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Public course
Enterprise AI — Course 1: Framing AI Work and Requirements
Turn an AI proposal into a bounded, testable brief covering outcomes, task allocation, responsibilities, oversight, requirements and a useful pilot decision.
enterprise AIrequirementstask allocationoversightevaluationpilot design
By Telari Labs
Learning on Telari
Created by Telari Labs, delivered through Telari
The course creator controls the material and assessment standards. Telari provides structured lessons, practice, feedback against those standards and a record of your progress. See how Telari works.
AI access
The first managed lesson is included on Free. Continue with Plus or your own supported API key; premium assessments and certificates may require Plus.
Audio
No reviewed lesson audio is currently advertised for this course.
Lesson list
- Business outcomes and credible baselinesThis lesson connects generated outputs to useful outcomes and credible comparisons, including displaced work.
- Mapping the workThis lesson separates interpretation, confirmed facts, decisions and external actions and makes their dependencies explicit.
- Choosing AI and the level of assistanceThis lesson examines method and assistance choices using task structure, verification effort and action authority.
- System boundaries and responsibilitiesThis lesson examines supplied agreements and the responsibilities for sources, services and handovers.
- Consequences and effective oversightThis lesson connects oversight to consequences, evidence, real authority and feasible review capacity.
- Requirements and tradeoffsThis lesson develops checkable requirements and acceptance conditions and explains the limits of finite evidence.
- Designing a pilot that supports a decisionThis lesson develops a bounded pilot that supports a real continue, redesign or stop decision.
- Applying the complete briefThis assessment applies the complete brief to new organisational situations and a bounded next commitment.