Oncology Imaging AI Market to Hit $7.74B by 2032 - 32.7% CAGR Growth

Oncology Imaging AI Market Set to Explode: $7.74B by 2032

The oncology imaging AI sector is positioned for explosive growth, with the global market expanding from $604.7 million in 2023 to $7.74 billion by 2032—representing a remarkable 32.7% compound annual growth rate. This makes oncology one of the fastest-growing segments in medical imaging AI.

A comprehensive new strategy report from ResearchAndMarkets.com reveals how cancer imaging AI is transforming from experimental technology to essential healthcare infrastructure across health systems, medical device manufacturers, and pharmaceutical companies.

Key Market Transformation Trends

• From Detection to Measurement-Centric Workflows: The market is shifting beyond simple detection apps toward measurement-focused solutions including segmentation, volumetrics, RECIST/PERCIST tools, radiomics, and structured reporting. Tumor boards and payers now demand reproducible metrics rather than just "AI flags."
• Screening Programs Drive Adoption: National breast DBT and lung CT screening initiatives across the US, Europe, China, and Japan are embedding AI into standard operating procedures for triage, second reads, and quality assurance.
• Platform Integration Reduces Friction: PACS-integrated AI marketplaces and cloud orchestrators enable multi-vendor oncology suites under single contracts, while evidence validation and monitoring capabilities become standard RFP requirements.

Six-Cluster Competitive Landscape

The report maps the competitive landscape into six distinct clusters: AI software vendors, imaging OEMs, radiation therapy vendors, AI platforms, teleradiology providers, and imaging pharma/CRO companies. Each cluster operates with unique economics and go-to-market strategies, creating diverse pathways for AI adoption.

Regional Growth Dynamics: APAC's growth rate now exceeds Europe's, driven by state-backed screening programs and domestic platforms. However, adoption remains uneven in Latin America and Middle East/Africa, where cloud-first and pay-per-use models are emerging to bridge access gaps.

The research positions oncology as the reference use case for medical imaging AI, where enterprise buyers are establishing budgets, governance rules, and evidence standards that will influence every other AI-imaging domain through 2032.

🔗 Read the full report details on AI Journ