DORA and Model Risk Push QA/QC into Continuous Control Testing
Regulatory pressure is turning QA/QC into a continuous assurance function focused on live control effectiveness, model monitoring, and audit-ready evidence.
What is this trend?
QA/QC is shifting from one-time release checks to continuous control testing that proves resilience, model governance, and compliance in live operations.
- DORA pushes QA/QC to prove controls keep working under stress, not just at release.
- Model risk guidance now requires ongoing validation and monitoring for AI and external models.
- Evidence generation, audit trails, and remediation tracking are becoming core QA/QC work.
- Teams must test cloud, third-party, and operational dependencies continuously.
- QA/QC roles are moving from defect detection to lifecycle control assurance.
What’s the latest?
EU DORA now makes the next requirement explicit for banks and fintechs: QA/QC must support ongoing ICT resilience testing, remediation of findings, and proof that controls stay effective under stress,
How it developed
Go deeper
Curated long-form picks on this trend — podcasts, videos, and analysis, by seniority.
If you're an individual contributor
Model versioning alone fails production AI systems, engineers argue for release manifests
Explainer by engineers on release manifests for end-to-end QA/QC, beyond model weights, for DORA-style continuous control testing.
news.lavx.hu · News
Read →AI Evolution Loops: How Continuous Deployment, Feedback, and Learning Could Create Self-Evolving AI Systems
News explainer on AI evolution loops, linking continuous deployment feedback to DORA-style continuous QA/QC controls.
AiThority · News
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Stop Testing AI Agents Like Normal Functions | HackerNoon
Explainer news piece on QA/QC for AI agents—contract checks, semantic grading, and continuous control testing.
HackerNoon · News
Read →If you manage a team

Proof Architecture: Evidence, Governance, and Ongoing Integrity
Substack explainer mapping four AI architectures to continuous QA/QC, DORA-style evidence, and post-deploy integrity checks.
Context & Chaos · Substack
Read →QMSR 2026: Quality as an Innovation Enabler, Not a Gate
News analysis of QMSR 2026 lifecycle quality, using PCCPs to shift QA/QC from checks to change control.
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Read →AI Agent QA & Testing: The Hidden Gap Nobody's Solving
News analysis on AI agent QA & testing, shifting from output checks to lifecycle evaluation and monitoring.
Nasscom · News
Read →If you lead the organization
Creating Confidence in Intelligent Systems: Tanvi Mittal on AI Quality Engineering, Security, and the Future of Trustworthy AI
Interview with Tanvi Mittal on shifting AI QA from output checks to lifecycle security, monitoring, and governance.
Tech Times · News
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Building AI Trust and Prioritizing Initiatives for Business Value
How-to podcast Q&A with David McKeering on lifecycle QA/QC controls, stress testing, and risk-led AI prioritization.
Fear & Greed Q+A · Podcast
Listen from 10:31 →Banking QA’s new reality: Is point-in-time testing ‘dead’
News analysis on banking QA shifting from point-in-time checks to continuous lifecycle monitoring and runtime governance.
QA Financial · News
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