Portfolio & prioritization
A way to choose what ships next — balancing risk, value, readiness, and organisational capacity.
- Firms with five or more candidate AI initiatives and no method to choose
- Leadership teams under board or sponsor pressure to show a coherent plan
- Firms preparing for a multi-quarter investment, not a single pilot
- Single-initiative firms (use Executive Advisory instead)
- Pure technical selection (workflow tooling, vendor vs. vendor)
Why does AI prioritization fail at mid-market firms?
Two reasons. First, the loudest stakeholder wins, regardless of fit. Second, capacity is invisible — firms commit to five initiatives when they have headroom for two. Our scoring model surfaces capacity explicitly, and the executive workshop forces a sequenced answer rather than a parallel one.
What does the scoring model evaluate?
Four dimensions: value (cash-equivalent impact, time-to-value), readiness (data, workflow, governance), capacity (internal team load, change tolerance), and risk (regulatory, reputational, technical). Each candidate gets a score; the roadmap sequences by score and dependency.
How does this connect to delivery?
Direct. The top-ranked initiative on the roadmap is usually the first delivery engagement we scope (or a partner does). We hand off with a brief, an owner, and a target outcome — not a slide.
Frequently asked
- Is the output a deck or a working tool?
- Both. The scoring model is a working spreadsheet your team uses as the candidate list evolves. The roadmap is a 1-page executive summary plus the underlying detail. We optimize for what gets used in week six, not what looks best in week three.
- How do you handle disagreement among the executive team?
- The scoring model creates a structured disagreement — instead of arguing about whether initiative A should ship first, the conversation becomes ‘what do we believe about A’s readiness score?’ That is a more productive argument and usually resolves in one workshop.
Related
- AI advisory for mid-market law firms
- AI operating model — Roles, decision rights, governance, and a practical cadence — so AI work doesn’t live in a lab or a slide deck.
- Product & delivery support — We work alongside your teams as the work becomes real — shaping scope, unblocking decisions, keeping quality intact.
- Executive advisory — A steady partner for complex terrain — governance, vendors, capability building, and the hard calls that don’t fit a template.