AI ROI for businesses expected to materialize in 2026 as experts predict shift from hype to results

AI might finally deliver real ROI for businesses in 2026 - and experts say this is why

AI will enter a new phase in 2026, analysts said. Businesses will better leverage the tech and see results. AI agents and commerce opportunities will be key. The AI hype fueled by the launch of ChatGPT at the end of 2022 has only accelerated. Organizations, however, have yet to see much ROI on their mounting investment in the technology -- but experts say that wait may be over in the new year. Based on promises of AI's potential to dramatically optimize operations through new developments in the space, including models that are smarter, cheaper, multimodal, better at reasoning, and even autonomous, business leaders have funneled money into related expenses. Global corporate AI investment reached $252.3 billion in 2024, and US private AI investment hit $109.1 billion, according to Stanford data -- it's safe to assume those numbers will only continue to grow. Also: Why AI agents failed to take over in 2025 - it's 'a story as old as time,' says Deloitte But a look back at 2025 reveals a common thread: AI's potential to dramatically optimize operations has not yet been realized across the board. Most memorably, a now-infamous MIT study found that 95% of businesses weren't seeing an ROI from their generative AI spend, with only 5% of integrated AI pilots extracting millions in value. While the criteria for returns are narrowly defined, which partially explains the high percentage, it is still indicative of a wider trend. "So far, a small group of leaders have converted AI into outsized value -- new revenue pools, new business models, and real valuation premiums -- while most others have settled for 'respectable but modest' returns," said Dan Priest, US chief AI officer at PwC. Yet, Priest adds that he thinks the new year will finally see AI's value gap start to close, a position held by nearly every expert ZDNET spoke to. Priest mostly attributed this forthcoming expansion to the precision that CEOs and other business leaders will have to bring to their AI projects by identifying a few high-impact areas where AI can "reshape the economics of the business" and pursuing those with focus. Also: This company's AI success was built on 5 essential steps - see how they work for you China Widener, Deloitte vice chair and US TMT industry leader, echoed this sentiment, claiming that the upcoming year will shift from "heavy AI investment that remained stuck in pilots" to meaningful changes for enterprises. "In 2026, competitive advantage will come not from simply adopting AI, but from orchestrating it -- translating innovation into sustained ROI and new forms of business value," said Widener. It is notable that in both of these predictions, experts highlight that the shift doesn't lie in the evolvement of the technology itself, but rather in how business leaders approach implementing AI into their businesses. How will that get done? There are several key considerations for businesses, starting with the adoption of AI agents. For instance, Widener suggests that embracing AI's agentic capabilities will enable business leaders to meaningfully rethink how teams operate, as well as how they carry out work and generate growth. Also: The fix for messy AI agent ecosystems might finally be here - and it's open source In theory, the value of AI agents for businesses is simple: these AI assistants can perform tasks that humans can, but without human limitations (such as needing breaks), while also collaborating with each other to efficiently carry out tasks. In practice, however, that reality is somewhat more challenging to implement. 2025 was touted by many as the year of AI agents. Yet, as revealed by Deloitte's Tech Trends report this week, the technology did not take off this year despite the hype and promise. In particular, Deloitte's 2025 Emerging Technology Trends study, which surveys 500 US Tech Leaders, found that 30% of the surveyed organizations are exploring agentic options, with 38% piloting solutions and only 14% having solutions ready to deploy. The number of organizations actively using the systems in production is even lower, at 11%. Also: AI could double the US economy's growth rate over the next decade, says Anthropic Gartner has released similar data saying that over 40% of agentic AI projects will be canceled by the end of 2027, due to factors such as escalating costs, unclear business value, or inadequate risk controls. Even still, Gartner analyst Arun Chandrasekaran coined 2026 as the year of "Operationalizing AI agents." "While AI agents are becoming increasingly common as pilot projects, most enterprises are struggling with moving them into production," said Chandrasekaran. "Ensuring a robust control plane for managing agent lifecycle, instituting governance to secure, red-team, validate and observe agents and building stateful multi-agent systems are all major goal posts for the industry to improve on in 2026." Also: AI agents are already causing disasters - and this hidden threat could derail your safe rollout The firm is also bullish on the value AI agents will bring to businesses, predicting that at least 15% of day-to-day work decisions will be made autonomously through agentic AI by 2028, up from 0% in 2024. AI agents have the potential not only to optimize internal business operations but also to enhance how people execute everyday tasks. For example, one of the most buzzworthy topics related to AI agents is AI for commerce. In their simplest use case, AI agents can help users select the product they need and add items to their cart. In their ideal state, AI agents will be able to complete transactions on users' behalfs, which could come in handy when purchasing a product at a certain price point or when avoiding tedious tasks like travel booking. Also: Should you trust AI agents with your holiday shopping? Here's what experts want you to know The latter, more advanced use cases may just be possible in 2026, according to Ken Moore, chief innovation officer at Mastercard. "In 2026, two powerful forces will converge -- AI-driven autonomy and the evolution of trust -- as agentic commerce moves from early adoption to scale," said Moore. "Consumers will shift from manual operators to strategic orchestrators, delegating routine decisions to AI like replenishment or travel booking." Beyond agents, a central puzzle piece in how businesses will successfully implement AI is proper education. Forrester predicts that by 2026, 30% of large enterprises will make AI fluency training mandatory to lift AI adoption and reduce risk. This is a major departure from what we have seen thus far. Deloitte found that only 7% of AI spend goes to changing the culture and training, and learning. An October 2025 Wharton study also found that investment in training is softening, dropping eight percentage points year over year. Also: The great AI skills disconnect - and how to fix it This lack of adoption is an impediment to successful AI implementation, with Forrester data showing that 21% of AI decision-makers cite employee experience and readiness as a barrier to adoption. Kim Herrington, a Forrester senior analyst, added that an improperly trained workforce is a recipe for risk. "AI runs on data, and employees shape that data every day (often without realizing it)," she said. "Poor literacy and fluency lead to poor inputs or behaviors, which cascade into flawed decisions or poorly trained AI models that can rapidly scale access to misinformation." Herrington said that mandatory training will help remind employees that AI outputs are capable of making mistakes, as well as how to best use them, which can also build their confidence in using the tools. While a lot of AI delivery predictions for 2026 seem to rely on AI agents, it is worth hedging expectations, as the change won't happen overnight or be seamless. Also: 5 ways to prevent your AI strategy from going bust "Agents will still be imperfect, and that's okay," said Priest. "The difference in 2026 is that more companies will have real benchmarks, clearer guardrails, and a repeatable playbook. Combined with a tighter, top-down focus on where agents are deployed, that's what will turn agentic AI from experimentation into real enterprise transformation."

