it works, it’s incredibly and deeply rewarding for both participants.”
