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ZDNET Key Takeaways
- AI will enter a new phase in 2026, analysts believe.
- Businesses will take better advantage of technology and see results.
- AI agents and business opportunities will be key.
AI hype fueled by ChatGPT launch in late 2022 only accelerated. However, organizations have I haven’t seen much return on investment yet. on their growing investments in technology – but experts say that wait could be over in the new year.
Building on the promise of AI’s potential to dramatically optimize operations through new developments in the field, including smarter, cheaper, multi-modal, more reasoning, and even autonomous models, business leaders have been pouring money into related expenses. Global corporate investment in AI reached $252.3 billion in 2024, and U.S. private investment in AI reached $109.1 billion, according to Stanford data — it is reasonable to assume that these numbers will only increase.
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But looking back to 2025 reveals a common thread: AI’s potential to significantly optimize operations has not yet been fully exploited. The most memorable, a now infamous MIT study found that 95% of companies were not seeing a return on investment from their generative AI spend, with only 5% of embedded AI pilots generating millions in value. Although the performance criteria are narrowly defined, which partly explains this high percentage, it is nonetheless indicative of a broader trend.
“So far, a small group of executives have converted AI into outsized value – new revenue streams, new business models and real valuation premiums – while most others have settled for ‘respectable but modest’ returns,” said Dan Priest, US director of AI at PwC.
Still, Priest adds that he thinks the new year will finally see the AI value gap begin to close, a position supported by nearly every expert ZDNET surveyed.
A change in return on investment
Priest attributed this upcoming expansion primarily to the precision that CEOs and other business leaders will need to bring to their AI projects by identifying a few high-impact areas where AI can “reshape the economics of business” and pursuing those targeted there.
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China Widener, vice chairman of Deloitte and leader of the US TMT industry, echoed this sentiment, saying that the coming year will move from “heavy AI investments stuck in pilot projects” to meaningful changes for businesses.
“In 2026, competitive advantage will come not simply from adopting AI, but from orchestrating it, translating innovation into sustainable ROI and new forms of business value,” Widener said.
Application over time
It is worth noting that in both of these predictions, experts emphasize that the change lies not in the evolution of the technology itself, but rather in the way business leaders approach the implementation of AI in their companies. How will this be done? There are several key considerations for businesses, starting with the adoption of AI Agents.
For example, Widener suggests that adopting AI’s agentic capabilities will allow business leaders to significantly rethink how teams operate, as well as how they get work done and drive growth.
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In theory, the value of AI agents to businesses is simple: These AI assistants can perform tasks that humans can, but without human limitations (like the need for breaks), while collaborating with each other to complete tasks efficiently. In practice, however, this reality is a little more difficult to implement.
AI Agents
2025 has been touted by many as the year of the AI agent. However, as revealed Deloitte Technology Trends report this week, the technology hasn’t taken off this year despite the hype and promises.
In particular, Deloitte’s 2025 Emerging Technology Trends study, which surveyed 500 U.S. technology leaders, found that 30% of organizations surveyed are exploring agentic options, with 38% testing solutions and only 14% having solutions ready for deployment. The number of organizations actively using the systems in production is even lower, at 11%.
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Gartner has published similar data claiming that more than 40% of agentic AI projects will be canceled by the end of 2027, due to factors such as cost escalation, unclear business value or inadequate risk controls. Yet Gartner analyst Arun Chandrasekaran has designated 2026 as the year of “operationalizing AI agents.”
“While AI agents are becoming more common in pilot projects, most companies struggle to put them into production,” Chandrasekaran said. “Ensuring a robust control plan to manage the agent lifecycle, establishing governance to secure, group, validate and observe agents and creating dynamic multi-agent systems are all major objectives that the industry must improve in 2026.”
The company is also optimistic about the value AI agents will bring to businesses, predict that at least 15% of daily business decisions will be made autonomously using agentic AI by 2028, compared to 0% in 2024.
Trade agent
AI agents have the potential to not only optimize internal business operations, but also improve the way people carry out their daily tasks. For example, one of the most interesting 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 carry out transactions on behalf of users, which could prove useful when purchasing a product at a certain price or avoiding tedious tasks like booking a trip.
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These latter, more advanced use cases may well 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 agent commerce moves from early adoption to scale,” Moore said. “Consumers will shift from manual operators to strategic orchestrators, delegating routine decisions to AI like restocking or booking travel.”
Education and development
Beyond agents, a central piece of the puzzle in determining how companies will successfully implement AI is adequate training. Forrester predicts that by 2026, 30% of large companies will mandate AI training to drive AI adoption and reduce risks.
This is a major change from what we’ve seen so far. Deloitte found that only 7% of AI spending is spent on culture change, training and learning. A Wharton study from October 2025 also found that investment in training is slowing, falling eight percentage points year over year.
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This lack of adoption poses a barrier 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, senior analyst at Forrester, added that a poorly trained workforce is a source of risk.
“AI runs on data, and employees shape that data every day (often without realizing it),” she said. “A lack of literacy and fluency leads to poor input or behavior, which results in faulty decisions or poorly trained AI models that can quickly expand access to misinformation.”
Herrington said the mandatory training will help remind employees that AI results are capable of making mistakes, as well as how to best use them, which can also boost their confidence in using the tools.
Chronology
Even though many AI deployment predictions for 2026 appear to rely on AI agents, it’s worth hedging expectations because change won’t happen overnight or happen seamlessly.
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“Agents will always be imperfect, and that’s OK,” Priest said. “The difference in 2026 is that more companies will have real benchmarks, clearer guardrails and a repeatable playbook. Combined with a narrower, top-down focus on where agents are deployed, this is what will take agentic AI from experimentation to true business transformation.