Applied Enterprise AI & ML Best Practices
Applied AI and ML create impact when teams focus on the right problems, work through a clear delivery lifecycle, and align roles across functions.
Leave with an applied AI/ML blueprint—use case targets, lifecycle approach, and a cross-functional plan.
Many organizations want more AI impact, but struggle to turn interest into consistent execution.
- Problem selection is unclear: Teams chase “AI ideas” instead of prioritizing business problems where AI/ML is.
- Delivery expectations vary: Without a shared lifecycle and success criteria, efforts stall, restart, or miss.
Roles aren’t aligned across functions: Business, analytics, and technology teams lack clear ownership, slowing decisions and delivery.
Without a practical operating approach, AI/ML becomes a series of disconnected projects
We guide your team through a business-first approach to plan applied AI/ML work with clear targets, roles.
- Enterprise Framing for Applied AI/ML: Establish how AI/ML supports innovation goals and where it should (and shouldn’t).
- Business Problem Identification and Fit: Define criteria to select problems suited for AI/ML and prioritize near-term opportunities.
- AI/ML Lifecycle and Success Criteria: Align on lifecycle stages, decision gates, and what “success” looks like.
- Roles, Skillsets, and Collaboration Model: Clarify cross-functional responsibilities and the skills required to deliver effectively.
- Initiative Planning Workshop Output: Produce a practical plan for initial initiatives, including scope, owners, risks.
- Framing Applied AI & ML in Enterprise Innovation
- Identifying Business Problems Suited for AI & ML
- Outlining the AI/ML Project Lifecycle and Success Criteria
- Reviewing Roles and Skillsets in Applied AI & ML
- Planning Applied AI Initiatives in Cross-Functional Teams
- Establish a shared view of how applied AI/ML creates value in your.
- Identify and prioritize business problems that are well-suited for AI/ML approaches.
- Align on an end-to-end lifecycle and success criteria that reduce ambiguity.
- Clarify the roles and skillsets needed across business, analytics, and technology teams.
- Leave with a practical plan for next-step applied AI initiatives and ownership.
Who Should Attend:
Solution Essentials
Facilitated working session
2 hours
Beginner to Intermediate
Slides, workshop templates, key worksheets, checklists, and collaboration tools.