Data Readiness & AI Foundations
Prepare the information and integration required for AI applications to work reliably.
AI & Automation
AI Use-Case Strategy & Investment Case
Prioritise AI investment around value, feasibility and control.
Overview
What this means for your business.
AI investment decisions should start with the business outcome and the process that will use the capability. Value, feasibility, data, risk and cost all affect whether a use case deserves investment.
Capmark helps clients assess use-case portfolios, compare build, buy and partner options, and develop investment cases and roadmaps.
We distinguish applications that require AI from those better served by simpler automation, and make the ownership, dependencies and measures of value explicit.
What we do
The expertise we bring.
We assess the full register of AI ideas and pilots, then rank each use case by value, data readiness, control burden and run cost. The output is a funded shortlist, a stop-list with reasons and a clear sequence for delivery.
We test each shortlisted case against the data it needs: quality, completeness, access, lineage and how outputs reach the people who act on them. Where gaps are material, the data fix becomes a costed part of the roadmap.
We classify each use case before funding based on decision impact, data sensitivity, human oversight and monitoring requirements. The governance route is known before design and build begin.
We separate simple automation, model-assisted workflow and agentic AI use cases. Each has different costs, risks and controls, so they are scoped, funded and governed differently.
We build costed investment cases with stage gates, funding tranches, evidence requirements, run costs and named benefit owners. Delivery can start without re-scoping.
What to expect
A team shaped around the work.
A Senior Practitioner leads throughout. The first weeks build the use-case inventory with business, technology, risk and compliance, then test each case against value, data readiness and control requirements.
We then score, sequence and pressure-test the portfolio with executive sponsors.
Engagements run as a short senior-led assessment, either standalone or as the front end of a broader AI delivery programme.
Support can range from a focused investment case to prioritisation of an enterprise AI portfolio.
01
Assess
Establish the current state, the constraints, the risks and the value at stake.
02
Define
Shape the target model and the business case with the executives who own the outcome.
03
Mobilise
Stand up the team, the plan and the governance around the outcome.
04
Implement
Design, build and test the change, with the business alongside.
05
Sustain
Cutover, hypercare and handover, so the business runs it under its own control.
The same five stages on every engagement, led by senior practitioners end to end. How we work
Client result
Relevant client experience.
Asset & Wealth Management · Financial Crime
Financial-crime controls rebuilt for the world's largest alternative asset manager
The World's Largest Alternative Asset Manager · Financial Crime Transformation
The firm partnered with us to convert regulatory findings on AML control deficiencies into a resilient financial-crime framework: customer risk assessment, screening, enhanced due diligence and AI-assisted alert reduction, remediated to completion under independent scrutiny.
- 100%
- AML findings closed and evidenced to the independent monitor
- 3
- Control domains rebuilt: customer risk assessment, name screening and enhanced due diligence
- 5
- Interlocking initiatives directed
Read the case study
Insights
Related perspectives.
Get in touch
Discuss AI Use-Case Strategy & Investment Case.
Tell us what you are working through and the expertise you need.