Let’s be honest: most “AI for business” advice is either too high-level or too technical to be helpful. During the development of our AI for Process course, I spoke with dozens of BPMInstitute.org members — analysts, architects, and process leads — who were already experimenting with GenAI. Some were just starting, some were going deep, but all were trying to make it useful in the context of everyday process work.
These 10 techniques rose to the top. If you’re just getting started, use this list as a launch pad. Each of these tips reflects real lessons, real utility — and a clear path to working smarter starting tomorrow.
- Jumpstart Process Discovery
Early-stage discovery always takes longer than expected. Between scattered documentation, vague job descriptions, and outdated SOPs, the starting line is never as clear as you’d like.
You can use GenAI tools to organize this mess. Drop in notes, transcripts, or even snippets from a kickoff deck, and ask the AI to identify likely steps, actors, and decisions. This will help you frame an initial hypothesis you can validate — instead of starting from scratch.
- Analyze Feedback and Exceptions
Exception logs, support tickets, and escalation emails hold valuable insight — but few teams have time to comb through them manually.
This is where AI can save you hours. Export comments, copy content from a spreadsheet or shared doc, and prompt the AI to group the issues into patterns or themes. This will help you identify where your process is actually breaking down — so you can improve based on reality, not assumptions.
- Identify Friction in Human Decisions
Not all delays are task-based. Many live in gray areas where humans are forced to interpret rules inconsistently — like approvals, risk checks, or handoffs between roles.
If you collect a few examples (from forms, approvals, case notes), you can ask AI to help you spot ambiguity, missing criteria, or steps that rely too heavily on tribal knowledge. This will help you design smarter workflows that reduce confusion and decision fatigue.
- Draft Process Documentation
Whether you’re starting fresh or updating outdated SOPs, AI can speed things up.
Start by listing your key steps, responsible roles, and known variations. Prompt the AI to write a first draft in clear, procedural language. This will help you generate documentation that’s 70% done — and gives you a clean baseline to edit for accuracy and tone.
- Prep for Stakeholder Meetings
AI can help you communicate process changes more clearly and confidently.
Before your next meeting, feed it background material and ask it to summarize key points, draft a talking script, or even generate a slide outline. Even better — ask it to list common stakeholder objections or confusion points. This will help you anticipate tough questions and show up better prepared.
- Automate Repetitive Tasks
You don’t need a BPMS or RPA solution to reduce friction in your day. GenAI can handle plenty of microtasks with the right prompt.
This will help you:
- Convert messy notes into clean follow-up emails
- Reformat SOPs into checklists for frontline use
- Generate stakeholder summaries from meeting notes
- Review intake forms for missing information
- Rewrite dense documentation for readability
- Extract action items from planning docs
- Summarize survey comments into key takeaways
- Draft compliance checklists from policy language
- Turn task bullets into project templates
- Create job aids from standard workflows
These aren’t demos — they’re real ways process pros are reclaiming time.
- Compare Process Variants
When proposing improvements, it’s helpful to show options. Most teams said they’ve used GenAI to explore alternate flows before a stakeholder meeting.
You can describe your current state and ask AI to generate variations: leaner, lower-risk, customer-centric, or more scalable versions. This will help you spark ideas, explore alternatives, and support your change narrative with credible options.
- Accelerate Process Modeling
When faced with a blank modeling canvas, AI can help you build your initial scaffolding.
Paste in job descriptions, vendor SLAs, or informal process writeups and ask AI to organize steps and responsibilities. This will help you outline swimlanes, task sequences, or RACI roles — which you can then import or replicate in your preferred modeling tool.
It’s not final, but it gets you to version one much faster.
- Create a Process Change Summary
Once a process redesign is complete, communicating it well is half the battle. AI can help you explain the change clearly — in less time.
Feed it a list of before-and-after steps, and ask for:
- A summary email to impacted users
- A briefing for execs or sponsors
- A bulleted list of key differences
- Suggested FAQs for rollout support
This will help you maintain consistency across channels — and reduce the rewriting cycle.
- Build a Reusable Prompt Library
Experienced process professionals aren’t writing new prompts every time. They’re saving what works.
Most told me they keep a simple Word doc, Google Doc, or pinned Notion page. When they land on a prompt that generates useful output — a good stakeholder message, a clean checklist, a training outline — they save it for reuse.
This will help you get faster and more consistent with every project. You can even create categories: discovery, documentation, comms, prep, and more.
Final Thoughts
These aren’t experiments anymore. They’re real ways professionals like you are using AI today — without a platform migration, IT dependency, or steep learning curve.
You don’t need permission. You don’t need code. You just need one practical use case to start.
And when you do? You’ll start saving time, working smarter, and bringing more value to your process work — just like the members who shared these ideas.
By applying even a few of these techniques, you could reclaim 4–8 hours a week — time that can be redirected toward higher-value analysis, collaboration, and process improvement.
