Look beyond the AI hype and uncover the repetitive, frustrating, or time-consuming work inside your business where AI could actually make a difference.

Evaluate potential projects based on business value, frequency, repeatability, available information, human oversight, measurability, and risk so you can focus on an idea that matters without biting off too much.

Define what AI should and shouldn’t do, decide how you’ll measure success, and create a small pilot that gives you something concrete to learn from before you expand.

Find out which tools employees are using, where sensitive data may be exposed, and how dependent the team already is on AI.

Guide clients through accountability, data sensitivity, risk tolerance, and the hidden cost of trusting AI without governance.

Identify where AI can reduce cost, add capacity, improve margins, or accelerate a workflow that actually changes how the business runs.

Use practical prompts to uncover where clients are losing time, repeating work, struggling with visibility, or relying too much on manual processes.

Get structured questions for sales calls, QBRs, leadership conversations, governance discussions, and internal MSP alignment.

Prioritize use cases by time savings, revenue impact, risk reduction, employee impact, and ease of implementation so AI becomes a practical business conversation, not just another shiny tool.

Use this worksheet to identify where AI is being used across departments, including shadow usage leadership may not see.

Guide clients through the critical questions around AI policies, sensitive data, and acceptable use so you can surface gaps before they become security or compliance issues.

Walk away from the conversation with clear next steps, from AI discovery workshops to policy creation, training, and controlled pilot implementations.

Learn how to move client conversations beyond “Is AI risky?” to “How do we govern and leverage it responsibly?”

Identify unmanaged AI usage, permission gaps, and data risks before they turn into compliance, security, or reputation problems.

Follow a clear 4-step model to secure identity, clean data, establish guardrails, and pilot high-value AI use cases with measurable ROI.

This worksheet shows you how to turn roadmap, risk, and business alignment conversations into a repeatable service clients understand and pay for.

Segment your clients, choose the right advisory model per tier, and apply clear pricing paths so you’re no longer giving away strategy to the loudest accounts.

Use a standardized meeting framework, risk snapshot, and delivery pillars so advisory doesn’t depend on one person and scales across your entire client base.

Use the built-in ICP Canvas to document firmographics, tech stacks, compliance regimes, and buying roles. Get clarity on who your “perfect fit” customers are.

Identify clients, conditions, and behaviors that break profitability or outcomes. Learn when to say “No” — and when a conditional “Yes” makes sense.

Guided prompts and scorecard templates help you translate pain points into measurable business results, craft outcome-based offers, and track success with exec-level KPIs.

Evaluate clients using simple P (Profit) and F (Fit) scores based on MRR, hours, endpoints, and alignment with your stack.

Clearly identify next steps for each client: Expand, Maintain, Reprice & Standardize, or Offboard/Partner.

Follow the built-in scoring guide for margin, load, rate, payment reliability, and standardization willingness.

Kill, Keep, Deepen, or Partner-Out services to free up margin and focus on what drives results.

Clarify your ideal customer profile, from industry and company size to top pains and desired outcomes.

Take the guesswork out of where to focus your MSP’s time, talent, and resources.