Transformation & AI Readiness Assessment

1. Business Memory (Data)

How is your core business information (sales, notes, customers) stored?

Mostly paper or unorganized files Digital, but scattered across different apps or computers Organized in a centralized database / cloud system

AI and automation depend on consistent inputs. Messy data leads to unreliable results.

Do you have a single source of truth for customers, products, and services?

No — duplicates are common Some consistency, but not enforced Yes — standardized and enforced

Standard definitions are what make reporting, dashboards, and automation stable.

Can your current tools (Accounting, CRM, ERP) talk to each other automatically?

No — old desktop-only software Some can, but we usually move data manually Yes — modern tools connected via integrations/APIs

How do you access your business tools?

Only installed on office computers A mix of installed tools and web-based tools 100% web-based (SaaS)

Cloud tools are easier to integrate, automate, and govern than desktop-only systems.

Are pricing, customer updates, and key records synchronized across systems?

Multiple places — often missed Sometimes centralized, sometimes not One place — single source of truth

Are core processes documented so staff run them consistently?

No documentation — tribal knowledge Some notes, but not consistently used Yes — documented and followed

You can’t automate chaos. Standard workflows come before automation.

How often do errors happen due to manual copy/pasting or handoffs?

Often Sometimes Rarely

Is there a repetitive task wasting 5+ hours of staff time per week?

No specific task identified Ideas exist, but we haven’t timed them Yes — clear targets for automation

How fast can you get reliable numbers for basic KPIs?

Days — requires manual work A few hours — partial automation Minutes — automated and trusted

If reporting isn’t trusted, AI adds noise. Visibility comes before intelligence.

Are you exploring Canadian innovation support (SR&ED, IRAP, Mitacs) for technical work?

No / never looked into it Aware, but unsure if we qualify Yes — actively exploring eligibility

Can you explain why an automated system makes a decision?

No — it would be a black box Some oversight, but limited explanation Yes — transparency and auditability matter

Do you have a formal AI safety policy for staff use of public AI tools?

No — staff use AI tools freely Informal guidance / occasionally monitored Yes — clear policy and safe usage rules

Policies protect your data and reduce risk while you modernize.