CAI Collective GroupCAI COLLECTIVE GROUPTHINK · DO · TRANSFORM

Use cases

What the work looks like when it is scoped properly.

Representative engagements showing who they are built for, the scope of work, what gets delivered, and the outcomes we measure. Client names, pricing, prompts, configurations, and proprietary materials are never published.

Think. Do. Transform.

Eight scopes. One standard:nothing vague.

Every engagement names who it is for, what gets delivered, and how success is measured — before the work begins.

Representative engagements

Scopes you can read in one pass.

Learning & adoption

Applied AI learning and assistant ecosystem

Built for
Associations, professional communities, and enterprise learning teams
The problem
Members and employees have sat through AI awareness sessions and still cannot say which parts of their own work AI should touch.
Scope of work
A cohort-based applied program for roughly 120 professionals across four cohorts, paired with purpose-built assistant workspaces and implementation support.
What we do
  • Role and task analysis to identify where AI belongs and where it does not
  • Six-session applied curriculum built on real work, not generic exercises
  • Design and configuration of four purpose-built assistant workspaces
  • Office hours, coaching, and manager enablement through the cohort cycle
Deliverables
  • Applied curriculum and facilitator materials
  • Four configured assistant workspaces
  • Pre-, midpoint, and post-program assessments
  • Licensing and continuation pathway
Outcomes we measure
  • Measured change in applied AI use by role, not attendance counts
  • Confidence and judgment scores captured before, during, and after
  • A documented list of tasks moved into a governed AI workflow
Governance
Human-review checkpoints, role-based access, consent language, and defined escalation paths.
Typical timeline
10–14 weeks per cohort cycle after a paid discovery.
Enterprise AI

Responsible AI governance and implementation architecture

Built for
Executive teams with several pilots and no shared owner
The problem
AI activity is spread across teams with no decision rights, no controls, and no way to defend the next investment.
Scope of work
A readiness assessment, prioritized use-case portfolio, governance operating model, and a sequenced implementation roadmap.
What we do
  • Inventory of AI use already inside the organization, including embedded vendor features
  • Use-case prioritization by value, risk, and readiness — including what to refuse
  • Decision rights, human oversight design, and named accountability
  • Roadmap with success measures and stop criteria
Deliverables
  • Governance operating model and policy baseline
  • Prioritized use-case portfolio
  • Human-oversight and escalation design
  • Implementation roadmap with measures
Outcomes we measure
  • A defensible decision to expand, hold, or stop each use case
  • Baseline metrics captured before any launch
  • One accountable owner per system, documented
Governance
Designed against NIST AI RMF and ISO-aligned practice; policy, lifecycle review, and vendor criteria.
Typical timeline
6–10 weeks, fixed deliverables with a defined revision limit.
Custom builds

Custom AI assistants and governed workflows

Built for
Operations, service, and back-office teams with repeatable knowledge work
The problem
Skilled people spend hours on drafting, research, and summarizing that a governed workflow can carry.
Scope of work
Buy. Borrow. Build.™ evaluation, then design and delivery of assistants scoped to specific tasks with review built in.
What we do
  • Workflow mapping and task-level time baseline
  • Buy, borrow, or build recommendation with reasoning written down
  • Assistant design, source grounding, and guardrails
  • Team rollout with review and escalation rules
Deliverables
  • Assistant configuration and documentation
  • Workflow and review design
  • Team enablement session
  • Measurement plan with a before baseline
Outcomes we measure
  • Cycle time on targeted tasks measured before and after
  • Rework and review-failure rates tracked, not assumed
  • Clear list of tasks the assistant is not permitted to handle
Governance
Source verification, mandatory human sign-off, and no automated decisions about people.
Typical timeline
4–8 weeks per bounded build.
Government & defense

Federal GTM and prime-partnership strategy

Built for
Small businesses and specialty firms entering or growing in the government market
The problem
Real capability, no repeatable path into pursuits, and introductions that never turn into pipeline.
Scope of work
A governed pursuit process — Position, Validate, Match, Engage, Pursue, Govern — with owners and review points.
What we do
  • Capability positioning and market intelligence review
  • Prime and gap analysis against target work
  • Decision-maker mapping and engagement sequencing
  • Pursuit governance: owners, evidence, risks, and review gates
Deliverables
  • Market intelligence summary
  • Prime and gap analysis
  • Decision-maker map
  • Pursuit governance structure
Outcomes we measure
  • Qualified opportunities with documented evidence
  • Prepared teaming conversations with defined roles
  • A pursuit cadence the team can run without us
Governance
No awards, teaming agreements, subcontracts, or endorsements are implied or guaranteed by this work.
Typical timeline
8–12 weeks, then optional pursuit support.
Mission-driven orgs

