Assessment Progress
Question 1 of 10
01 / 10
Current AI Usage
How is your organization currently using AI tools?
A
We haven't started. AI is on the radar but nothing is in use yet.
B
A few individuals use general tools like ChatGPT occasionally, but it's informal and inconsistent.
C
We have some AI tools adopted across the team with clear use cases, though not fully integrated into our workflows.
D
AI is embedded in multiple workflows. We measure its impact and actively look for new applications.
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02 / 10
Current AI Usage
How would you describe leadership's view on AI adoption?
A
Skeptical or unaware - AI hasn't come up in any serious strategic conversation.
B
Curious but cautious - leadership sees value but is unsure where to start or what to trust.
C
Supportive - leadership has approved exploration and expects AI to play a role in the organization's future.
D
Committed - AI is part of the strategic roadmap with budget, ownership, and accountability assigned.
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03 / 10
Manual Process Pain Points
How significant are your manual, repetitive processes in terms of time cost?
A
We haven't mapped our processes in enough detail to know where time is being lost.
B
We know manual work is a problem but haven't quantified it. It feels like a lot, but we can't be specific.
C
We've identified specific repetitive tasks that consume significant team hours weekly and are eager to address them.
D
We have a documented list of high-cost manual processes with time estimates and have already prioritized them for automation.
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04 / 10
Manual Process Pain Points
Which of the following best describes your biggest operational bottleneck?
A
We don't have a clearly defined bottleneck - things are generally slow everywhere.
B
Reporting and data consolidation - pulling information together from different sources takes too long.
C
Communication and content - drafting, reviewing, and sending communications consumes disproportionate time.
D
Decision-making - we have the data, but turning it into actionable decisions is slow and inconsistent.
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05 / 10
Team Readiness
How would you characterize your team's current attitude toward AI?
A
Resistant or apprehensive - there's real concern about job security or distrust of the technology.
B
Passive - the team will use what they're told to, but there's no organic interest or self-directed exploration.
C
Curious - a meaningful portion of the team is actively experimenting with AI tools on their own.
D
Proactive - team members actively champion AI tools, share learnings, and push for broader adoption.
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06 / 10
Team Readiness
Does your organization have a designated person or team responsible for AI and technology adoption?
A
No - it falls to whoever has time, which means it rarely happens.
B
Informally - there's someone who tends to lead these efforts but it's not an official role.
C
Yes - we have an IT lead or operations manager who owns technology decisions including AI.
D
Yes - we have a dedicated role or team (e.g., CDO, AI task force) focused specifically on AI strategy and implementation.
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07 / 10
Data Readiness
How would you describe the state of your organization's data?
A
Scattered - data lives in emails, spreadsheets, and individual files with no central structure.
B
Partially organized - we have systems in place (CRM, ERP, etc.) but data quality and consistency is inconsistent.
C
Well organized - data is centralized, reasonably clean, and accessible to the right people when needed.
D
Strong foundation - we have structured data pipelines, defined quality standards, and regular governance reviews.
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08 / 10
Data Readiness
How comfortable is your organization with sharing internal data with AI systems for analysis or automation?
A
Not comfortable - data privacy and security concerns are significant blockers, with no clear policy in place.
B
Cautious - we'd consider it for non-sensitive data but need to understand risks better before committing.
C
Comfortable with guardrails - we have policies that define what data can be used and have reviewed leading AI vendors' security posture.
D
Ready - we have enterprise agreements, data classification frameworks, and AI usage policies already in place.
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09 / 10
Budget & Timeline
What budget range is your organization prepared to invest in an initial AI initiative?
A
No budget allocated - we'd need to prove value first before any financial commitment.
B
Small budget - enough for tool subscriptions and a few days of advisory support to explore options.
C
Moderate budget - sufficient for a focused pilot project with external support to implement and measure results.
D
Dedicated budget - a meaningful line item approved for AI implementation, with room to scale based on outcomes.
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10 / 10
Budget & Timeline
What is your expected timeline for seeing meaningful results from an AI initiative?
A
We haven't defined a timeline - we're still in early exploration mode.
B
12+ months - we understand transformation takes time and are planning for a longer horizon.
C
6-12 months - we want a structured pilot with measurable outcomes within the year.
D
Under 6 months - we have a specific, defined problem and want to see working results quickly.
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