Not every company is ready for AI-powered workflows. Jumping in before you're prepared is how projects fail, budgets evaporate, and "AI" becomes a dirty word in your organization. This checklist helps you assess your readiness–and identify what to fix before investing.
Score yourself honestly on each factor. A green flag earns full points; a red flag earns zero. Your total score predicts your likelihood of success. If you need help, consider working with AI automation services to assess your readiness.
How to Use This Checklist
For each question, give yourself full points if you match the green flag, zero if you match the red flag, and half if you're somewhere in between. Total your score at the end.
Process Readiness
Can you identify 3+ repetitive processes that consume significant staff time?
3 ptsYes, we know exactly which processes are candidates
""We're not sure what to automate""
Are these processes documented with clear inputs, outputs, and rules?
2 ptsDocumented SOPs exist for target processes
""Sarah knows how it works, but nothing is written down""
Do you have baseline metrics for current process performance?
2 ptsWe track time, cost, and error rates
""We don't really measure this""
Data Readiness
Is your data digital and accessible (not paper-based or in silos)?
3 ptsData is in modern systems with APIs or exports
""A lot is still in paper files or locked in legacy systems""
Is your data reasonably clean and consistent?
3 ptsRegular data hygiene, consistent formatting
""Lots of duplicates, missing fields, inconsistent formats""
Do you have at least 6 months of historical data for target processes?
2 ptsHistorical data available for training and validation
""We don't keep much history""
Technical Readiness
Do your core systems have APIs or integration capabilities?
2 ptsModern systems with REST APIs or native integrations
""Our main system is custom-built and has no integrations""
Do you have IT support for integration projects?
2 ptsIT team available or budget for technical support
""IT is completely overwhelmed and won't prioritize this""
Can you provide secure access to necessary systems for automation?
2 ptsWe can create service accounts and provide access
""Security won't allow any external system access""
Organizational Readiness
Do you have executive sponsorship for AI automation initiatives?
3 ptsC-level or VP champion with budget authority
""This is a grassroots/skunkworks effort""
Is there organizational appetite for changing how work gets done?
3 ptsLeadership actively promoting operational efficiency
""Our culture resists change""
Are affected employees aware and at least not hostile to automation?
2 ptsTeams understand AI will handle tedious work, not replace them
""Staff will see this as a threat and resist""
Financial Readiness
Do you have budget allocated for AI/automation initiatives?
2 ptsSpecific budget line item approved
""We'll find money if the ROI looks good""
Can you calculate the true cost of roles you want to automate?
1 ptsFull loaded cost (salary + benefits + overhead) available
""We only know base salaries""
Is there patience for 3-6 month ROI timelines?
2 ptsExpectations aligned with realistic timelines
""We need results in 30 days or it's cancelled""
Scoring Your Results
Add up your points across all 15 questions. Maximum possible score: 34 points.
Ready to Go
You're well-positioned for AI automation success. You have clear processes, clean data, organizational support, and realistic expectations. Start evaluating solutions.
Almost Ready
You have a solid foundation with some gaps. Address your weak areas before major investment. Consider a small pilot project to build organizational confidence and fill gaps.
Foundation Work Needed
Significant gaps exist. Investing in intelligent systems now would likely fail. Focus on process documentation, data cleanup, and building organizational buy-in first.
Not Ready
Major foundational issues need addressing. AI-driven process optimisation would almost certainly fail. This isn't bad news–it's honest news. Build the foundation first, then revisit in 6-12 months.
What to Do If You're Not Ready
A low score isn't a death sentence–it's a roadmap. Here's how to improve each category:
- Low Process Readiness: Document your top 5 manual processes. Time them. Measure errors. Create the baseline you'll need.
- Low Data Readiness: Audit your data quality. Invest in cleanup before automation. Consider a data governance initiative.
- Low Technical Readiness: Evaluate modern alternatives to legacy systems. Talk to IT about integration priorities.
- Low Organizational Readiness: Build the case for AI-powered workflows. Find an executive champion. Start change management early.
- Low Financial Readiness: Calculate true employee costs to build the ROI case. Set realistic timeline expectations.
The Key Insight
Readiness isn't about being perfect–it's about being honest. Companies that acknowledge and address gaps succeed. Companies that ignore gaps and hope for the best fail. This checklist helps you see clearly so you can act wisely.
The Bottom Line
Process optimisation with AI isn't magic–it's implementation. And implementation requires readiness. Use this checklist before every major AI deployment initiative. Share it with stakeholders. Let it guide your investment decisions.
A score of 20+ means you're ready to explore AI solutions. Below 20, invest in foundations first. Either way, you now know where you stand–and that's worth more than wishful thinking.
Want a professional readiness assessment? Our free consultation includes a detailed evaluation of your AI readiness with specific recommendations.