AI Strategy: separating the signal from the noise
A pragmatic guide for business leaders on how to implement AI without wasting millions on science projects.
The Board Mandate
"What is our AI strategy?" It is the question every founder and CEO is getting from their board. The knee-jerk reaction is often to task engineering with "adding AI" to the product, resulting in a slightly better chatbot that cost $500k to build.
Internal Leverage vs. Product Features
Before you try to sell AI to your customers, use it to gain leverage internally. The highest ROI implementations of AI for growth-stage companies are almost always operational:
- Automating customer support triage
- Speeding up engineering velocity with Copilots
- Automating repetitive finance and data entry tasks
The Data Problem
AI is useless without clean data. If your CRM is a mess, your ERP is siloed, and your databases are fragmented, an AI initiative will fail. As your vCTO, DoubleChecked focuses first on data governance and infrastructure readiness, ensuring that when you do deploy machine learning, it actually has accurate data to learn from.