Data Readiness & AI Foundations
AI only works where the data is complete, accessible, controlled and connected to the workflow.
AI & Automation
AI Use-Case Strategy & Investment Case
Fund the AI use cases your data and controls can support.
Overview
AI use-case registers grow faster than production deployments. Pilots multiply, platform costs rise and few use cases reach a live process where the benefit can be measured.
Capmark helps institutions turn AI ideas into a governed investment portfolio. We score each use case against value, data readiness, control burden and cost to run, then sequence funding through stage gates and stop criteria.
Weak cases stop before build money is spent. Strong cases move forward with a clear business owner, data plan, governance route and investment case written for approval.
What we do
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 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.
Runs as a short senior-led assessment — standalone, or as the front end of a broader AI programme.
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
Proven in the work, not the pitch.
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.
- 5
- Interlocking initiatives directed
- AI/ML
- Screening false positives reduced
- 2 clouds
- Azure and AWS delivery
- Evidenced
- To independent monitors
Read the case study
Insights
Related thinking.
Get in touch
Talk to a Partner about AI Use-Case Strategy & Investment Case.
Tell us what needs to change and where the pressure or risk is showing.