June 2026: New IT Standards Drive Biometric Security, AI, and Digital Ecosystems

As digital transformation accelerates, June 2026 brings a significant wave of newly published standards shaping information technology, digital platforms, and AI-driven applications. This second installment in our four-part series dives into five key standards covering biometric face identification, medical device risk management for machine learning, electronic fee collection, intelligent multimedia analysis, and frameworks for the sharing economy. Each standard delivers robust requirements to enhance interoperability, security, and innovation—providing essential guidance for compliance officers, IT leaders, engineers, and policy makers across sectors.

Overview

The Information Technology and Office Equipment sector continues to be at the forefront of digital advancement and regulatory oversight. Standards in this space foster interoperability, security, and reliability, allowing stakeholders to drive innovation while ensuring global alignment on best practices. This article unpacks the objectives and detailed requirements embedded in five newly released standards, equipping professionals with the knowledge they need to ensure compliance and harness business value from these latest developments.

Readers will discover:

• Key technical requirements and guidance for biometric and AI-powered systems
• Details on electronic toll collection test procedures
• Multimedia video optimization concepts for machine analysis
• A holistic framework for implementing sharing economy models
• Practical tips for compliance, industry impact, and technical implementation

Detailed Standards Coverage

CEN/TS 18212-5:2026 – Face Biometrics for Personal Identification

Personal identification – Requirements for biometric products – Part 5: Face biometrics

CEN/TS 18212-5:2026 is dedicated to setting the evaluation methodology and defining application profiles for face biometric products. This standard is part of a broader series that underpins the development and assessment of biometric identification systems, focusing particularly on face recognition.

Scope and Key Requirements:

• Establishes general requirements and resources for evaluating face biometric systems, including specifications for capture devices, scenarios, and background settings.
• Defines standardized TESTs for performance and robustness, ensuring products are evaluated consistently across various scenarios (e.g., different capture devices, lighting conditions, background variations, and subject appearance).
• Details a multi-phase assessment framework, including interoperability, performance, and vulnerability analysis covering attacks such as morphing, the use of masks, makeup, or data injection.
• Includes application profiles tailored for public sector deployments (e.g., digital identity onboarding, remote identity verification) and supports compliance with EU cybersecurity act requirements.

Who Should Implement:

• National ID authorities, border control, banking and financial organizations leveraging facial biometrics for authentication and onboarding.
• IT and system developers, solution integrators, and quality assurance teams building or evaluating face recognition systems.

Practical Implications:

• Enables more secure, interoperable, and testable biometric products
• Reinforces impartiality and consistency in face recognition system evaluations via normative criteria and reference toolkits
• Addresses threat modeling but leaves out the storage and communication system vulnerability assessments, focusing solely on the biometric application's functional security

Key highlights:

• Structured test phases for technology & vulnerability evaluation (including morphing and mask attacks)
• Defined levels of assurance (LoA) for different deployment use cases
• Annexed application profiles for digital wallets and remote verification

Access the full standard:View CEN/TS 18212-5:2026 on iTeh Standards

ISO/TS 24971-2:2026 – Guidance on Risk Management for Machine Learning in Medical Devices

Medical devices — Guidance on the application of ISO 14971 — Part 2: Machine learning in artificial intelligence

ISO/TS 24971-2:2026 addresses the risk management process for medical devices utilizing machine learning (ML). It expands on ISO 14971 and ISO/TR 24971 by identifying the unique risks posed by AI and ML-enabled medical devices (MLMD), with explicit exclusions for large language models or generative AI.

Scope and Key Requirements:

• Provides guidance on applying established risk management processes to MLMD, with an emphasis on the specific risks associated with autonomous behavior, bias, explainability, and retraining.
• Outlines steps for risk analysis, risk control, and post-production monitoring tailored for MLMDs, including system training, data management, bias mitigation, and disclosure of significant residual risks.
• Calls for clear distinction between traditional device acceptance criteria and ML performance targets, stressing the need to establish criteria early in the development process.
• Discusses management responsibilities, competence of personnel, documentation, production, and ongoing post-production information gathering.

