$2.17b AI surge projected by 2034 amidst pursuit to end missed cancer diagnoses

Asia-Pacific drives the fastest growth.

The global Artificial Intelligence (AI) in cancer diagnostics market is projected to reach $2.17b by 2034, expanding at a compound annual growth rate of 25.9%, driven by a global shift towards high-precision oncology and automated clinical workflows.

The Asia-Pacific region is poised to record the fastest growth through 2034, supported by aggressive healthcare digitalisation in emerging economies and increased government funding for AI-led medical innovation, according to Polaris Market Research.

North America currently holds the largest market share, underpinned by robust healthcare infrastructure, high R&D spending, and a technologically advanced regulatory environment.

Europe, Latin America, and the Middle East & Africa also present strong long-term growth opportunities as healthcare systems increasingly adopt smart diagnostic technologies, the report said.

The primary driver of this expansion is the rising global cancer burden, which requires faster and more accurate diagnostic capabilities than traditional methods can deliver.

AI technologies—particularly machine learning and deep learning—are addressing this gap by interpreting medical imaging and clinical datasets at unprecedented speed and scale.

Real-world evidence already supports this transition, with AI-assisted mammography reducing later-stage cancer diagnoses by 12% through earlier detection of malignancies, the report cited.

This capability to identify subtle anomalies that may escape the human eye continues to attract significant public and private sector investment.

Screening and Diagnosis remains the largest revenue-generating application, whilst Tumour Identification is emerging as the fastest-growing sub-segment, driven by AI’s high accuracy in distinguishing malignant from benign masses.

By cancer type, breast cancer diagnostics account for the largest market share, supported by the rapid integration of AI in mammography, whilst lung cancer applications are gaining momentum as demand rises for advanced CT imaging analysis.

Hospitals remain the dominant end-user, serving as the primary deployment point for AI solutions, followed by diagnostic centres and research institutes, as adoption continues to shorten diagnostic turnaround times and support precision medicine initiatives.

Looking ahead to 2034, strategic partnerships between technology firms and established medical device manufacturers are expected to accelerate adoption by reducing clinician workload and improving workflow efficiency.

For industry stakeholders, the coming decade represents a critical opportunity to capitalise on the convergence of digital technology and life sciences, positioning AI-enabled diagnostics as a global standard of care in oncology.