🔹 The Automation of Deception: Are We Training AI to Reinforce Bias? 🤖💡

Businesses love to measure Customer Experience (CX)—but here’s the uncomfortable truth: Most CX metrics don’t predict profitability or success. They measure sentiment, not reality.

Take a look at these two groups:

âś… Metrics Based on Real Numbers & Facts:
• CAC (Customer Acquisition Cost) → The cost of getting a customer.
• RPR (Repeat Purchase Rate) → Whether customers actually buy again.
• OEE (Overall Equipment Effectiveness) → Factory floor data that exposes inefficiencies.
• SWOT (Strengths, Weaknesses, Opportunities, Threats) → A fact-based reality check on strategy.

⚠️ Metrics Based on Sentiment & Assumptions:
• NPS (Net Promoter Score) → How customers feel, not what they do.
• CLV (Customer Lifetime Value) → A projection built on assumptions, not real behavior.
• Most CX Metrics → Vanity measures that look good on a dashboard but don’t drive business value.

🚨 The real problem? We’re now training AI on these same distorted metrics.

A dashboard can be removed. But an AI remembers.

When we automate bias—when we feed AI the wrong KPIs—we don’t just mislead ourselves today. We create systems that reinforce selective truths—until bias becomes reality.

🔎 What happens when the truth is no longer part of the equation?

I’ve seen this pattern before. Optimizing for the wrong things doesn’t just waste time—it creates long-term damage. And with AI, that damage won’t be easy to undo.

⚡ It’s time to rethink how we measure success. If your AI and dashboards aren’t built on real profitability drivers, they’re just automating blind spots.

👉 If you stopped tracking NPS tomorrow, how would your CX strategy change?

Disclaimer

The companies and organizations mentioned in this article are referenced for informational and analytical purposes only. All discussions about their potential roles and interests in space-based data centers are based on publicly available information and do not imply any endorsement, partnership, or direct involvement unless explicitly stated. The opinions expressed are solely those of the author and do not reflect the official positions of the companies mentioned. All trademarks, logos, and company names are the property of their respective owners.

#AI #CustomerExperience #Profitability #Automation #MachineLearning