Who Needs to Comply:

• Medical device manufacturers designing and deploying AI or ML-powered diagnostic, monitoring, or decision aid systems
• Regulatory affairs professionals, quality managers, and developers involved in health IT and medical device risk evaluations

Practical Implications:

• Equips organizations to proactively identify and mitigate new safety and cybersecurity risks emerging from machine learning algorithms in medical devices
• Fosters improved patient outcomes and trust by ensuring transparency and continuous control over MLMD performance
• Provides actionable annexes on bias, hazard identification, and managing ML autonomy

Key highlights:

• Full integration with ISO 14971 risk management principles
• In-depth guidance on AI/ML-specific risks (e.g., bias, explainability, retraining, post-market monitoring)
• Alignment with global regulatory trends for safer, more reliable AI in healthcare

Access the full standard:View ISO/TS 24971-2:2026 on iTeh Standards

prEN ISO 14907-1 – Electronic Fee Collection Test Procedures

Electronic fee collection - Test procedures for user and fixed equipment - Part 1: Description of test procedures (ISO/DIS 14907-1:2025)

This upcoming standard is instrumental for the automated tolling and electronic fee collection (EFC) industry. prEN ISO 14907-1 defines test procedures for user (on-board) and fixed (roadside) equipment, ensuring the reliability, interoperability, and compliance of toll systems worldwide.

Scope and Key Requirements:

• Specifies detailed test procedures for EFC roadside equipment (RSE) and on-board equipment (OBE), focusing on dedicated short-range communication (DSRC) protocols and compliance with regional radio and traffic regulations.
• Categorizes test parameters into functionality, quality, referenced pre-tests, and provides plans and tools for validation.
• Does not set performance benchmarks, but defines comprehensive instructions and documentation requirements for conformance evaluation, type approval, and acceptance testing.
• Excludes enforcement and central administration systems, focusing strictly on OBE, RSE, and the DSRC interface between them.

Target Audience:

• Toll system developers, intelligent transportation system integrators, procurement specialists, and QA/certification bodies
• Highway and urban transport authorities seeking transparent methods for periodic and on-site equipment inspections

Practical Implications:

• Ensures seamless and accurate functionality of EFC systems in diverse operational environments
• Mitigates interoperability risks among vendors and across geographic regions
• Streamlines certification, acceptance, and periodic inspection processes through harmonized testing guidance

Key highlights:

• Defined sequence for pre-tests, functionality, and quality assessments
• All-encompassing toolbox for testing communication, environment, and DSRC-specific parameters
• Aligns with evolving European Electronic Toll Service (EETS) certification frameworks

Access the full standard:View prEN ISO 14907-1 on iTeh Standards

ISO/IEC TR 23888-3:2026 – AI for Multimedia: Optimization of Video Encoding and Analysis

Information technology — Artificial intelligence for multimedia — Part 3: Optimization of encoders and receiving systems for machine analysis of coded video content

ISO/IEC TR 23888-3:2026 provides emerging guidance on optimizing both video encoders and receiving systems specifically for machine analysis applications, such as object detection, tracking, and automated surveillance.

Scope and Key Specifications:

• Offers a concept-level overview of encoding, pre-processing, and post-processing strategies that enhance the efficiency and effectiveness of machine-driven video analytics.
• Discusses the use of metrics such as bit rate, PSNR, mean average precision (mAP), and multiple object tracking accuracy (MOTA) to benchmark optimization results.
• Details pre-processing (region-of-interest methods, noise filtering, subsampling), encoding (parameter adjustments, chroma offsets), and post-processing enhancements.
• Introduces the use of advanced metadata (object masks, annotated regions, neural-network post-filters) to improve analysis capability

Who Should Use:

• Developers of video encoding/decoding systems for smart cameras, traffic management, urban security, and industrial process monitoring
• AI and computer vision researchers, multimedia system integrators, and equipment manufacturers

Practical Implications:

• Enables more efficient transmission and higher precision in automated video analysis tasks by customizing encoding strategies
• Supports intelligent transportation, industrial automation, and large-scale surveillance with optimized workflows
• Bridges the gap between video production and downstream AI consumption for scalable, robust applications

Key highlights:

• Extensive review of recent encoder optimization technologies for machine consumption
• Clear mapping of use cases: surveillance, smart vehicles, industrial visual inspection
• Guidance on deploying and assessing complex multi-step processing pipelines

Access the full standard:View ISO/IEC TR 23888-3:2026 on iTeh Standards

ISO 42503:2026 – Framework for Implementing the Sharing Economy

Sharing economy — Framework for implementation

ISO 42503:2026 provides a universal framework for implementing sharing economy models across digital platforms. It is designed to facilitate responsible, effective, and sustainable sharing economy ecosystems spanning commercial, governmental, and non-profit contexts.

