LLM Evaluation & AI Output Quality Assurance
Measure generative AI quality before it measures you in public.
The executive challenge
The problem this program solves
Your competitors have industrialised their llm evaluation capability into pricing, service and operations while your organisation still debates the pilot. Every quarter of hesitation now compounds. The board does not need more dashboards; it needs an executive who can say where llm evaluation pays, where it does not, and how the institution will know. You leave with the frameworks to commission work on llm evaluation, interrogate its outputs and govern it with the discipline applied to any other capital allocation.
Context
Why this matters now
Capability
What you will be able to do
- Commission llm evaluation work and interrogate its outputs with an operator’s confidence.
- Distinguish llm evaluation automation opportunities from decisions where human judgement remains strategically important.
- Price the build, buy and partner options for llm evaluation capability with real economics.
- Govern llm evaluation models and data with controls that satisfy both boards and regulators.
The IPAT Course Standard
The five-day journey
Each day is a deliberate progression in managerial capability — from strategic context, to analytical frameworks, to applied practice, to executive judgement under pressure, to a capstone that produces something your organisation keeps.
IPAT Signature Case™
Six Weeks to Prove LLM Evaluation
A newly appointed chief data officer at a fast-scaling e-commerce platform inherits a llm evaluation mandate, one budget cycle to show value, and three functions that each claim ownership of the same dataset. The CEO wants a decision improved this quarter — not a strategy deck.
Your decision: Choose the single llm evaluation initiative worth proving in six weeks, name what gets stopped to fund it, and decide who owns the result.
IPAT Data Lab™
Three functions at a national revenue authority report three different truths about the same llm evaluation question.
Dataset: Synthetic multi-source llm evaluation dataset — finance, operations and customer tables that disagree.
Your task: Reconcile the sources, build the single defensible view, and decide which dashboard the executive committee keeps.
A reconciled llm evaluation decision view and the data architecture behind it.
Data → Analysis → Decision, not Data → Code → Certificate
Day 5 · The Capstone
What will you change when you return to work?
Build a twelve-month analytical and AI roadmap for your organisation: the value case, the data foundations, the governance, and the first 90 days.
Methodology
Frameworks you will master
- • IPAT Data-to-Decision Framework™
- • IPAT Executive Capability Model™
- • Value-versus-feasibility portfolio analysis
- • CRISP-DM analytical lifecycle
- • Model risk management principles (SR 11-7 adapted)
Cohorts
Upcoming cohorts
New dates are being scheduled
Register with your preferred start date and our admissions team will match you to the next available cohort — or contact us to arrange an in-house delivery for your organisation.
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