Technology advances in the lab: MLO’s 2025 LIS and Lab Data Solutions Guide

Technological advancements

The current biggest technological advancements impacting LIS and other lab data tools in 2025 are artificial intelligence (AI), cloud-based products, and interoperability, according to the experts. Rob Brown, Head of the Scientific Office, Sapio Sciences emphasized, “The most transformative advancements impacting lab information tools are focused on intelligence, usability, and configurability. Lab information tools are moving beyond passive record-keeping to integrate AI that acts as a co-scientist, helping with experiment design, result analysis, and the recommendation of next steps.”

“Voice is also emerging as a new interface in both research and diagnostics labs, allowing scientists to interact with their LIMS using natural language. These advancements are supported by unified platforms that connect various tools in a single environment, reducing handoff errors and enabling full traceability,” he said.

Suren Avunjian, CEO, LigoLab observed the quick adaptation and flexibility of laboratories as new technologies are rolled out. “Automation and AI are no longer experimental; they’re embedded into modern LIS platforms. Labs are utilizing agentic tools to automatically flag inconsistencies, interpret results, apply AI to digital slides, scan paper requisitions and import them as an order, voice-to-text and command control of the LIS, and generate customized reports. This reduces manual review and allows staff to focus on higher-value clinical work,” he said.

Kim Futrell Senior Strategic Marketing Manager, Clinisys said, “In 2025, cloud-based LIS platforms have become foundational to modern lab operations, offering remote access, scalability, and built-in disaster recovery. With rising concerns around data privacy, vendors are enhancing cybersecurity and compliance features to meet regulatory demands. A primary emphasis is placed on interoperability, with LIS platforms increasingly engineered to seamlessly connect with EHRs, digital pathology, genomics, and AI diagnostics.

She added, “Structured data frameworks facilitate seamless integration, allowing labs to function within broader healthcare ecosystems. Utilizing embedded analytics tools powered by pay-per-use cloud computing, labs can access real-time dashboards and insights into test utilization, staffing, and patient outcomes—optimizing performance and demonstrating value. Simultaneously, digital pathology and AI are revolutionizing remote collaboration, accelerating image analysis, and creating adaptive workflows that cater to evolving diagnostic needs. Moreover, AI presents innovative opportunities for enhancing service and support delivery models.”

Avunjian continued, “With open APIs and interoperability standards, LIS systems are now able to connect seamlessly with instruments, EHRs, billing platforms, and digital pathology solutions. This creates a more unified ecosystem and reduces the silos that have traditionally hindered lab efficiency and growth.” He noted that with all this, labs are also focusing more on cybersecurity, complying with regulations, and hardening their systems against ransomware and hacker attacks. “Modern systems incorporate embedded encryption, robust audit trails, and predictive analytics, enabling labs to reduce both risk and waste across a range of applications, from instrument maintenance to reagent management,” he said.

Furthermore, “All of these advancements are converging into comprehensive informatics platforms, systems of action that cover the entire lifecycle of a case, from accessioning through revenue capture,” according to Avunjian.

When asked what challenges labs face when adopting or upgrading LIS and other data platforms, Gilbert Halkim, CEO, SCC Soft Computer mentioned mindset as the main obstacle. “Too often, labs try to replicate their legacy workflows in a new LIS. The best results come when labs adopt vendor best practices, streamline implementations, and leverage modern functionality without over-customization.”

Labs often face significant challenges from legacy systems that create rigid workflows, siloed data, and a frustrating user experience, Brown said. “These issues directly impact critical metrics like turnaround time, sample traceability, and regulatory compliance. A key problem often occurs in the pre-analytical phase, where manual data entry and poor sample handoffs introduce errors.”

Eric Dingfelder, President and CEO, Data Innovations pointed out another barrier. “One of the most significant challenges laboratories encounter when upgrading their Laboratory Information Systems (LIS) or other data platforms is achieving seamless interoperability across diverse systems, instruments, and automation technologies. Integrating these components—often from different vendors—can be complex, time-consuming, and costly,” he said.

Futrell said, “Staffing shortages often limit the time and resources available for implementation and training, delaying adoption, curtailing new feature adoption rates and reducing onboarding effectiveness. Labs are required to maintain fast turnaround times and avoid any disruptions that could impact result delivery and provider satisfaction. Additionally, they must ensure compliance with HIPAA, CLIA, and FDA standards, including secure data transmission and audit trails. It is essential that LIS platforms connect seamlessly with lab instruments and external systems to prevent workflow disruptions.”

Labs should look beyond current features and evaluate a vendor’s roadmap for AI, interoperability, and patient-facing tools, said Ed Price, CEO, Computer Service & Support, Inc. “Just as important, they should ensure they own and can access their data. Too many systems restrict exports or lock customers into closed databases. Avalon gives clients direct read-access, empowering them to build their own analytics, integrate external tools, and retain full control. The LIS platforms that balance compliance, innovation, and empowerment will deliver the greatest long-term value.”

Jomah Williams, Product Manager for IT, Siemens Healthineers emphasized the importance of choosing a solution that will evolve with the laboratory. “Within any cost associated purchase, you want value and a vehicle that can handle the growth of your lab needs as well as offering innovate for the functions.”

Halkim offered clear advice, “Don’t compromise by cutting corners. Implementing systems without investing in a robust LIS can create long-term limitations. Instead, partner with a state-of-the-art LIS that supports advanced interoperability, scalability, and modern lab workflows. This ensures labs remain agile, secure, and future-ready.”

A common observation is that a neutral platform allows for adaptation to changes in the LIS or device manufacturer without being limited by operational tools that may not align with evolving laboratory needs, Dingfelder added. “It is advisable to consider flexibility and adaptability in both purchasing and change management decisions when selecting a partner.”

The evolving LIS

LIS platforms are required to evolve to support interoperability with EHRs, digital pathology, genomics tools, or AI diagnostics.

“Interoperability is now essential,” Price stressed. “Avalon LIS supports HL7, FHIR, and modern APIs to connect directly with major EHRs. We’re expanding these capabilities to integrate with digital pathology systems, genomics data, and external AI diagnostics - enabling true bi-directional data exchange rather than isolated workflows.”

Williams said, “Auto-verification workflows drive faster results and integration with many new devices like middleware providers and real time data streaming. Standardization of result protocols leads to consistent quality.”

The stress on laboratories to use more technologies and the need for one seamless workflow for EHRs, digital pathology tools, genomics data, RCM, and AI diagnostics was spotlighted by Avunjian. “Advanced LIS platforms are evolving to make this possible by serving as the central hub where all of these technologies come together.

Digital pathology is a prime example. Moving from glass slides to high-resolution digital images allows pathologists to review cases remotely, collaborate with peers, and use AI to highlight patterns that the human eye may miss or fill out the report with the AI diagnosis in preparation for the pathologist to review and sign out. But scanners and viewers on their own do not solve the interoperability challenge. That requires a modern LIS.”

He continued, “Diagnostic accuracy improves when AI and human input are combined in a unified report. Turnaround times drop because case data, images, and results are all in one place. Collaboration becomes easier, whether within a hospital network or across the globe. Most importantly, patient care improves because clinicians receive complete, timely, and clear results. By building interoperability into the core of an advanced LIS platform, labs are provided with the foundation to adapt to the digital future.”