AI Advisory

Illustrative AI Advisory Sprint example

A regional B2B distributor with a high-volume customer-inquiry workflow

Discuss an AI Advisory Sprint View all illustrative scenarios
1. The business problem

A fragmented inquiry-to-response workflow

A regional distributor with approximately 90 employees receives hundreds of recurring customer inquiries about order status, product availability, product specifications, substitute products, quotes, shipping, and returns.

Employees manually search an ERP, supplier documents, shared drives, email history, and internal knowledge before responding. The fragmented process creates repetitive employee effort, inconsistent response times, and dependency on experienced staff who know where reliable information lives.

Leadership wants to understand whether AI can reduce repetitive work without creating pricing errors, exposing customer information, sending unsupported responses, or automating decisions that should remain under human control.

2. What RayAI would examine

The workflow, decision, boundaries, and readiness

  • Current inquiry-to-response workflow
  • Business objective and desired decision
  • Representative inquiries and process materials
  • Existing systems and information sources
  • Candidate AI and automation opportunities
  • Data sensitivity and access requirements
  • Reliability and human-approval boundaries
  • Implementation readiness
  • Build-vs-buy-vs-partner options
3. Three illustrative use cases

An example prioritization

These recommendations are illustrative judgments, not claimed client results.

Internal inquiry classification and employee-reviewed response drafting

Classify requests, retrieve approved information, and prepare drafts for employee review.

Pilot first

Internal product and policy knowledge assistant

Help employees find approved product, shipping, returns, and policy information.

Include in the pilot or Phase 1B

Automated quote preparation and autonomous customer sending

Prepare final quotes or send customer responses without employee approval.

Defer
4. Illustrative executive recommendation

Proceed with a bounded internal pilot

Pilot inquiry classification, approved-information retrieval, and employee-reviewed response drafting. Do not initially automate final quote generation or deploy a public customer chatbot.

5. Why this recommendation

A lower-risk path to operational learning

The first use case combines high repetitive-work volume, a clear human approval point, measurable operational value, and lower risk than autonomous customer communication.

Automated quoting should be deferred because pricing, exceptions, data quality, ERP dependencies, and approval rules require further control and validation.

6. Trust-first operating boundaries

Human control and approved information remain central

  • No outbound response without employee approval during the pilot.
  • No AI authority to make final pricing commitments.
  • Responses grounded only in approved sources.
  • Existing access controls continue to apply.
  • Sensitive data is minimized.
  • Unsupported or conflicting answers escalate to a person.
  • Drafts, approvals, corrections, and source use are logged where appropriate.
  • Client ownership of approved content, access rules, and pilot decisions is explicit.
7. Illustrative implementation-readiness findings

A compact illustrative readiness summary

These are illustrative findings for this scenario, not findings from an actual client.

Business ownership
Ready
Workflow clarity
Ready
Approved knowledge sources
Needs work
ERP integration
Requires validation
Data sensitivity
Requires controls
Autonomous quoting
Not ready
8. Illustrative 30/60/90-day roadmap

A controlled path from preparation to decision

The 30/60/90-day path is an illustrative roadmap the Sprint could recommend. It is not a promise that RayAI will implement the roadmap or achieve results within 90 days.

Days 0–30

  • Confirm sponsor and workflow owner
  • Establish baseline measures
  • Select approved information sources
  • Clarify access and human-approval rules
  • Validate integration options

Days 31–60

  • Configure or develop a bounded internal assistant
  • Test against representative inquiries
  • Evaluate factual corrections and unsupported answers
  • Train a limited pilot group
  • Refine workflow and escalation rules

Days 61–90

  • Conduct a controlled employee pilot
  • Require human approval
  • Measure handling time, corrections, escalations, and adoption
  • Decide whether to expand, revise, pause, or stop
9. What the standard Sprint does not include

Clear scope boundaries

The standard Advisory Sprint creates practical clarity for responsible next decisions. It does not guarantee implementation or outcomes.

  • Prototype development
  • Production software implementation
  • Detailed technical architecture
  • Formal legal, security, compliance, financial, or medical advice
  • Production-system integration
  • Implementation project management
  • Multi-department enterprise AI strategy
  • Guaranteed ROI or implementation outcomes