A new AI leader in the first ninety days
You need a defensible picture of current capability and a first portfolio before budget and expectations harden around the wrong work.
Ignite · Bounded diagnostic
AI Readiness Assessment
A readiness assessment answers a specific question: what can this organization responsibly put into production next? The output is a decision instrument, not an AI maturity score designed to flatter or alarm.
Who this is for
Start with the operating trigger, not the model.
A board mandate without operating detail
Executives need to connect ambition to workflows, accountable owners, measurable outcomes, investment, and risk boundaries.
A portfolio of stalled experiments
Teams have prototypes but no shared explanation of why they stalled or which one deserves a path to production.
What ships
Concrete artifacts your team can inspect and operate.
Readiness scorecard
A documented assessment of strategy, workflows, data, technology, team, governance, and change capacity with evidence behind each finding.
Opportunity map
Candidate use cases tied to operating pain, current baseline, affected users, available data, risk, and likely implementation effort.
Prioritized first initiatives
A short list of opportunities that are valuable enough to matter and constrained enough to execute, including explicit reasons for deferring the rest.
Implementation roadmap
Owners, phases, architecture decisions, dependencies, budget inputs, governance gates, and next actions for the selected initiative.
How the engagement works
Decisions and working systems in a visible cadence.
- 01 · Days 1–3
Collect the operating evidence
Review strategic goals, candidate workflows, systems, data access, current experiments, and existing security or governance requirements.
- 02 · Days 4–6
Interview owners and users
Map how decisions and handoffs actually happen, where delay or error enters, and which metric the accountable leader already watches.
- 03 · Days 7–8
Score opportunities and constraints
Compare impact, feasibility, readiness, risk, adoption burden, and speed to learning using evidence gathered in the assessment.
- 04 · Days 9–10
Make the roadmap decision
Deliver the scorecard, recommended first initiative, implementation sequence, ownership model, and conditions that would change the recommendation.
Reliability, security, and governance
Production boundaries are part of the product.
No maturity theater
Every score links to an observed artifact, interview, workflow, or system constraint, and uncertainties stay visible.
Sensitive access is minimized
Discovery starts with the least information needed. Production data is not copied into assessment documents unless the scope explicitly requires it.
Recommendations include stop conditions
The roadmap states what must be true before investment increases and when a use case should be paused, redesigned, bought, or abandoned.
Questions buyers ask
Scope the decision before you scope the software.
What does the AI readiness assessment evaluate?
It evaluates strategy, workflows, data, technology, team capability, governance, and change capacity in the context of a real operating objective.
Is this a technical audit?
It includes technical constraints, but it is broader than a stack review. A technically feasible system still fails if ownership, workflow adoption, measurement, or authority boundaries are missing.
What happens after the assessment?
You can execute the roadmap internally, with VallySeed, or with another partner. The deliverables are designed to stand on their own; a follow-on build is not required.
Do we need clean data first?
No. The assessment identifies which data is needed, where it lives, what access or quality constraints matter, and whether the first initiative should avoid those constraints.
Related services and resources