Catalogue › Opportunity Management

CopilotForge - Opportunity Management

Use it in Copilot Cowork: download the Opportunity Management plugin for Copilot Cowork and upload it under Customize > Plugins > Upload plugin. How to install.

Create a disciplined path from business problem to prioritised and governed initiative, including the decision about whether AI is the right answer at all.

Layer: transformation
Lead role: AI Portfolio Manager
Plugin name: copilotforge-opportunity-management

Skill Status Lifecycle Description

ai-suitability draft Envision, Deliver Decides whether a framed business problem should be solved with AI at all, and if so which pattern fits - Copilot Chat, a Cowork task, an agent, Copilot Code, a Foundry solution or plain automation - with the reasoning recorded. Use when an idea arrives at intake, when a team has already picked a tool, or when a sponsor asks why AI is preferable to process change or training.

backlog-management draft Mobilise, Deliver, Measure Sets up and operates the AI opportunity backlog as one visible board - choosing the tool, defining stages with entry and exit rules, mandatory fields per stage, work-in-progress limits, ageing rules, merges, archiving and a regular hygiene routine - so it stays the single route to resources. Use when there is no backlog or several competing lists, when the board is stale or cluttered, or when nobody trusts its status fields.

business-case draft Envision, Mobilise Writes a proportionate business case for one significant AI initiative - choosing no case, a light case or a full case by cost, risk and reach, then setting out options including a non-AI option, build and run costs, benefits from the value hypothesis, risks, the ask and the decision. Use when a single agent, automation or engineered solution needs funding or approval beyond delegated limits, or when a sponsor asks for a case before committing.

effort-assessment draft Envision, Mobilise Estimates what an AI opportunity will really take - build effort by pattern, the scarce skills and owners it needs, its dependencies on knowledge, data, platforms and reviewers, and the ongoing run cost after release - as ranges with stated confidence. Use when an opportunity needs a feasibility score, when a team says an agent will take a week, or when nobody has asked who will run and pay for a solution after launch.

idea-capture draft Discover, Envision Designs and runs the organisation's open route for staff to submit AI ideas - the submission channels, a short form, acknowledgement and triage timings, duplicate checks, idea campaigns and feedback to every submitter - so ideas reach the backlog instead of side requests. Use when there is no obvious place to send AI ideas, when ideas arrive through managers and chat threads and get lost, or when submissions have dried up.

opportunity-prioritisation draft Envision, Mobilise, Scale Scores and balances a backlog of framed AI opportunities on value, feasibility, risk, readiness of knowledge and ownership, and strategic fit, and shapes a portfolio of quick wins and strategic bets. Admits nothing without an owner, problem, outcome, risk tier and suitability decision. Use when ideas outnumber capacity, when a steering group must choose what goes next, or when the backlog has lost its link to outcomes.

pilot-selection draft Mobilise, Deliver, Measure Chooses which AI opportunities to pilot and designs each pilot so it can prove or disprove its value hypothesis - a representative cohort, a comparison, a fixed duration, success and stop thresholds set in advance, quality checks, risk containment and an exit plan. Use when an opportunity is ready to test with real users, when pilots keep running indefinitely, or when a pilot ended and nobody could tell whether it worked.

portfolio-balancing draft Mobilise, Scale, Improve Reviews the whole AI opportunity portfolio, planned and in flight, and rebalances its mix across quick wins, strategic bets and foundation work, risk-tier exposure, scarce owner and reviewer capacity, business units, outcomes and platforms, then decides what to start, pause, accelerate or stop. Use when the portfolio feels lopsided, when reviewers or owners are overloaded, or at each quarterly portfolio review.

problem-framing draft Envision Turns a raw idea or tool request into a framed business problem with a named business owner, affected roles, current cost, expected outcome and baseline, and politely sends solution-first requests back to the problem. Use when an idea arrives at intake, when someone asks for an agent or Copilot feature before saying what is wrong, or when a pilot cannot say what it was meant to improve.

risk-classification draft Envision, Assure, Scale Assigns a progressive risk tier from 0 to 4 to an AI opportunity or solution by rating impact, reach, data sensitivity and autonomy, then derives the minimum governance posture and the reviewer gates it must pass, and re-classifies when scope changes. Use when an idea has a chosen pattern, when a solution is about to be shared more widely, or when someone asks which reviews a build needs.

scale-or-stop draft Measure, Scale, Improve Makes the evidence-based decision after a pilot or first release to scale, iterate, pivot or stop, judged against the value hypothesis, adoption, quality and cost, and treats a well-evidenced stop as a success. Use when a pilot reaches its review date, when a sponsor wants to roll a solution out wider, or when a live initiative has been running for months without anyone deciding its future.

value-hypothesis draft Envision, Mobilise States the expected value of a framed AI opportunity as a testable hypothesis before anything is built - the mechanism of change, the measure, its baseline, an expected range, the date it should show, leading indicators and the result that would disprove it. Use when an opportunity is about to be prioritised or piloted, when a team claims an agent will save time without saying how, or when nobody can say what would count as failure.

