Build and ship technology with the rules in view. Technology providers and digital businesses must navigate AI regulation, cybersecurity, data protection and platform obligations while continuing to innovate.
The regulatory picture
For technology businesses, regulation can attach to the product, the service, the data, the business model or the role played in an AI value chain. A single organisation may be a provider for one system and a deployer for another.
AI products and services
Understand provider and deployer roles, risk classification, prohibited practices, transparency requirements and obligations for general-purpose AI models.
Privacy by design
Product analytics, personalisation, training data and customer integrations all create data protection questions that need to be considered early.
Cybersecurity & resilience
Security expectations increasingly shape engineering practices, incident response, supplier assurance and service continuity.
Standards and assurance
Management systems and recognised standards can provide a structured foundation for security, governance and customer assurance.
Questions for product and engineering teams
- Have we mapped the AI features, models, datasets and external services embedded in our products?
- Can we explain our role and obligations for each AI system and intended use?
- Are privacy, security, accessibility and transparency requirements built into product delivery?
- Can customers understand the limitations, intended purpose and appropriate use of our technology?
- Do release and change processes account for evolving regulatory expectations?
A practical starting point
Build a product-level inventory that links systems and features to intended purposes, data, suppliers, users, risk owners and applicable requirements. Bring legal, product, engineering, security and commercial teams into the same conversation.
General educational information only. Lucentreg does not provide legal advice or certify products or services.
