Forrester maps AI shift from digital into physical use

Forrester has published its Top 10 Emerging Technologies In 2026 report, which argues that artificial intelligence is moving from digital systems into physical settings.

The report groups technologies by when they are expected to affect business, dividing them into short-, medium- and long-term horizons. It identifies agentic commerce, AI security and trust, and frontier AI models as the areas most likely to deliver returns within the next two years for many organisations.

These short-term technologies are moving beyond pilot projects and into day-to-day use. Forrester expects agentic commerce to show results first in company-controlled channels such as apps and websites, where businesses can use AI-driven personalisation and automated interactions to reduce friction in sales journeys.

AI security and trust tools also feature prominently in the short-term category. As generative and agentic AI spread through organisations, the report says, companies will need tighter governance, security and trust controls, with early effects expected in sectors including financial services, healthcare and the public sector.

Frontier AI models are also among the technologies nearing wider business adoption. While placed in the near-term category, they are presented as part of the broader infrastructure expected to support later advances in software, automation and customer-facing services.

Physical shift

A central theme in the research is AI's movement into 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 shift directly through what the report calls layer zero experiences, physical AI and robotics, and autonomous transportation. That would mark a move from back-office or online applications of AI to systems embedded in everyday environments.

Mid-term trends

Among the medium-term technologies, Forrester highlights agentic software development. Software teams are beginning to use networks of AI agents across the development process to generate and refine code and other software artefacts, though stronger coordination and guardrails are still needed before the biggest gains are realised.

Humanoid robots also appear in the medium-term group. They could help address labour shortages across industries, but integration, scaling, safety, data and workforce issues remain barriers to broader deployment and near-term value.

Long-term outlook

Quantum computing is the only technology in the report placed firmly in the long-term category. Meaningful return on investment is likely to be five or more years away, even as progress in hardware, algorithms and hybrid approaches continues.

That longer timeline does not mean companies can ignore the field. The research argues that organisations should begin preparing now, particularly because of the potential effect of quantum advances on cryptography and secure communications.

Industries such as financial services, pharmaceuticals and manufacturing are among those most likely to benefit first if the technology matures as expected. Even so, the report treats broad commercial use as a more distant prospect than the AI-related technologies higher in its rankings.

Sharyn Leaver, Chief Research Officer, Forrester, said the report is intended to help leaders weigh timing, value and risk when deciding where to allocate technology budgets.

"With new technologies constantly emerging, business and technology leaders need to plan their tech investments based on value, risk, and potential payout timelines," said Sharyn Leaver, Chief Research Officer, Forrester. "While AI continues to dominate the top emerging technologies list for 2026, AI technologies vary widely in capability and impact. Our research is designed to help business and technology leaders spread their investments out by identifying shorter-term technologies that can deliver quick returns and longer-term bets that require more effort, more foundational investment, and the capacity to manage more risk," added Leaver.

Planning shift

The findings reflect a broader shift in technology planning, as companies face pressure to distinguish between tools that can support operations now and those that remain largely experimental. Rather than treating AI as a single trend, the report breaks it into separate categories with different adoption curves and operational risks.

That framing also highlights a practical point for executives: the next phase of AI adoption may depend less on novelty and more on where systems can be integrated safely, governed properly and tied to measurable outcomes. In Forrester's analysis, the technologies closest to delivering returns are not necessarily the most ambitious, but those that can move from experimentation into regular use.