Scope and Main Requirements:

• Establishes governance, operational, and continual improvement frameworks for sharing economy platforms.
• Defines stakeholder relationships (platform operator, provider, user, supporting ecosystem) and their respective roles in facilitating safe and efficient exchanges.
• Covers legal, social, environmental, and compliance considerations, including risk management, complaints handling, and governmental roles.
• Applies to organizations of all sizes and types, promoting alignment with UN Sustainable Development Goals (SDGs).

Implementation Guidance:

• Outlines best practices for platform governance, human resources, transparency, and stakeholder engagement
• Recommends mechanisms for provider verification, supply chain controls, and redress procedures
• Supports sectoral innovation by accommodating advanced technologies like blockchain, AI, cybersecurity, and digital ID verification

Target Organizations:

• Platform operators, sharing economy service providers, regulatory agencies, and consultants
• Entities seeking to build, scale, or audit digital sharing services (peer-to-peer, B2B, B2C)

Key highlights:

• Comprehensive operational and compliance framework for sharing economy participants
• Strong focus on risk management and continual improvement processes
• Direct alignment with ISO’s core principles for quality and sustainability

Access the full standard:View ISO 42503:2026 on iTeh Standards

Industry Impact & Compliance

Business Impact

Adopting these new and revised standards is essential for organizations aiming to:

• Accelerate innovation in biometrics, artificial intelligence, and digital platforms
• Ensure products, systems, and services meet regional and international regulatory requirements
• Reduce legal and operational risks by following standardized evaluation, risk management, and compliance procedures

Compliance Considerations

• Most standards specify immediate applicability for new products, while transition arrangements may be considered for existing deployments
• Compliance may be mandated for market access, procurement, and certification (especially in regulated sectors such as healthcare, transportation, and digital identity)
• Risks of non-compliance include loss of certification, penalties, product recalls, and exclusion from key digital infrastructure contracts

Benefits

• Increases trust and reliability in digital and AI-powered products
• Enhances organizational reputation and customer confidence
• Facilitates global market access and cross-border interoperability

Technical Insights

Common Technical Requirements

• Robust test and validation methods for security, interoperability, and user privacy (biometrics, AI, EFC)
• Specific documentation and evaluation artifacts required for audit and certification
• Data quality, system transparency, and explainability emphasized throughout (particularly for ML and sharing economy models)

Best Practices for Implementation

1. Engage early with risk, compliance, and technical leads in product development.
2. Document system designs, data flows, and evaluation procedures per standard requirements.
3. Integrate evolving best practices—e.g., bias mitigation (AI), DSRC protocol adherence (EFC), continual improvement (sharing economy frameworks).
4. Conduct internal or third-party testing using reference methodologies and toolkits.
5. Keep abreast of updates in related international standards to maintain ongoing compliance.

Testing and Certification

• Ensure that test plans, evaluation metrics, and documentation are fully aligned with the given standards
• Use accredited test houses or certification bodies where external validation is needed
• Leverage annexed scenarios and application profiles for complex cases (e.g., remote biometric onboarding)

Conclusion / Next Steps

June 2026 marks a significant milestone in the standardization of information technology—creating new opportunities for secure biometric authentication, responsible AI in healthcare, reliable electronic tolling, optimized multimedia AI, and sustainable peer-to-peer digital platforms. Organizations should review these new standards, update internal policies, and ensure comprehensive training for their teams.

Recommendations:

• Audit existing systems and processes for gaps against new requirements
• Plan for timely adoption—especially in regulated or fast-evolving sectors
• Consult each standard directly for detailed guidance and interpretation
• Bookmark iTeh Standards for the latest updates and access to the full library of standards

Stay ahead of regulatory trends and innovation—integrate these authoritative standards now to future-proof your operations and lead in the new digital era.