Radiology 2026: Five Trends Defining the Next Era of Imaging

It’s hard to believe that RSNA is over and 2026 is fast approaching. What will 2026 hold for the future of imaging? Radiology enters 2026 at a critical inflection point; imaging volumes continue to rise, staffing remains tight, and many health systems still rely on fragmented infrastructure built for a different era of medicine. Incremental upgrades aren’t cutting it anymore – will this be the year a fundamental rethinking of how radiology workflows, reporting, and AI all come together?

These are the five most significant shifts that will shape radiology in 2026, and why platforms like Sirona’s RadOS™ will become the foundation of modern imaging operations.

Personalization 

In 2026, radiologists will expect personalized displays, relevant priors, study-aware reporting templates, and intelligent hanging protocols to be automatically generated — not as add-ons or separate point tools. Sirona’s RadOS™ is leading this shift with automated surfacing of prior imaging, dynamic reading environments that adapt to subspecialty and user preferences, and Sirona’s patented Pixel-to-Reporting® technology that creates a direct bridge between images and structured reports.

A Reporting Revolution 

For decades, radiology reporting has lived separately from image interpretation. Radiologists interpret pixels in one environment and then rebuild that reasoning manually in another system. Despite advancements in voice recognition and AI, reporting has remained a parallel process. A shift is underway in which reporting occurs within the interpretation rather than after it. Measurements, annotations, and observations captured in the viewer generate structured report content in real time. Sirona’s patented Pixel-to-Reporting® technology automatically populates structured report fields with images without manual surfacing and enables quality checks to run in the background. This personalization accelerates, rather than slows, the reading process. This is really a complete rebuild of legacy workflows. In a recent episode of The Imaging Wire Show, Kate Kovalenko, Chief Product Officer at Sirona Medical, said, “You can imagine a world where the report just disappears,” Kate said. “You’re looking at the images, asking questions, and the information moves into the report as a byproduct of your interaction with the pixels.”

AI Moves Inside the Workflow 

AI tools that live outside the workflow simply don’t get used. In 2026, adoption will accelerate only if platforms become smarter about where and how AI is used. AI that isn’t workflow-native will fade. During a recent webinar with Sirona Medical, Dr. Jon Masur said,’ Everyone talks about speed,  but the real gains come from eliminating fragmentation. When everything speaks the same language, you don’t need to ‘go faster.’ You just stop slowing down.”

According to Precedence Research, radiology AI is projected to grow from about $794M in 2025 to nearly $1B in 2026 and eventually surpass $7.1B by 2035. The majority of that growth is in cloud-based SaaS software rather than hardware-heavy tools — reinforcing that the future of imaging will favor platforms that can scale quickly, support distributed reading models, and enable radiologists to work flexibly from anywhere. AI that’s woven into a platform like RadOS™ is invisible, contextual, and instantly available. For example, agentic AI triggers downstream workflow actions; integrated third-party apps are routed through unified data models, and radiology-specific LLMs (such as SironaLex™) perform real-time consistency checks.

Cloud Native is a Requirement 

In 2026, the market will begin to draw a clear line between cloud-hosted (legacy systems lifted into the cloud) and cloud-native (architected for the cloud from day one). A true cloud-native PACS is built for distributed, elastic operation and connects all patient data. It updates continuously with downtime, scales automatically, and works anywhere via a secure browser. Cloud-native systems can also be updated weekly with no downtime and minimal user disruption. The future of radiology is distributed; practices are expanding across regions and relying on flexible staffing models. A PACS that requires dedicated workstations, local installs, or VPN connectivity limits how quickly you can scale and how efficiently your team can support distributed workflows.

Modern cloud-native systems enable instant, secure remote reading from any device, with performance on par with or better than on-premises systems.

Radiologists Regain Flexibility and Practice Profitably

The radiology workforce shortage isn’t going away. But in 2026, radiologists will expect (and choose employers based on) platforms that give them the freedom to read from anywhere, seamless access to priors and patient context, and technology that adapts to their lifestyle.

A perfect example: In 2021, Dr. Roller was a solo radiologist in the Midwest, hoping to serve rural and underserved communities. The barriers he faced were steep: costly workstations, weeks of installation, and a significant IT lift just to get started. Building a practice under that model felt insurmountable.  When he moved to Sirona in 2022, the path changed. With only a browser, he was able to get up and go within weeks. Instead of six-figure startup overhead, Dr. Roller launched with minimal cost and maximum agility. He said during a recent webinar,  “The fixed costs were so low that my practice could actually breathe.” He began reviewing more than 50 studies per month for small sites, such as a regional prison and a rural outpatient clinic. Over the following year, volume grew steadily, and through Sirona’s ecosystem, he partnered with another teleradiology group to share overnight reads. Today, he reads for a significant health system and has a thriving practice. 

Incremental improvements will not define radiology’s next era; instead, they will enable a fundamental rethinking of how imaging, reporting, and AI come together. The trends shaping 2026 all point to the same reality: radiologists need unified, intelligent, cloud-native platforms that dissolve friction rather than add to it.