AI Readiness and Use-Case Prioritization Sprint
Choose the right first AI workflow before you choose the tool.
The AI Readiness Sprint helps public health and mission-driven teams identify practical AI opportunities, compare risks, prioritize use cases, and build a realistic 90-day roadmap.
AI interest is high. Clarity is usually low.
Many teams have staff experimenting with AI, leaders asking about AI strategy, and several ideas for possible use cases. But without a clear way to compare those ideas, teams can waste time on workflows that are too vague, too risky, too hard to review, or not valuable enough to pilot.
The Readiness Sprint creates a practical decision process so your team can move from scattered ideas to a focused next step.
This is a good fit if your team:
Is interested in AI but unsure where to start
Has several possible AI use cases and needs help prioritizing
Wants to avoid risky or unrealistic first pilots
Needs to understand staff readiness, workflow fit, and review expectations
Wants a simple roadmap before investing in a larger project
Needs language to explain AI opportunities and boundaries to leadership or partners
What is included
The sprint may include:
Intake review and stakeholder interviews
Inventory of possible AI use cases
Workflow scoring using practical readiness criteria
Risk and feasibility review
Prioritized list of recommended first pilots
90-day implementation roadmap
Basic guardrail recommendations
Summary memo or presentation for leadership
Process
Step 1: Intake and context
Backyard-AI reviews your organization, audience, current workflows, tools, priorities, and concerns.
Step 2: Use-case inventory
Together, we identify possible AI-supported workflows across communication, reporting, evidence synthesis, training, resource navigation, and internal operations.
Deliverables
AI readiness summary
Ranked use-case list
Risk and feasibility notes
Recommended first workflow or pilot
90-day implementation roadmap
Leadership-ready summary
Next-step recommendation for training, workflow design, responsible AI guidance, or pilot development
Step 3: Prioritization
Each candidate workflow is assessed for value, repeatability, risk, source clarity, reviewability, staff adoption, and implementation feasibility.
Step 4: Roadmap
You receive a practical roadmap showing which workflow to pilot first, what to avoid, which guardrails are needed, and what success should look like.
Timeline and pricing
Typical timeline: 2 weeks to 3 months - rush work is available, but we won’t compromise quality
Typical range: Depending on scope, complexity, number of stakeholders, and deliverables.
Final pricing is quoted after discovery. Discount for non-profits.
Need help choosing the right first AI workflow?
Start with a readiness call. We will discuss your team, current workflows, possible use cases, and whether a Readiness Sprint is the right fit.