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Free Guide

AI Implementation Risk Playbook

4 critical problems that derail AI projects — and how to fix them before implementation begins.

Problem 01

Data & Integration Chaos

What it looks like Customer data lives in multiple systems — Salesforce, Excel, CRM backups. When teams ask "how many customers do we have?", different sources give different answers. AI systems can't learn effectively from conflicting or duplicated data.

Red Flags

  • Multiple systems have the "same" data in different formats
  • Reconciliation meetings to figure out what's the real number
  • Someone frequently asks "which spreadsheet is the latest?"
  • Data entry happens in multiple places simultaneously
  • Export/import process is manual and error-prone

This Week's Actions

Problem 02

Process Opacity

What it looks like Process ownership is distributed or unclear — sometimes three people can approve the same decision, sometimes one person is the required bottleneck. Processes exist in documentation but don't match current reality. Critical knowledge concentrates with one or two key people rather than being shared across the team.

Red Flags

  • "Ask [person]" is how people learn the process
  • Everything slows when one key person is unavailable
  • Different people do the same task differently
  • Documentation exists but doesn't match what actually happens
  • No one can tell you who owns each critical process

This Week's Actions

Problem 03

Blind Operations

What it looks like Process performance isn't formally tracked — cycle times, error rates, and costs remain estimates rather than measured data. Changes happen based on intuition rather than evidence. When AI is implemented, there's no baseline to measure against, so it's unclear whether it's actually helping.

Red Flags

  • "How long does onboarding take?" gets different answers
  • You can't tell if a process is getting faster or slower
  • Changes happen because someone has an idea, not based on data
  • No baseline to compare before/after AI implementation
  • You feel like improvements are happening but can't prove it

This Week's Actions

Problem 04

Compliance & Risk

What it looks like Approval chains are often informal or verbal rather than documented. Audit trails (who, what, when) aren't systematically recorded. Decision rationale is implicit rather than explicit. When AI automates a process, there's no clear record of how decisions were made, creating compliance and audit challenges.

Red Flags

  • Teams can't easily answer "who approved this and when?"
  • Approval chains are informal or ad-hoc
  • No documentation explaining why a decision was made
  • No timestamp or audit trail on important transactions
  • Compliance requirements are unclear to the team

This Week's Actions

Quick Diagnostic: Rate Yourself

For each statement, rate yourself: 1 = Struggling, 5 = Solid

Data & Integration

Our data has ONE clear source of truth (not scattered)
12345
We can easily combine data across different systems
12345
New employees know where data lives and how to access it
12345

Process Clarity

Every critical process has one clear owner
12345
Processes are documented and match what we actually do
12345
No single person is a bottleneck for critical decisions
12345
Knowledge isn't siloed (anyone can execute critical processes)
12345

Measurement

We track metrics for critical processes (cycle time, error rate, cost)
12345
Process changes are deliberate, measured, and improve performance
12345
We can measure before/after impact of changes
12345

Compliance & Risk

We understand what compliance requirements apply to us
12345
Approval chains are documented and enforced
12345
We have audit trails (who, what, when) for critical decisions
12345

Your Action Plan

1–2

Critical blocker. Fix this before AI implementation. This is where your project will fail if you don't address it now.

2–3

Important gap. Prioritize this in the next 2–4 weeks. It won't stop you immediately, but it will slow you down.

4–5

You're solid here. Maintain it. This is a foundation you can build on.

This Week: Pick your lowest-scoring category. Pick ONE action from that section. Complete it by Friday. Next week, pick the next one.

Before AI Implementation: Make sure all categories are 3+ (ideally 4+). AI will magnify problems, not solve them.

Which Problem Resonates Most?

Let's discuss your specific gaps and build a roadmap to fix them — starting with what will have the biggest impact on your AI readiness.

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