Fabio Caversan is Vice President of Digital Business and Innovation at Stefanini, driving new product offerings and digital transformation.
Every year, pundits in the technology sector share their predictions on what to watch in the coming year. Some of those predictions offer refinements on developments from prior years, while others forecast cutting-edge trends. After multiple cycles of hype with promised revolutions around blockchain, the metaverse and NFTs, many of these tech forecasts are understandably approached with a little bit of skepticism.
While this can make planning for the future more difficult, the continued momentum of new technology requires clarity and planning. That’s why grounding your plans for 2026 should focus on proven use cases of these technologies and on what applications are right for your organization now and which ones are not ready for prime time.
As companies consider deploying emerging technologies in 2026, the challenge isn’t whether or not they should adopt them. Instead, the challenge becomes how to make the most informed bets on what will deliver organizations the most value. Let’s review a few standout applications of emerging technology and see how companies should leverage them in the coming year.
AI is reshaping how software is built.
Application development is already shaping up to be a clear dividing line, as AI-native development platforms, where AI is embedded directly into the software, have moved from a concept to reality. These platforms are changing how software is designed, built and tested.
As this model matures, the gap between AI-assisted workflows and manual coding will become clear. AI tools allow developers to deliver faster and better results, increasing quality, decreasing time-to-market and improving overall user satisfaction.
Demand for software has only increased, and without AI embedded in the development process, organizations will struggle to meet rising demand.
Software creation itself is also shifting. Rather than relying on traditional development cycles, more applications will be generated in response to user intent. While some worry this will diminish the role of developers, that shift will expand the industry. Experts are needed to build and maintain complex systems that enable a large number of users without deep technical training to create.
Agentic AI moves into the enterprise, but humans remain accountable.
The adoption of agentic AI has grown significantly throughout the past year as coordinated systems of AI agents begin to show value across development, marketing, operations and analytics. Rather than relying on a single general-purpose AI, agentic AI deploys specific “agents” for each task, driving the need for solutions that offer agent orchestration.
As I’ve said before, with this technology comes the need for restraint and new governance frameworks that allow companies to harness the enormous potential of agentic AI while limiting potential risks. Human oversight is absolutely critical as this technology is in the early stages of development.
A more stable model is built on a hybrid approach grounded in collaboration rather than replacement, where AI agents handle orchestration, analysis and execution, while humans review and approve decisions before action, whether the task involves issuing purchase orders or neutralizing a cybersecurity threat.
AI-powered browsers are another emerging development that is still in the early stages of development. These browsers carry unresolved privacy and security concerns, from prompt-injection vulnerabilities to the risk of exposing sensitive data, which makes them risky for workplace use. Eventually, they might replace some legacy automation tools, but organizations should currently limit these tools to low-risk experimentation until there are stronger safeguards in place.
Cybersecurity is nonnegotiable.
Although development and productivity tools are moving quickly, real-world applications are being developed at varying paces across industries. Cybersecurity is one vertical where AI has shown some of the strongest early potential, and organizations that have not already moved to adopt AI tools into their program are falling behind.
AI-driven threats are already a reality, as organizations wrestle with ransomware attacks that damage operations and data breaches that erode customer trust. These attacks are coming at a faster pace than ever before, and the consequences of a slow response can be devastating. Organizations that leverage AI for detection, threat response and resilience are able to better respond to emerging threats and protect their organizations from bad actors.
Geopatriation and cloud repatriation are also emerging as responses to a more complex global operating environment, rather than a rejection of cloud altogether. As regulatory pressures, data sovereignty requirements and geopolitical uncertainty increase, organizations continue to reassess where their data and workloads should physically reside.
The future isn’t an all-in public cloud model or a wholesale return to on-premise infrastructure. A hybrid approach where companies are more selective on which workloads need greater control, while also leveraging cloud platforms for scalability, is key.
Physical AI moves forward, but with boundaries.
Physical AI and robotics will continue to progress in 2026, but these technologies still have clear boundaries. Task-specific robotics is advancing rapidly as improvements in vision, simulation and AI-driven training reduce cost and complexity. In manufacturing, logistics and operations, these purpose-built systems are becoming more viable than ever.
However, humanoid robots that are capable of adapting to multiple environments or performing a suite of unrelated tasks well are still a distant dream. Although the technology will continue to advance, I don’t expect to see widespread deployment in the near term. Instead of focusing on all-purpose solutions, it often makes more sense to focus on narrowly defined applications in this space that can provide measurable outcomes.
These trends are not driven by one single breakthrough, but by rapid advances in practical use cases for emerging technologies. Every major technological transformation in history, from computing and the internet to electricity, comes from a shift in expanding what was possible without erasing what came before. AI follows that same pattern.
I expect that in 2026, AI will enable more people across more roles to create, adapt and evolve digital systems. Some organizations will miss the mark, but ignoring AI isn’t an option. The companies that will succeed in the years ahead will be the ones that understand emerging technologies and can recognize which tools are ready for adoption and which tools should be evaluated for future adoption once technical or privacy concerns are addressed.
This article was originally posted on forbes.com
