EU AI Act compliance checklist: pragmatic dev & SaaS compliance steps

Many AI product teams and SaaS builders — roughly 500,000 globally by our estimate — face a suddenly concrete set of obligations from the EU AI Act: risk classification, documented risk management, model provenance, logging, and transparent model cards. The problem is practical: engineering teams need audit-ready evidence in CI/CD formats rather than legal prose, while compliance teams need repeatable artifacts that hold up to regulator and buyer scrutiny across fragmented national guidance. You could build a developer-first compliance platform: an SDK and CI/CD checks that enforce policy gates, automated generation of model cards and risk assessments, tamper-evident evidence logs for datasets and model lineage, plus pre-built templates mapped to specific AI Act articles and industry verticals. Delivered as SaaS with monitoring and alerting, the economics look feasible at an illustrative $16K ACV targeting an $8.0B addressable market (500k builders × $16K), with room for add-on professional services and audit integrations. This market is attractive now because law text has become enforcement reality and buyers are demanding demonstrable transparency; regulatory acceleration and the shift-left governance trend create an immediate runway for developer-integrated tooling. To stand out you’ll need rigorous mappings to legal requirements, lightweight developer ergonomics, and defensible evidence chains—strengths that a focused product can deliver—while being honest about challenges: competition is medium, rules will evolve, and winning trust requires third-party audits and ongoing updates.