Why 61% of CEOs Are Burning Cash on "Weak AI"

The Hard Truth: You are trying to "Procure" AI instead of "Invest" in it.

Most CEOs treat AI like software procurement—buying a tool and expecting efficiency. But AI is labor.

You don't "procure" a new VP of Sales; you invest in them.

You give them a salary (budget) and access to the CRM (data).

If you hired a VP of Sales and locked them out of the building, you wouldn't blame them for zero revenue. You'd blame the infrastructure.

The Missing Step That Is Killing Your AI ROI

Most of you are placing bets on "Use Cases" before you have audited your Data Readiness. You are paying for high-IQ digital labor, then forcing it to stare at a blank wall.

To fix this, you need to audit your business for Legibility vs. Eligibility.

1. Legibility (The Structure)

Can the machine understand the logic?

The Trap: You have "unstructured sludge"—messy text files, loose notes, or audio recordings.

The Fix: You don't just feed this to a model. While it can read this data, you must structure it to use this data. You need to map the logic of your business so the AI can reason with it, not just summarize it.

2. Eligibility (The Access)

Can the machine touch the source?

The Trap: Your data is "clean," but it lives in a static PDF report or a dashboard like Looker.

The Fix: Do not try to make the AI "read" the PDF. You must build the pipeline to the source. If the PDF comes from a SQL database, you give the AI access to the SQL database. If you receive many PDFs in email, you give AI access to the emails to first store and categorize the PDFs. If you don't, you are asking your AI labor to work with its hands tied behind its back.

The Playbook: Test Today

Stop guessing if your data is ready. Test it.

Before you execute a single AI investment, you must execute an Eligibility and Legibility Audit. You can start small with a Sandbox Audit:

• Clone & Isolate: You pull a segment of your business data into a secure, isolated environment.
• Strip the Risk: You programmatically remove PII, if applicable, so the data is safe to touch.
• The Test: You point an LLM at the sandbox. If it cannot derive the same insights your human analysts do, your data structure is Ineligible.

The Bottom Line

If you skip the audit, you aren't investing; you're gambling. You are building expensive engines on top of dirt roads.