Skill	Status	Lifecycle	Description
`ai-suitability`	draft	Envision, Deliver	Decides whether a framed business problem should be solved with AI at all, and if so which pattern fits - Copilot Chat, a Cowork task, an agent, Copilot Code, a Foundry solution or plain automation - with the reasoning recorded. Use when an idea arrives at intake, when a team has already picked a tool, or when a sponsor asks why AI is preferable to process change or training.
`backlog-management`	draft	Mobilise, Deliver, Measure	Sets up and operates the AI opportunity backlog as one visible board - choosing the tool, defining stages with entry and exit rules, mandatory fields per stage, work-in-progress limits, ageing rules, merges, archiving and a regular hygiene routine - so it stays the single route to resources. Use when there is no backlog or several competing lists, when the board is stale or cluttered, or when nobody trusts its status fields.
`business-case`	draft	Envision, Mobilise	Writes a proportionate business case for one significant AI initiative - choosing no case, a light case or a full case by cost, risk and reach, then setting out options including a non-AI option, build and run costs, benefits from the value hypothesis, risks, the ask and the decision. Use when a single agent, automation or engineered solution needs funding or approval beyond delegated limits, or when a sponsor asks for a case before committing.
`effort-assessment`	draft	Envision, Mobilise	Estimates what an AI opportunity will really take - build effort by pattern, the scarce skills and owners it needs, its dependencies on knowledge, data, platforms and reviewers, and the ongoing run cost after release - as ranges with stated confidence. Use when an opportunity needs a feasibility score, when a team says an agent will take a week, or when nobody has asked who will run and pay for a solution after launch.
`idea-capture`	draft	Discover, Envision	Designs and runs the organisation's open route for staff to submit AI ideas - the submission channels, a short form, acknowledgement and triage timings, duplicate checks, idea campaigns and feedback to every submitter - so ideas reach the backlog instead of side requests. Use when there is no obvious place to send AI ideas, when ideas arrive through managers and chat threads and get lost, or when submissions have dried up.
`opportunity-prioritisation`	draft	Envision, Mobilise, Scale	Scores and balances a backlog of framed AI opportunities on value, feasibility, risk, readiness of knowledge and ownership, and strategic fit, and shapes a portfolio of quick wins and strategic bets. Admits nothing without an owner, problem, outcome, risk tier and suitability decision. Use when ideas outnumber capacity, when a steering group must choose what goes next, or when the backlog has lost its link to outcomes.
`pilot-selection`	draft	Mobilise, Deliver, Measure	Chooses which AI opportunities to pilot and designs each pilot so it can prove or disprove its value hypothesis - a representative cohort, a comparison, a fixed duration, success and stop thresholds set in advance, quality checks, risk containment and an exit plan. Use when an opportunity is ready to test with real users, when pilots keep running indefinitely, or when a pilot ended and nobody could tell whether it worked.
`portfolio-balancing`	draft	Mobilise, Scale, Improve	Reviews the whole AI opportunity portfolio, planned and in flight, and rebalances its mix across quick wins, strategic bets and foundation work, risk-tier exposure, scarce owner and reviewer capacity, business units, outcomes and platforms, then decides what to start, pause, accelerate or stop. Use when the portfolio feels lopsided, when reviewers or owners are overloaded, or at each quarterly portfolio review.
`problem-framing`	draft	Envision	Turns a raw idea or tool request into a framed business problem with a named business owner, affected roles, current cost, expected outcome and baseline, and politely sends solution-first requests back to the problem. Use when an idea arrives at intake, when someone asks for an agent or Copilot feature before saying what is wrong, or when a pilot cannot say what it was meant to improve.
`risk-classification`	draft	Envision, Assure, Scale	Assigns a progressive risk tier from 0 to 4 to an AI opportunity or solution by rating impact, reach, data sensitivity and autonomy, then derives the minimum governance posture and the reviewer gates it must pass, and re-classifies when scope changes. Use when an idea has a chosen pattern, when a solution is about to be shared more widely, or when someone asks which reviews a build needs.
`scale-or-stop`	draft	Measure, Scale, Improve	Makes the evidence-based decision after a pilot or first release to scale, iterate, pivot or stop, judged against the value hypothesis, adoption, quality and cost, and treats a well-evidenced stop as a success. Use when a pilot reaches its review date, when a sponsor wants to roll a solution out wider, or when a live initiative has been running for months without anyone deciding its future.
`value-hypothesis`	draft	Envision, Mobilise	States the expected value of a framed AI opportunity as a testable hypothesis before anything is built - the mechanism of change, the measure, its baseline, an expected range, the date it should show, leading indicators and the result that would disprove it. Use when an opportunity is about to be prioritised or piloted, when a team claims an agent will save time without saying how, or when nobody can say what would count as failure.

Credit

Created by Simon Foote as part of CopilotForge. Content is licensed under CC BY 4.0; keep the credit in each skill's license and authors fields when you share or adapt it. See NOTICE.md in the repository.