The Testing, Inspection, and Certification (TIC) industry is modernising how trust is delivered through agile, digitally supported approaches that reflect current industrial practices, shaping the future of efficient, scalable, and trustworthy conformity assessments.

The accelerating pace of digital innovation requires Quality Infrastructure (QI) to evolve by strategically adopting new technologies to meet the demands of a rapidly digitalising world. For QI to remain relevant in today’s tech landscape, all actors (Accreditation Bodies, Standard Development Organisations, Metrology Institutions, Conformity Assessment Bodies) must innovate, share best practices, and cooperate effectively to preserve the trust at the heart of third-party assurance.

Integrating cutting-edge tools—including Artificial Intelligence (AI), Internet-of-Things (IoT), and digital twins—into long-established QI processes demands a framework for responsible adoption grounded in clear principles. The TIC industry advocates for the freedom to adopt emerging technologies while upholding
essential boundaries and non-negotiable principles of independence, impartiality, and technical competence.

Central to this framework is the human-in-the-loop (HITL) principle, which ensures that human oversight and human accountability are integrated at critical decision points so that technological innovation enhances, rather than replaces, professional judgment and responsibility.

TIC Council Recommendations

1. Recognise and facilitate digital conformity methods that uphold established QI principles while sustainably integrating deep technical expertise and practical experience.
2. Establish red lines, specifically that human accountability for conformity outcomes remains non-delegable and clearly assigned within the accredited TIC organisation.
   • While full automation of conformity decisions is not acceptable in the current state of innovation and adoption within the TIC sector, we encourage ongoing dialogue and frameworks that leave room for the potential integration of fully automated processes in the future.
   • The threshold between permissible semi-automation and inadmissible full automation in decision-making must be clearly defined, with input from all TIC members.
3. Modernise accreditation models to reflect the reality of AI-supported audit and testing, remote inspections, and continuous assurance, without which the absence of clear digital accreditation schemes risks undermining public
   trust.
4. Mandate transparency and auditability for all digital tools used in assurance processes.
5. Reinforce the role of accredited, independent TIC providers as the foundation of trust in digital and physical systems alike.
6. Apply principle-based guardrails for emerging technologies, ensuring that:

• Tools are validated and used strictly within their proven scope and re-validated at defined intervals.
• Human accountability and oversight will continue to be integrated at critical decision points, particularly where higher risks are involved.
• Algorithms used in decision-making must be explainable and auditable to clients and regulators.
• Data integrity, traceability, and evidence quality must be guaranteed and protected.
• Secure, ethical handling of all collected data complies with relevant privacy regimes.
• Strengthen metrology alignment by ensuring that measurement methods, calibration, and traceability for new digital and sensor-based technologies are harmonised internationally and regularly updated to prevent fragmentation and maintain consistent global standards.