AI-supported grant and funding readiness

Built for
Nonprofits and community organizations with limited development capacity
The problem
Small teams spend more time hunting for funding than preparing to win it.
Scope of work
A governed research and funding-readiness workflow with human review of every AI-supported finding.
What we do
  • Funding-readiness assessment across narrative, data, and budget
  • Opportunity qualification workflow with scoring criteria
  • Pursuit tracking structure and calendar
  • Team training on verification and review
Deliverables
  • Funding-readiness assessment
  • Qualification workflow
  • Pursuit tracker
  • Team training session
Outcomes we measure
  • Time from opportunity found to qualified decision, measured
  • Higher share of submissions backed by verified evidence
  • A repeatable review step before anything is sent
Governance
Source verification, human sign-off, and no automated funding decisions.
Typical timeline
4–6 weeks.
Digital growth

Digital growth and commerce implementation

Built for
Purpose-driven brands with a funded growth need
The problem
Content effort is constant, but there is no system behind it and no way to report what worked.
Scope of work
A digital-growth assessment, AI-enabled content workflows, and a bounded implementation pilot.
What we do
  • Audience, channel, and offer review
  • Content workflow design with brand guardrails
  • Campaign plan and production cadence
  • 30–60–90–120+ day roadmap and handoff
Deliverables
  • Audience and channel strategy
  • Content workflow design
  • Campaign plan
  • Phased roadmap
Outcomes we measure
  • Repeatable production capacity owned by the internal team
  • Reportable channel performance against a starting baseline
  • A defined change-control and revision process
Governance
Editorial review and brand guardrails. Full e-commerce management, daily posting, paid-media buying, community management, influencer contracting, photography, and video production are not included unless separately contracted.
Typical timeline
Bounded pilot, typically 8–12 weeks.
Workforce innovation

Human-centered workforce navigation

Built for
Regional workforce ecosystems, employers, and community organizations
The problem
Talent, employers, and service providers operate in disconnected systems that never see each other.
Scope of work
Platform strategy and MVP design for guided navigation, readiness translation, and employer engagement.
What we do
  • Journey design for four audiences
  • Explainable matching design with human determination
  • Data, consent, and correction-rights model
  • Pilot validation plan with partner criteria
Deliverables
  • Platform strategy
  • Four audience journeys
  • Explainable matching design
  • Pilot validation plan
Outcomes we measure
  • Connected pathways with placement and retention signals defined up front
  • Participants able to see and correct what the system holds about them
  • A pilot scope partners can fund and evaluate
Governance
Consent, explainability, human review, participant agency, correction rights, and data controls.
Typical timeline
8–12 weeks for strategy and MVP design.
Education

Youth AI literacy program design

Built for
Schools, districts, and out-of-school-time partners serving grades 3–12
The problem
Students meet AI everywhere and are rarely taught to question it before they use it.
Scope of work
Grade-banded curriculum design for grades 3–5, 6–8, and 9–12 with facilitator and family materials.
What we do
  • Grade-banded session design across eight sessions per track
  • Facilitator guide, student workbook, rubric, and family letter
  • Educator training and delivery support
  • Pre/post measurement design
Deliverables
  • Three grade-track curricula
  • Educator toolkit
  • Facilitator training
  • Measurement instruments
Outcomes we measure
  • Completion and participation tracked per cohort
  • Pre/post growth in AI understanding and critical questioning
  • One completed student project per finishing student
Governance
Age-appropriate data practice, family transparency, and no student data used to train models.
Typical timeline
Program design in 6–8 weeks; pilots run one term.

These are representative scopes, not guarantees of results. Every engagement starts with a paid discovery, and measures are set with you before anything launches.

Start the conversation

Have a problem that looks like one of these?

Start with a scope review. We'll tell you honestly whether it's a fit.

Request a Scope ReviewAsk the AI Service Advisor

Keep exploring