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How to Avoid the Quality Control Approval Trap When Using AI

Sue Lhymn, Ph.D.

Enterprise HRIS & Quality Leader

Laura Harris, Ph.D.

Data Quality & AI Risk Specialist

Use AI to catch what QC requirements, reports, and updates are hiding.

Most project documents look complete. Requirements feel thorough. Status reports read confidently. Updates sound reassuring, but the gaps that cause delivery failures rarely announce themselves. They hide inside vague acceptance criteria, missing edge cases, and assumptions no one questioned at sign-off. This workshop focuses on that critical window between receiving a document and approving it. Instead of relying on instinct or a quick read-through, you will learn how to use AI as a structured verification partner; one that surfaces what's missing, flags what's ambiguous, and confirms what actually needs to be true before the work begins. If you have ever approved something that later turned into a costly rework, a missed dependency, or a scope dispute, this session will give you a repeatable system to prevent it. You will leave with an AI-powered verification framework you can apply to requirements, status reports, and project updates starting the same day.

What you’ll learn

    Workshop agenda

    • Welcome and Introductions

      Get to know your instructor and fellow PMs, BAs, and Product Owners

    • Why Approvals Fail

      Understand the structural reasons documents pass review with hidden gaps, and where AI changes the equation

    • Break

      Take a moment to connect with your instructor and classmates

    • Build Your Verification Prompts

      Hands-on: craft AI prompts that interrogate requirements, surface assumptions, and flag missing acceptance criteria in real documents

    • Break

      Take a moment to connect with your instructor and classmates

    • Apply It to Status Reports and Updates

      Extend the framework to progress reports and change requests; the documents most likely to obscure delivery risk

    • Your Personal Verification Checklist

      Leave with a tailored, reusable checklist and prompt library matched to your project context

    • Closing

      Connect with your instructor and classmates before you go

    Learn directly from Sue & Laura

    Sue Lhymn, Ph.D.

    Sue Lhymn, Ph.D.

    HRIS Manager with 25+ years in systems, data, and analytics

    Erie Insurance
    National University
    Laura Harris, Ph.D.

    Laura Harris, Ph.D.

    CEO of an AI-driven, IP-generating, quality-focused company

    Pfizer
    Emergent
    University of Phoenix
    Davenportu
    National University
    See all products from Harris Analytics Institute

    Who this workshop is for

    • PMs, BAs, and Product Owners who are the last line of defense before a document moves to execution and want to be confident in that role

    • Stakeholders who approve project documents regularly but lack a structured method for knowing what to look for

    • Delivery leads who have experienced late-stage surprises caused by gaps that were present at sign-off but never caught.

    What's included

    Live sessions

    Learn directly from Sue Lhymn, Ph.D. & Laura Harris, Ph.D. in a real-time, interactive format.

    Hands-on verification practice

    Work through real document examples with AI tools at each step; leave with prompts you can use immediately

    Verification prompt library

    A ready-to-use collection of AI prompts for requirements, status reports, and change requests

    Lifetime access

    Return to recordings and materials whenever you need a refresher

    Community of peers

    Stay connected with a cohort of practitioners facing the same approval challenges

    Certificate of completion

    Share your new capability with your employer or on LinkedIn

    Maven Guarantee

    Your purchase is backed by the Maven Guarantee.

    Free resource

    Don’t Be Fooled: Drive Business Outcomes with ISO Standards cover image

    Don’t Be Fooled: Drive Business Outcomes with ISO Standards

    Apply ISO quality principles in practical, everyday work.

    Be more efficient in working with stakeholders through customer focus, process and risk-based thinking.

    Turn quality objectives into clear, actionable processes.

    Reduce ambiguity by defining requirements and expectations clearly.

    Build repeatable, ISO-aligned quality practices that scale.

    Continuously improve by managing requirements, processes, and controls consistently.

    Testimonials

    • Your focus on customer orientation, continuous improvement, process thinking, and risk-based thinking is especially relevant right now, particularly for people working in AI and other fast-moving technical spaces where strong outcomes depend on strong systems.

      As someone working at the intersection of data, AI, and organizational performance, I found this talk to be a valuable reminder that quality is not just about end results; it is about the strength of the processes that produce them.

      Testimonial author image

      Dylan Collier

      Medical Operations Planner - US Navy

    Frequently asked questions

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