The big AI New Year's resolution for businesses in 2026: ROI | Fortune

After a few years of experimentation and pilots, businesses are getting serious about making AI investments pay off.Illustration by Simon Landrein After three years of experimenting and spending, and as talk of an AI bubble looms, enterprises are starting to demand results. According to Kyndryl's recent Readiness Report, drawing on insights from 3,700 business executives, 61% of CEOs say they are under increasing pressure to show returns on their AI investments compared with a year ago. This is putting company leaders to the test in terms of balancing long-term innovation with the need to prove outcomes now, all while AI development continues to move at breakneck speed. It's also creating risks of misalignment in the C-suite, with tech and business leaders looking out for their firm's innovation while financial leaders look out for the balance sheet. "The last year was a lot about experimental budgets, like, 'I'm just going to give the budget to every department [and] experiment with whatever tools they think are useful,'" said Lexi Reese, a former strategy executive at firms including Google and the current CEO of AI observability platform Lanai. "Now, it's accountable acceleration, because the price tag on this is very expensive." The AI spending spree The unprecedented amount of money being spent to develop and deploy AI has been grabbing headlines all year. Much of this surrounds infrastructure spending by frontier AI labs and eye-popping startup investments, but enterprises are heavily investing, too. Garner expects spending on AI application software to more than triple from last year to almost $270 billion in 2026. Over the past year, Reese said she's had conversations with over 300 customers about their AI tool costs and found they are spending between $590 and $1,400 per employee annually, according to internal data shared with Fortune. For many executives, this is causing flashbacks to digital transformations of the past -- in particular, the transition to cloud, which left some with a bad taste in their mouth. Michael Bradshaw, global practice leader for applications and data at Kyndryl, told Fortune he sees this consistently in his role, where he works with executives on bridging the gap between their business strategy and what they are actually trying to do with their technology. "Almost two-thirds said, 'We got to our cloud strategy by accident,' and 95% of them said, 'If we could do it over again, we would redo our cloud strategy,'" he noted, referring to data in Kyndryl's report. "That is shocking to me as a practitioner, because we're about to see the same thing happening. I think we're seeing it with AI today." For example, he pointed to one customer that spent over a billion dollars just to implement its initial ERP (enterprise resource planning) software: "As they're looking at the next wave, their frame of reference is, 'Oh, my gosh, I'm going to have to spend that same amount of money to do the next wave of transformation, on top of the challenged business environment. I can't afford that!'" Manisha Khanna, senior product manager for AI and generative AI at analytics firm SAS, told Fortune this is now the number one challenge she's hearing from customers, who are asking: How much should I invest in these technologies so that it gives me ROI? "Our customers have seen some very flashy demos from various vendors. They have high expectations. But then they start asking questions as to, 'Do you really understand how much this is going to cost in production?' There is compute cost, data infrastructure requirements, talent cost," she said. "How do you budget for all of that?" The challenges hindering ROI When Dan Rogers stepped into the CEO role at Asana just a few months ago, AI ROI quickly became top of mind. Understanding the return on AI is a top priority, he told Fortune, and he is using a formalized approach that includes both financial ROI and "human-centered" ROI metrics, such as reduced administrative burden and improved decision-making. Every functional leader owns outcomes from AI in their area and must report specific metrics, he said, adding that the company is "setting ambitious efficiency targets as part of a top-down strategy." At the same time, this poses a challenge around how to weigh long-term bets against short-term value. "Ask for financial ROI too early and you kill experimentation. Wait too long and you're in pilot purgatory," he said. Rogers noted he's cautious about forcing every AI initiative to clear