AI’s Great. It Just Can’t Work Alone (Yet).

Hiya 👋

The studies I’m looking at recently are not the benchmarks from frontier AI model providers like OpenAI and Anthropic. I’m looking for the real world analysis and I was not surprised to see AI can only fully automate about 3% of real work.

It’s easy to laugh at the number, but honestly, I think it’s the most refreshing data we’ve seen all year.

Because here’s the truth: AI’s getting smarter, but the real gains still come from how we design the systems, workflows, and habits around it and even if AI didn’t progress any further, there’s still SO much that most teams can do to modernize how they work.

Let’s dive in to that and how important culture and change management considerations are in modern digital transformation👇

A new study from the Center for AI Safety and Scale AI caught my attention this week.
They tested leading AI models (GPT-5, Grok 4, Gemini 2.5 Pro, etc.) across hundreds of real remote-work projects to see how much of the work they could fully automate.

The result? Less than 3% of tasks were completed at a professional level.

That’s not a typo, all the buzz about AI replacing work doesn’t hold up (yet) when tested against the messy, complex reality of real jobs.

What stood out to me:
We’ve spent the past year helping clients implement automation and AI tools, and this study backs up what we see daily:
AI can accelerate work, but it still depends on how ready your systems and data are.

You can’t automate chaos.
If your software, processes, and workflows aren’t modernized, AI won’t save time, it’ll just surface the inefficiencies faster.

Why it matters:
The companies that start modernizing now -cleaning up data, integrating tools, documenting workflows, will be the ones ready when that 3% becomes 30% in a few years.
That’s the digital transformation advantage: being prepared before the breakthrough, not scrambling after it.

Go deeper:
📊 Explore the study → Remote Labor Index
📄 Read the paper → Remote Labor Index: Measuring AI Automation of Remote Work (PDF)

Every week, I see the same thing inside client teams:
smart people spending hours on rote work they’ve already figured out but still has to be done.

Here’s what I’ve learned:
Automation feels like a mountain, until you map the workflow.
Once you see the pattern, you know what’s automatable (new word…going with it) and what’s not.

We do this exercise regularly with our clients but we built a resource to share it as anyone can do it. The Workflow Audit & Automation Readiness Workbook is a simple self-audit you can run in under an hour to uncover your worthwhile automation opportunities.

We’ve run this exercise with dozens of teams, and it always surfaces clear wins. Sometimes that means automating a weekly reminder. Sometimes, it’s a full day of work saved between half a dozen people.

Why it matters:
Doing this builds automation muscle memory. Once your team learns to spot patterns, you’ll see opportunities everywhere.

No gatekeeping, grab it here directly:
🗂️ Workflow Audit & Automation Readiness Guide

I came across a great piece from MIT Sloan Management Review that nails something we see all the time:
Digital transformation isn’t really about the tech, it’s about the people.

They call it the Culture-Transformation Matrix, and it shows how the success of any modernization effort depends on balancing two things:

• Digital Transformation - how much your systems and processes evolve

• Cultural Continuity - how much your organization’s identity stays intact

Most transformation efforts fail not because the technology doesn’t work, but because culture can’t keep up or people aren’t setup to properly adopt it.

You can have the right tools, but if communication, training, and support aren’t built into the rollout, you end up with confusion or resistance instead of adoption.

Why it matters:
We see this firsthand, the teams that win aren’t just implementing automation, they’re creating buy-in.
When leaders treat modernization as both a technical and a human project, transformation sticks.

How we approach it at Switchboard:
Every engagement we run includes a cultural layer, from workflow design sessions to pilot testing with the people who’ll use the tools daily to proper training sessions and working with leadership to ensure they’re communicating a “why” that lands.

Go deeper:
📖 Cracking the Culture Code for Successful Digital Transformation - MIT Sloan Management Review
🔗 Read it here

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