FREE DOWNLOAD · 01 / 01

Is your business actually ready for AI?

15 questions. 10 minutes. A clear, honest answer — before you commit six figures to a solution that was never going to work. Built for mid-market leaders who want substance, not hype.

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Format 9-page PDF
Length 15 questions
Time 10 minutes
Cost $0
Built by engineers from
01 · WHAT'S INSIDE

Five dimensions. Fifteen questions. Zero fluff.

Most AI readiness frameworks are written by vendors who want you to fail the assessment and call their sales team. This one isn't. Score yourself honestly across the five dimensions that actually predict AI project outcomes.

01

Business & Strategy

  • Is there a measurable business outcome, or a vague "adopt AI" mandate?
  • Have you committed to a realistic timeline and budget range?
  • Can you measure ROI — with baselines captured before anything ships?
02

Data & Infrastructure

  • Can your engineers actually access and query operational data in a week?
  • Is sensitive and regulated data classified and governed?
  • Do you have (or can you build) a pipeline to an AI-accessible layer?
03

Team & Skills

  • Do you have an internal critic who can see through AI vendor marketing?
  • Does engineering have the capacity to go beyond POCs into production?
  • Does leadership understand LLM vs. classical ML vs. automation?
04

Processes & Workflows

  • Are your top 5 revenue-impacting workflows documented end-to-end?
  • Can you identify bottlenecks with numbers, not anecdotes?
  • Does every candidate workflow have a named, empowered owner?
05

Risk & Governance

  • Can your security policy extend to AI systems and third-party APIs?
  • Do you understand your regulatory exposure — before you ship?
  • Does vendor review cover AI-specific risks and exit clauses?
→

Then you get a tier and a plan.

  • A total score mapped to four readiness tiers
  • Category-level warnings that override a strong total
  • A recommended next step you can actually execute
02 · WHY THIS ONE

Written by people who ship AI systems, not sell them.

No vendor.

We don't sell AI tools.

We're an engineering consultancy. We have no pipeline of vendor commissions to protect. The questions reflect what actually causes AI projects to succeed or fail in mid-market environments.

Mid-
market.

Not written for FAANG.

Most AI frameworks assume you have a data engineering org, a CISO, and a budget of $20M. This one assumes you have a CTO, a handful of engineers, and a finance leader who wants ROI in writing.

Honest.

It will tell you "not yet."

Roughly half of mid-market companies score below the readiness threshold. If that's you, the checklist will say so — and tell you what to fix first. A real "no" saves more money than a false "yes."

03 · WHO BUILT IT

IT-PACKS LLC

A software engineering and AI integration consultancy led by engineers with 13+ years of enterprise delivery experience — across telecom BSS/OSS, financial platforms, legacy modernisation, and multi-agent systems.

We've shipped production systems at Netcracker Technology, Luxoft, DXC Technology, and Millennium Technology. We're SAFe-certified and specialise in the gap between AI hype and measurable business outcomes — particularly for regulated mid-market companies.

13+
Years enterprise delivery
4
Tier-1 clients shipped
5
Regulated industries
$0
Vendor commissions
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04 · QUESTIONS

A few things you're probably wondering.

Is this really free?
Yes. It's a lead magnet — we send it in exchange for your email, and we may contact you once or twice more with relevant material. If you unsubscribe, we remove you. No paywall, no upsell inside the PDF.
Who is this checklist for?
Mid-market leaders — typically CTOs, VPs of Engineering, Heads of Operations, and CEOs at companies between $5M and $500M in revenue — evaluating whether to invest in AI. It's especially useful if you're about to hire a consultancy or buy a platform and want a sanity check first.
How long will it take me to complete?
About 10–15 minutes if you work through it alone. We actually recommend doing it twice — once alone, then with two or three peers. Disagreements across your leadership team reveal more than agreement does.
What do I do with a low score?
A low score is a feature, not a failure. It tells you which foundations to fix before spending money on AI. The checklist includes tier-specific recommendations for what to prioritise next. And yes — if you want help, you can book a Discovery Session.
Is the checklist biased toward selling me something?
We're an engineering consultancy, not a software vendor, so we have no product to sell you. About half of respondents will score in a range where our recommendation is "fix your foundations first" — which explicitly is not "hire us."
What languages is it available in?
English only for now. If there's enough demand, we'll release Spanish and Russian versions. Tell us via the form or email info@it-packs.org.