Artificial Intelligence-Enabled Biometrics

Global Artificial Intelligence-Enabled Biometrics Market to Reach US$49.0 Billion by 2030

The global market for Artificial Intelligence-Enabled Biometrics estimated at US$18.7 Billion in the year 2024, is expected to reach US$49.0 Billion by 2030, growing at a CAGR of 17.5% over the analysis period 2024-2030. Healthcare End-Use, one of the segments analyzed in the report, is expected to record a 17.4% CAGR and reach US$21.2 Billion by the end of the analysis period. Growth in the BFSI End-Use segment is estimated at 19.2% CAGR over the analysis period.

The U.S. Market is Estimated at US$4.9 Billion While China is Forecast to Grow at 16.5% CAGR

The Artificial Intelligence-Enabled Biometrics market in the U.S. is estimated at US$4.9 Billion in the year 2024. China, the world`s second largest economy, is forecast to reach a projected market size of US$7.6 Billion by the year 2030 trailing a CAGR of 16.5% over the analysis period 2024-2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at a CAGR of 16.0% and 15.1% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 12.8% CAGR.

Global Artificial Intelligence-Enabled Biometrics Market – Key Trends & Drivers Summarized

Why Is AI Enhancing the Capabilities of Biometric Technologies Across Security and Identity Management?
Artificial Intelligence (AI)-enabled biometrics are revolutionizing identity verification and access control by improving accuracy, adaptability, and decision-making across biometric modalities such as facial recognition, iris scanning, fingerprint analysis, voice recognition, and behavioral biometrics. Traditional biometric systems depend on static pattern-matching techniques that can be limited by poor image quality, aging, spoofing attacks, or environmental variability. By integrating AI—especially deep learning and neural networks—modern biometric systems can dynamically learn from large datasets, continuously refine matching algorithms, and adapt to evolving patterns, thus significantly enhancing authentication robustness and reliability.

This intelligence layer allows biometric systems to perform complex recognition tasks with greater resilience to noise, partial inputs, or disguises. AI also enables contextual awareness by correlating multiple biometric and behavioral parameters (e.g., typing patterns, gait, eye movements) to verify identity or detect anomalies in real time. As cybersecurity threats escalate and digital transformation deepens, AI-enabled biometrics are becoming vital tools in sectors such as border control, banking, healthcare, law enforcement, enterprise IT, and smart city infrastructure—offering scalable, touchless, and frictionless security solutions.

How Are Deep Learning Models and Multimodal Systems Expanding Biometric Performance and Applications?
Deep learning models—particularly convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers—are at the heart of AI-enabled biometric systems, driving breakthroughs in pattern recognition and feature extraction. These models can process high-dimensional inputs, such as 3D facial maps, thermal imaging, or audio signals, to achieve superior precision in identity matching even under challenging conditions like low lighting, varied angles, or noisy environments. Continuous model training using real-world datasets enhances system resilience and reduces error rates, false acceptances, and rejections.

Multimodal biometrics—where AI fuses multiple types of biometric data such as facial features combined with voice or fingerprints—are gaining traction due to their ability to compensate for the limitations of single-modality systems. These hybrid systems improve authentication confidence and user experience, especially in high-security contexts like airports, military installations, and financial services. Additionally, AI is enabling liveness detection to counter spoofing attacks using masks, photos, or deepfakes, ensuring the person being authenticated is physically present. This capability is increasingly important as identity fraud and biometric spoofing threats become more sophisticated.

Where Is Adoption of AI-Enabled Biometrics Accelerating and Which Sectors Are Leading Deployment?
AI-enabled biometric systems are experiencing rapid adoption across North America, Europe, and Asia-Pacific, with the U.S., China, India, the U.K., and South Korea among the most active markets. Government and defense sectors lead in deployment for border security, national ID programs, and forensic analysis. Airports, for instance, are implementing facial recognition gates for automated immigration and boarding, significantly reducing wait times and human error. Law enforcement agencies use AI biometrics for surveillance, suspect identification, and forensic investigations, leveraging real-time facial analysis and crowd behavior analytics.

In financial services, biometric authentication is being used for mobile banking access, ATM security, and fraud prevention—often replacing or complementing PINs and passwords. The healthcare sector is deploying biometric identity management to ensure accurate patient matching, secure medical record access, and authorized staff entry. Enterprises are using biometric authentication for zero-trust network access, time and attendance management, and secure remote logins. In consumer electronics, smartphones and wearables now routinely incorporate AI-enabled facial or fingerprint recognition, voice command personalization, and gesture-based interactions—embedding biometrics into everyday life.

What Is Driving the Global Growth of AI-Enabled Biometrics?
The growth in the AI-enabled biometrics market is driven by several converging trends, including the global shift toward contactless security, rising cyber and identity fraud threats, and increasing demand for seamless user authentication. A key driver is the maturity of AI technologies, which now allow biometric systems to operate at scale, in real-time, and with enhanced accuracy across diverse user populations and environments. Regulatory pressures for stronger data protection and identity assurance—such as GDPR, PSD2, and eIDAS in Europe, and KYC/AML mandates worldwide—are further accelerating enterprise investment in biometric solutions.

Advancements in edge AI chips, mobile computing, and 5G connectivity are enabling biometric processing directly on devices, preserving user privacy while reducing latency and reliance on cloud infrastructure. Cross-industry partnerships between biometric vendors, AI platform providers, and system integrators are also fostering scalable solutions for both public and private sectors. Additionally, rising public acceptance of biometrics in daily transactions—combined with enhanced liveness detection, encryption, and privacy-preserving techniques such as federated learning—is reinforcing market momentum. As AI transforms identity management into a smarter, frictionless, and adaptive process, a key question now arises: Can AI-enabled biometrics strike the balance between ubiquitous convenience, high-security standards, and ethical data governance in an increasingly digitized world?

SCOPE OF STUDY:

The report analyzes the Artificial Intelligence-Enabled Biometrics market in terms of units by the following Segments, and Geographic Regions/Countries:

Segments:
End-Use (Healthcare, BFSI, Transportation & Logistics, Government & Law Enforcement, Other End-Uses)

Geographic Regions/Countries:
World; United States; Canada; Japan; China; Europe (France; Germany; Italy; United Kingdom; and Rest of Europe); Asia-Pacific; Rest of World.

Select Competitors (Total 32 Featured) -

• Aware Inc.
• Ayonix Pty Ltd
• Biocube Technologies Inc.
• BIODIT Global Technology Ltd.
• BioEnable Technologies Pvt. Ltd.
• Camvi Technologies Inc.
• Clearview AI
• Cognitec Systems GmbH
• Facephi Biometria S.A.
• Fujitsu Limited
• Herta Security
• IDEMIA
• IDfy
• Incode Technologies Inc.
• Leidos Holdings Inc.
• M2SYS Technology
• NEC Corporation
• Neurotechnology
• Nuance Communications
• Onfido

TARIFF IMPACT FACTOR

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APRIL 2025: NEGOTIATION PHASE

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