AI, Marriage, and the Systems We Build: Why We Shouldn’t Be Surprised By High Failure Rates

What do AI investments and marriage have in common? A lot more than you'd think.

Recently, while walking past Las Vegas wedding chapels, I was struck by how we’re encouraged to leap into marriage—despite a 76% chance of it leading to dissatisfaction or divorce. If that were your odds of getting hit by a bowling ball, you’d wear a helmet, right?

Yet, we treat AI investments the same way: chasing transformation, pouring money into the latest technology, and ignoring the evidence that most implementations fail. Some studies suggest that over 80% of AI projects never reach deployment or meaningful ROI—but companies keep making the same mistakes.

The real issue? The systems we build produce the results we deserve. Just as societal expectations drive people toward marriage, hype, pressure, and poor planning drive businesses into AI investments that are doomed from the start.

So what if we designed AI strategies with the same scrutiny we should apply to marriage? The results might surprise you.

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#AI #DigitalTransformation #Leadership #Strategy #SystemsThinking #DataDriven

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The Serviceberry Mindset: How Nature’s Gift Economy Can Reshape Data Governance

For years, we’ve heard that breaking down data silos is the holy grail of business transformation. We’ve been told that better pipelines, integrated analytics, and AI-driven decision-making will finally unlock the full potential of enterprise data. But here’s the question no one seems to ask: What if we’re still thinking too small?

The real challenge isn’t just technological—it’s conceptual. We don’t just need better data governance or cleaner metadata. We need a way of thinking that moves beyond technical optimization and into deeper creative problem-solving. That’s where multidisciplinary thinking comes in.

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GREAT SPEECHES: IF RUSS ACKOFF GAVE A TED TALK

This presentation is from a 1994 event hosted by Clare Crawford-Mason and Lloyd Dobyns to capture the Learning and Legacy of Dr. W. Edwards Deming. Russ knew Dr. Deming and speaks here about the difference between "continuous improvement" and "discontinuous improvement" as seen through the lens of systems thinking.

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