Forrester releases a report on the top 10 emerging technologies of 2026, claiming that artificial intelligence is moving from digital systems to physical environments.
This report groups technologies by the time they are expected to impact your business and divides them into short-term, medium-term, and long-term time horizons. It identifies agent commerce, AI security and trust, and frontier AI models as the areas most likely to benefit many organizations within the next two years.
These short-term technologies are moving beyond pilot projects and into everyday use. Forrester expects that agent commerce will first show results in company-managed channels such as apps and websites, where companies can use AI-driven personalization and automated interactions to reduce friction in the sales journey.
AI security and trust tools also feature prominently in the short-term category. As generative and agentic AI becomes more pervasive across organizations, companies will need tighter governance, security and trust controls, with early gains expected in sectors such as financial services, healthcare and the public sector, according to the report.
Frontier AI models are another technology that is on the verge of widespread adoption in business. Although these fall into the short-term category, they are presented as part of a broader infrastructure that is expected to support future advancements in software, automation, and customer-facing services.
physical shift
The central theme of the research is the transition of AI to the physical world. Forrester points to robotics, autonomous transportation, and ambient digital experiences as evidence that AI is no longer limited to screen-based workflows.
Consumers are likely to encounter this change first-hand through what the report calls layer-zero experiences, physical AI and robotics, and self-driving transportation. It will mark a shift from back-office and online AI applications to systems embedded in everyday environments.
Medium-term trends
Within medium-term technology, Forrester focuses on agent software development. Software teams are beginning to use networks of AI agents throughout the development process to generate and improve code and other software artifacts, but stronger coordination and guardrails are still needed to achieve maximum results.
Humanoid robots will also appear in the mid-term group. While these can help address industry-wide workforce shortages, integration, scalability, security, data, and workforce issues remain barriers to widespread adoption and near-term value.
long term outlook
Quantum computing is the only technology in the report that reliably falls into the long-term category. Even with continued advances in hardware, algorithms, and hybrid approaches, it will likely take more than five years to see a meaningful return on investment.
Longer schedules don’t mean companies can ignore this area. The study argues that organizations need to start preparing now, especially given the potential impact that quantum advances will have on encryption and secure communications.
If the technology matures as expected, industries such as financial services, pharmaceuticals, and manufacturing will be among the first to benefit. Still, the report treats widespread commercial use as a more distant prospect than the top-ranked AI-related technologies.
Sharyn Lieber, chief research officer at Forrester, said the report is intended to help leaders consider timing, value and risk when deciding where to allocate their technology budgets.
“With new technologies constantly emerging, business and technology leaders must plan their technology investments based on value, risk, and potential payment schedule,” said Sharyn Leaver, Chief Research Officer at Forrester. “While AI continues to top the list of emerging technologies in 2026, the capabilities and impact of AI technologies vary widely. Our research aims to help business and technology leaders diversify their investments by identifying short-term technologies that can deliver quick returns and long-term bets that require more effort, more fundamental investment, and more risk management capabilities,” Lieber added.
planned shift
The findings reflect a broader shift in technology planning, as companies face pressure to distinguish between tools that can currently support operations and those that are largely experimental. Rather than treating AI as a single trend, this report breaks it down into distinct categories with different adoption curves and operational risks.
The framework also highlights practical points for managers. The next stage of AI adoption will likely depend less on novelty and more on where systems are securely integrated, well managed, and tied to measurable outcomes. Forrester’s analysis shows that the technologies closest to realizing benefits are not necessarily the most ambitious, but those that can move from experimentation to regular use.
