Forward Assurance for AI Systems
- Raimund Laqua
- 22 hours ago
- 2 min read
Audit looks backward. It verifies that something was done.
Forward assurance is confidence that a system will keep its promises in operation — and that confidence cannot be inspected in after the fact.
It is engineered in, by design.
The gap
AI is adopted when it can be trusted with the work that matters.
We trust a mission critical system because we trust the people who design and build it, and the discipline they follow. That is what has to be established, and mostly it isn't.
Most of what is offered to close this gap checks the output, attests to it, or reports on it. None of it establishes that the work itself was done to engineering and regulatory standards.
Engineering is how the gap closes
We provide consulting services to help you establish engineering practice that meets professional standards — applying the methods, technical standards, and disciplines that govern how AI systems should be engineered, such as ISO/IEC 5338 and others that apply.
The result is a practice that creates trust because AI systems are engineered by competent and trustworthy practitioners, following proven engineering methods to professional and regulatory standards.
Three disciplines, working together
→ Engineering Methodology — how AI systems are engineered for the enterprise: architecture, capability requirements, risk-based phasing, and separation of concerns.
→ Project Assurance — independent engineering judgment over the build: stage-gating, acceptance criteria, and design review that keep each phase sound enough to support the next.
→ AI Compliance — compliance engineered into the system from the design stage: obligations, controls, and the regulator structure built into the architecture, not bolted on after.
Who this is for
Data, software, and IT solutions firms putting AI into client work.
Organizations pursuing licensed engineering practice or a Certificate of Authorization.
Engineering and delivery teams standing up AI capabilities to professional and regulatory standards.
Organizations bidding into regulated or public work, where engineering assurance is the basis they compete on.
If you are working to put real engineering practice behind your AI, reach out.
