A service agent promises high value but needs data approval that is not yet available and the same scarce specialist as other initiatives. An internal search tool can be tried in a limited way with approved documents. Decide which AI initiative should start first.
Compare four to six AI use cases by value, data, effort, risk and shared resources. Set quality and value criteria for the search tool before assessing supplied test results against the previous way of working. Then revise the sequence if specialist capacity falls or data approval does not arrive.
Take away an editable portfolio with resources, dates and next tasks. Your own cases can replace the supplied profiles.
What you will work on
You formulate a decision question for four to six AI use cases and assign an owner and the limits of that role’s mandate.
You assess each case for expected value, feasibility, risk and dependencies, making assumptions and evidence gaps explicit.
You reorder four to six initiatives after a reduction in specialist capacity.
Who it is for
Transformation leads
Business-unit leaders with AI initiatives
Portfolio or programme owners
Topics
Portfolio boundaries and decision questions
Value hypotheses and strength of evidence
Feasibility, data readiness and technical prerequisites
Risk, control needs and unresolved legal and data protection questions
Dependencies, sequencing and scenario testing
Decision memo and handover to responsible management
Your result
Your editable AI portfolio records use cases, comparison criteria, shared resources, dates and next tasks. Update the sequence when new information arrives.
Prerequisites
Experience in leading projects or change initiatives, plus access to a list of use cases and to people who can answer questions on value, data and risk. A basic understanding of AI use cases is helpful; programming knowledge is not required. If access is unavailable or information is confidential, you work on a case study with a comparable decision structure.
Format and approach
Planned: 5–6 hours of self-study, with four to six case profiles, templates, an annotated example and self-checks.
Several AI initiatives compete for budget and specialist staff. Your leadership team compares them, allocates resources and reorders the portfolio when conditions change. Keep an editable board with follow-up assignments, owners and dates for further work.
Assess whether an AI initiative delivers its promised value and whether it should be scaled, adapted or stopped. Define a baseline and suitable indicators, separating available measurements from estimates and assumptions.
Your leadership team connects a concrete strategic decision with the development of initial AI tools. You assess options, test work processes and agree which decisions remain with people, which tasks AI may perform and what needs to happen over the next 90 days.