AI-Native Data Core: The Healthcare Shift You Can't Ignore
Healthcare is moving from trial-and-error to data-precise diagnostics and autonomous workflows. Reported estimates peg AI medical imaging at $2.57 trillion in 2026, with AI drug discovery at $1.81 billion on the back of federated learning, real-time sensing, and compressed development cycles. Big data spending is projected at $132.32 billion, while digital pathology hit $2.01 billion as biomarker prediction becomes a frontline tool in care decisions.
This isn't a software add-on. It's a diagnostic-edge stack where MRI-grade software, high-frequency sensing, and global model training are becoming the control layer for clinical operations and enterprise ROI.
What this means for healthcare leaders
- Diagnostics become a throughput engine: earlier reads, fewer rescans, and clearer triage.
- Procurement tilts to subscription and data contracts vs. pure capex buys.
- Evidence shifts from "clinical promise" to hard ROI tied to workflow and staffing relief.
- Federated learning matters: shared model gains without sharing proprietary data.
- Digital pathology scales decision support when tissue is scarce or turnaround is tight.
- Equity gets real with hub-and-spoke models that bring specialty reads to remote sites.
Ventripoint Diagnostics: 3D hearts from standard ultrasound
Ventripoint is commercializing software that converts routine 2D ultrasound into detailed 3D cardiac models with MRI-level accuracy at lower cost and complexity. The company is moving to a Device-as-a-Service subscription to shorten sales cycles and build recurring revenue while reducing upfront capital barriers for hospitals.
To reduce friction at the CFO level, Ventripoint brought in Summit Sciences to build ROI models that quantify savings from process improvements, better diagnostic accuracy, and smarter resource allocation. "We are excited to partner with Dana and Summit Sciences to elevate our financial modeling capabilities," said Hugh MacNaught, President and CEO. The company expanded its private placement to $1 million to fund commercialization, manufacturing scale-up, regulatory submissions, and operations.
Access is part of the plan. A partnership with the Nisga'a Valley Health Authority uses a hub-and-spoke model: local teams capture scans and send them digitally to a central hub for fast interpretation. Ventripoint also appointed David Swetlow as CFO, adding senior medtech finance experience to execution.
Recursion Pharmaceuticals: AI signal translating to clinic
Recursion reported Phase 1b/2 TUPELO data for REC-4881 in familial adenomatous polyposis (FAP): a 43% median reduction in polyp burden at 12 weeks, with 82% of patients maintaining reductions at week 25 (53% median decrease from baseline), 12 weeks post-treatment. "These Phase 2 results mark a meaningful validation of the Recursion OS," said CEO Chris Gibson, Ph.D.
The platform linked MEK1/2 inhibition to APC loss-of-function biology and identified REC-4881 as the first MEK1/2 inhibitor studied clinically for FAP. The company plans to meet the FDA in the first half of 2026 on a potential registration path and expand enrollment to adults 18+. The therapy remains investigational.
Tempus AI: Biomarkers from a single H&E slide
Following its acquisition of Paige, Tempus launched Paige Predict, an AI suite that analyzes H&E whole slide images to predict the likelihood of 123 biomarkers and oncogenic pathways across 16 cancers, including NSCLC, prostate, breast, pancreatic, and colorectal. Built on de-identified multimodal data from 200,000+ patients, results flow directly into clinical reports.
"Tissue can be scarce, but insights don't have to be," said Ezra Cohen, MD, Chief Medical Officer, Oncology. The aim: guide testing decisions when sequencing isn't feasible and help prioritize downstream molecular workups.
Schrödinger + Eli Lilly: Federated AI for drug design
Lilly's TuneLab will be available through Schrödinger's LiveDesign platform, giving discovery teams a unified interface for AI models, physics-based calculations, and experimental data. The approach uses privacy-first federated learning so participating companies can benefit from shared model improvements without exposing proprietary datasets.
"We are pleased that LiveDesign will be a priority platform partner for TuneLab workflows," said Schrödinger's CTO and COO, software, Pat Lorton. This is a practical route to scale AI across partner networks while keeping governance intact.
Implementation checklist for 2026 planning
- Pick 2-3 workflows to prove value in 90 days: echo-to-3D cardiology, digital pathology triage, or perioperative imaging support.
- Model TCO with subscription pricing: include IT, training, integration, and expected throughput gains.
- Interoperability: insist on DICOM, HL7/FHIR, and clear PACS/LIS/EHR integrations with documented APIs.
- Validation: run shadow reads, measure sensitivity/specificity, and set thresholds for concordance before going live.
- Workforce: define who reads, who escalates, and how alerts route; pair with brief, role-based training.
- Governance: document drift monitoring, audit trails, human-in-the-loop policies, and incident response.
- Equity: deploy hub-and-spoke reading to serve remote sites; track turnaround times and access metrics.
- Procurement guardrails: require ROI models, uptime SLAs, data retention terms, and clear de-identification policies.
Standards and compliance resources
Stay aligned with current guidance and interoperability practices:
Team upskilling
If you're standing up AI-enabled workflows this year, short, role-based training goes a long way. For curated options by job function, see AI courses by job.
Bottom line
Diagnostic software is becoming the operating system for care delivery. The winners in 2026 will pick specific workflows, prove ROI fast, and scale with clear governance, strong integrations, and a plan to serve both high-volume centers and underserved communities.
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