Listed below are ways to use AI for the opening phase of improving a process – when you're working to get a deep understanding of the current situation.

Enlist AI's help to uncover stakeholder needs and pain points. Provide AI with survey feedback, notes from input sesssions, and emails – then use the following prompts.

Prompts:

• Analyze these comments and summarize the top five themes or concerns.

• Identify the most frequently mentioned stakeholder pain points in this input.

• Group this feedback into categories and suggest a label for each group.

• Identify sentiment trends in these responses, and flag responses showing serious urgent concerns.

Describe the process and project goals to AI, and ask for several current-state process measures worth gathering for analysis.

Prompts:

• Here’s a description of our current process and improvement goals. What metrics should we track?

• What 3–5 meaningful measures would best assess this process’s effectiveness?

• Based on this process description, what are good leading indicators of performance?

• Suggest performance metrics tied to reducing errors and improving start-to-finish process time.

Upload the current-state process map, and/or the gathered measures, and prompt AI to identify where the biggest occurrences of process waste are likely happening (e.g., rework, loopbacks, delays, etc.).

Prompts:

• Review this process map and identify where waste (e.g., delays, rework, handoffs) is likely occurring.

• Here’s a list of process steps. Which contribute most to inefficiency?

• Given these time and volume metrics, where should we look first for performance gaps?

• Based on these descriptions, what types of waste may exist in this process?

AI can provide substantial help when you're working to generate, evaluate, and select the highest-impact improvement actions.

Tell AI the project goals along with key findings from the discovery phase. Then ask it to brainstorm immediate, short-term, and long-term improvements based on your discoveries.

Prompts:

• Given these issues, what are some short-term improvements we could implement quickly?

• Given these issues, suggest five creative ways to significantly improve this process within a year.

• What low-cost solutions might address the delays we are seeing here?

• Suggest innovative process changes that align with our goals of [insert project goals].

Conduct an AI-powered search to see how other institutions approach the process.

Prompts:

• How are other higher-ed institutions handling [name of process], and which practices stand out?

• Summarize approaches peer institutions use to manage [name of process or specific task].

• What are common strategies in higher education for improving this type of process?

• Provide specific examples of how other organizations have improved this process.

Feed improvement ideas into AI, and ask it to categorize by impact and effort.

Prompts:

• Categorize our ideas by high/low impact and high/low effort.

• Create a 2x2 impact-effort grid from these improvement ideas.

• Rank these ideas by how much time they would save if implemented.

• Which ideas are quick wins vs. longer-term investments?

Use AI to describe the improved process steps based on selected actions. The output can serve as a draft (or as general input) when creating a future-state map.

Prompts:

• Describe the ideal future-state process once these improvements are implemented.

• Based on these selected actions, outline the improved steps of the process.

• Generate a draft future-state map starting from the current pain points.

• What would this process look like with all process waste removed?

In this phase, you develop a plan that spells out key aspects of implementation.

Enter the selected improvement actions, and prompt AI to list all of the tasks likely needed for development and implementation.

Prompts:

• What are the key steps required to implement these improvement ideas?

• Create a task list for developing and rolling out this new process.

• For each improvement idea, list the key activities needed to implement it.

• Assign roles and responsibilities for each task in this improvement plan.

Ask AI to build an implementation timeline showing who does what and when.

Prompts:

• Develop an x-week implementation timeline from these tasks. (Set x to match the target duration.)

• Create a draft schedule with milestones for rolling out these process changes.

• Generate a simple Gantt-style timeline with key tasks and dependencies.

Prompt AI to identify potential barriers to your plan – and to suggest adjustments.

Prompts:

• What resistance might we face when implementing this plan, and how can we address it?

• Suggest 3-5 communication tactics to help staff adopt these changes.

• What are common change management pitfalls, and how can we avoid them?

• How can we best prepare stakeholders for a successful process rollout?

Even when the improvement project has been completed and the action plan is being implemented, AI can help – by suggesting key points for periodic progress checks.

Use AI to prepare questions or focus areas for 30/60/90-day check-ins.

Prompts:

• Suggest key questions to ask during a 30-day progress review of this improvement effort.

• At a 60-day check-in, what should we look for to ensure implementation is on track?

• Create a discussion guide for a 90-day review focused on results and next steps.

• How can we evaluate whether this change is having the intended effect?