Do you have documented, step-by-step procedures for your three most time-consuming processes?

Not in people's heads. Actually written down, specific enough that someone could follow them.

Are your key business processes repeating on a predictable schedule?

Daily data exports, weekly reports, monthly reconciliation. Automated systems thrive on rhythm, not randomness.

Do you have centralized repositories for your business data?

CRM, ERP, spreadsheets in a shared drive. Not scattered across email, notebooks, and personal devices.

Can you identify the top five time-wasters for your operations or administrative team?

Hours spent on data entry, manual report generation, copy-paste between systems. The bigger the pain point, the higher the automation ROI.

Do you have basic integrations between your core systems?

At minimum: your primary business platform talking to one other tool. APIs, Zapier, simple connectors. Doesn't have to be sophisticated.

Has your leadership team defined specific outcomes they want automation to achieve?

Reduce errors by X%, free up Y hours per month, cut cycle time from A to B. Not "make things faster" but measurable targets.

Do you have a person or team responsible for process improvement and testing?

Even part-time, someone owns "how we work better". Not just "how we work."

Can you capture and measure a current baseline for your most critical manual processes?

How long does the process take now? How many errors occur? What does it cost? You can't improve what you don't measure.

Are your employees willing to learn new software if it saves them work?

Adoption is a people problem, not a tech problem. Honest assessment: would your team embrace better tools?

Do you have budget allocated for operational improvement this year?

Not necessarily large, but real. Companies that improve usually dedicate resources intentionally.

Do you have a documented policy on which AI tools employees can and cannot use?

Not "use AI responsibly" but specific: ChatGPT yes/no, Claude yes/no, data-sharing restrictions documented.

Have you audited or identified which AI tools your employees are actively using?

Honest answer: you probably don't know. Can you name them? Browser extensions, cloud apps, mobile tools?

Do you have a process for employees to request new tools before using them?

Or do people just download things and start using them?

Are your most sensitive business documents protected from accidental upload to cloud AI?

Encryption, access controls, user training. Not all of it, but your crown jewels.

Do you have a data retention and deletion policy?

How long is customer data stored? Who can access it? What happens when someone leaves the company?

Have you trained your team on what data is safe to share with AI tools?

Not "never share anything" but nuanced: Which fields? Which tools? What's the rule?

Do you have a backup and disaster recovery plan?

Can you restore critical data if something goes wrong? Tested recently?

Are your user access controls based on role, not seniority?

Everyone with a login can see everything, or do people only see what they need?

Do you have a record of who accessed what data and when?

Audit trails are table stakes for serious operations.

Has your insurance broker reviewed your AI tool usage?

They probably haven't. And they need to, because vendor policies don't cover liability the way you'd expect.

Do you have a single source of truth for your customer data?

Not three systems with conflicting information. One system where customer info is accurate and current.

Can you answer these questions about your business in under 5 minutes?

Top 10 customers by revenue last month. Average order value. Churn rate. If you can't, your data is fragmented.

Are your most important business metrics calculated consistently?

Same definition of "revenue" or "customer" across your company, not debated each time.

Do you collect data on process performance and business outcomes?

Not just accounting data. What does it take to close a sale? How long is delivery taking? Where do orders fail?

Can non-technical team members run reports or pull data without IT help?

Self-service analytics separates mature operations from bottlenecked ones.

Do you have historical data going back at least 12 months?

Trends and seasonality matter. One month of data tells you almost nothing.

Is your data clean enough to trust for decision-making?

Duplicate records? Spelling inconsistencies? Outdated entries? Know your data quality baseline.

Do you have a data steward or analyst who owns data quality and integrity?

Not necessarily full-time, but someone responsible for keeping it accurate.

Have you identified 3-5 key business questions you want AI to help answer?

Not vague: specific, measurable questions your leadership actually needs answered.

Are you currently using any analytics tools to monitor business performance?

Dashboards, reports, even simple spreadsheets with KPIs. Just the baseline of structured insight.