Pilot Readiness Assessment

SECTION 1 · AI CURRENTLY IN USE

Which AI tools are currently deployed in your organization? *

ChatGPT / OpenAI API Claude / Anthropic API Microsoft Copilot Google Gemini / Workspace AI Self-hosted model (Llama, Mistral) Custom agents / workflows Vertical SaaS with AI features Other

How long has AI been in production use at your organization? *

Less than 3 months 3–6 months 6–12 months 1–2 years More than 2 years

What are the primary use cases AI is serving today? *

SECTION 2 · TRAINING & ADOPTION

Has staff received formal training on the AI tools in use? *

No formal training — staff figure it out on their own Ad-hoc onboarding — a few sessions, no structured curriculum Role-based training — specific curriculum per role Ongoing program — regular updates, certifications, internal champions

Roughly what percentage of staff actively uses AI in their daily work? *

Is there a designated AI lead, team, or champion in your organization? *

No — nobody owns it Informal — someone cares about it but it’s not their job Part-time — part of someone’s role Dedicated role or team

SECTION 3 · TECH INTEGRATION

How integrated is AI with your core business systems (CRM, ERP, helpdesk, etc.)? *

Not integrated — AI runs in separate apps, no data flow Manual copy-paste — humans bridge the two Partial API integration — some read-only data flows Deeply integrated — AI reads and writes across core systems

Where does your AI run? *

Cloud APIs only (ChatGPT, Claude, etc.) Self-hosted models only On-prem only (behind corporate firewall) Mix of the above Not sure

Who manages your AI tech stack day-to-day? *

SECTION 4 · MONITORING & AUDIT

Are AI actions logged for audit or review? *

No — we don’t know what the AI did yesterday Partial — some tools log, some don’t Full logging, no review — logs exist but nobody reads them Full logging and regular review

Is there a human approval gate for high-stakes AI decisions (money, commitments, external messages)? *

No — AI acts autonomously Informal — staff review when they notice Some workflows are gated, others are not Every high-stakes action requires human approval

When AI makes a mistake or produces a bad output, what happens? *

SECTION 5 · GOVERNANCE

Do you have a written AI usage policy? *

No written policy Verbal guidelines only Draft policy — not formally rolled out Formal policy — staff have signed/acknowledged

What compliance frameworks apply to your AI use? *

Do you know where your data goes when staff use AI tools? *

Not sure — haven’t checked Partial visibility — know some tools, not all Full visibility — documented per tool

SECTION 6 · GAPS & CONCERNS

What concerns you most about your current AI deployment? *

Where do you feel the biggest gaps are? *

Training — staff skills Tech — integration with systems Monitoring — knowing what AI is doing Governance — policies and oversight Compliance — regulatory alignment Cost — spend controls Scale — rolling AI beyond pilots Vendor lock-in

If you could fix one thing about your AI operations tomorrow, what would it be? *

Pilot Readiness Assessment

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