When “Progress” Is Actually Regression Dressed as Innovation
🙃 Output over outcomes. Efficiency over customer value. Automation over innovation. What is happening? Are we in the upside-down?
I originally shared this on LinkedIn.
I don’t usually repost things here as-is, but this one feels different.
I’m too passionate — and honestly, a bit too concerned — about where this is heading to soften it with a rewrite.
So I’m sharing it here mostly as it came out — raw, direct, and still very much on my mind.
Lately, it’s been feeling like we’re operating in the upside-down.
Not because things are changing — they should be.
But because some of the principles we’ve aligned on for years seem to be quietly flipping.
Almost like the scale has tipped… but we’re still calling it balance.
I had a “wait… are we serious?” moment tonight.
I thought we had already agreed on something.
We prioritize outcomes over outputs.
And then AI shows up… and suddenly it’s all about outputs again. Seriously?
That’s not progress.
That’s regression dressed up as innovation.
A lot of AI adoption talk doesn’t feel like progress to me.
It feels rushed. A little grabby.
Focused on how much we can automate, extract, eliminate.
More output. Faster.
But not necessarily better outcomes.
And this part really gets me: Customers are people. Efficiency at their expense isn’t a strategy. It’s a trade-off we should at least be honest about.
Because while I had worked with AI inside companies, this phase was different — not driven by a roadmap or a business case. I was using it across my own work and life. Writing. Thinking. Prototyping. Problem-solving.
And what I kept coming back to wasn’t:
“How do I do more, faster?”
It was:
“What becomes possible now that wasn’t before?”
There’s a difference between:
using AI to increase output
and using AI to expand capability and meaningfully increase impact
One is about efficiency. The other is about what actually gets better — for the people on the other end. And for the teams building it.
I understand why this is happening.
Public companies are under pressure to show immediate value. And efficiency is easy to measure.
But if we stop there, we miss the bigger opportunity.
Because the real promise of AI isn’t just doing the same work faster.
It’s doing better work. Or entirely new work. Together.
If we actually believe in outcomes over outputs —
then AI shouldn’t pull us away from that.
It should push us deeper into it.
Automation has its place.
But if we’re leading teams, building products, shaping strategy —
the question isn’t:
“What can we remove?”
It’s:
“What can we now achieve — together — that we couldn’t before?”
Because otherwise…
we’re not really moving forward.
We’re just repeating old patterns — dressed up as innovation.
💬 I’d genuinely love to hear how others are thinking about this.
Where are you seeing this tension show up — between output, efficiency, and real impact?
✨ If this resonated…
I write about product, leadership, and using AI as a true teammate — not a replacement — while juggling all the realities of modern adulting.
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✍️ Written by Maura Randall
Product & Platform Leader | Exploring Human + AI Collaboration
I design systems, frameworks, and playbooks for integrating AI into real teams — with a focus on creativity, judgment, and meaningful impact.