a narrow, short-term hurdle, as benefits sometimes accrue gradually. Some capabilities are infrastructure layers, for example, and you have to look at what that layer enables over time. On the flip side, the rapid innovation cycle of AI can make wait-and-see especially challenging. "The pace of AI change has effectively broken traditional planning cycles. We've moved from a 12-month ABR [annual business review] rhythm to quarterly checkpoints and continuous reprioritization, because you simply can't wait a year to course-correct in a domain evolving month to month," Rogers said. Kyndryl's Bradshaw echoed this, describing moving into "very, very rapid cycles where we're having conversations with customers about delivering value in four to six months." Another factor Bradshaw points to is that AI ROI can be difficult to measure, in particular with so much of it currently revolving around personal productivity technologies. "I have agents that are helping go through my mail. How do I translate that to my personal productivity, and what business outcomes am I driving? That's why businesses have really struggled with being able to articulate ROI," he said. Together, all of this is starting to create cracks in the C-suite. According to the Kyndryl report, nearly three in four CEOs said short-term ROI pressure undermines long-term innovation, and 65% said they aren't aligned with their CFO on long-term value. "A CFO might want to look at it from a balance sheet perspective. The business leader wants to make sure the business model changes. The technology leader -- like a CTO -- wants to make sure I'm innovating, I'm applying all the latest technologies, that I have the talent and the skills in my team so I'm really able to realize value," said Khanna. "And these three [C-suite leaders] are on completely different pages right now with regard to the expectation." A new year in AI ROI Asana's Rogers believes the larger industry conversation around spending has definitely intensified the focus on ROI. "And honestly, that's overdue," he said. "When reports say that 95% of AI pilots generate zero return, boards and executives are understandably asking tougher questions." He added he thinks the push for clear ROI is a positive step, and that it's time to shift the conversation "from novelty to outcomes." The growing desire to prove ROI could cause a boom for firms like Reese's Lanai, which promise to help customers get a clearer picture of how their teams are actually using AI, what's driving impact, and what isn't. Lanai in particular analyzes all of the prompts users are putting into their AI tools to get granular views of their work. Reese said the key to driving ROI is to determine what your "highest-value workflows" are and adjust from there. "If you can see the work and the workflows, you can start to standardize operations and say, 'Sales is finding a lot of value in these workflows, so let's double down on that. These workflows are getting a lot of adoption, but they're super risky. Let's nudge people in the right direction,'" she said. There will certainly be pressure to prove ROI in 2026, but Khanna and Bradshaw believe most firms aren't positioned to get there. "We'll see it within what we characterize as the 'pacesetters.' So where you have that alignment within the C-suite, where you have that outreach with your employee base, and you get that alignment of the technology strategy," Bradshaw said. "You will see some [companies that achieve ROI in 2026]. It will not be widespread. That'd be my prediction, because most firms are not positioned to be able to do it."

Sanford AI Experts Say the Hype Ends in 2026, But ROI Will Get Real

According to Deloitte's 2026 Tech Trends report, the rate at which AI is evolving is motivating the urgency to shift from "endless pilots to real business value." While the telephone reached 50 million users after 50 years, and the internet after seven years, AI tool ChatGPT reached twice that in two months and now has more than 800 million weekly users. Tangible Results AI next year may be characterized by rigor and ROI, according to Julian Nyarko, a law professor and Stanford HAI associate director. He spoke specifically about AI for legal services. "Firms and courts might stop asking 'Can it write?' and instead start asking 'How well, on what, and at what risk?'" Nyarko said. "I expect more standardized, domain-specific evaluations to become table stakes by tying model performance to tangible legal outcomes such as accuracy, citation integrity, privilege exposure, and turnaround time."