Good Morning, Reader it's Maria,

I attended a keynote this week where Sol Rashidi (fantastic speaker, check her out) said something that really resonated.

She talked about why she left her previous company: They were using AI as justification for mass layoffs.

That's not what AI was built for.

AI was created to amplify humans, not erase them, to support people in doing better work, not to make them redundant line items on a balance sheet.

But here we are.

If podcasts are more your speed, I've got you covered; there's a discussion about this topic available now here.

THE BIG IDEA

The Human Cost of "Efficiency"

Accenture recently cut 11,000 jobs while investing heavily in AI. They're calling it "reskilling" and "restructuring." The CEO said employees need to "retrain and retool" at scale, and those who can't will be "exited."

The Washington Post fired over 300 journalists this week. One of them, Lizzie Johnson, found out while reporting from a war zone in Ukraine. She was writing by headlamp, her pen freezing with no heat or running water. no "thank you for your service" here.

This is what happens when companies treat people like commodities, when AI becomes the justification for slashing headcount to boost shareholder dividends while calling it "digital transformation."

But here's what I don't get.

Why don't they understand that when companies cut people in the name of AI efficiency, they lose more than headcount?

They lose institutional knowledge. That person who knows why that process exists in the first place. The one who can spot a problem before it becomes a crisis. The relationships built over the years that make things happen.

They lose trust. Employees who remain don't feel "lucky to still have a job." They feel like they are next. And trust, once broken, doesn't come back because you send a company-wide email about "exciting new directions." Actually, that's the nail in the coffin.

They lose culture. The unofficial networks. The people who train others, who keep morale up, who know how to get things done when the system doesn't work.

At the Washington Post, they lost their entire Middle East team. Their Cairo bureau chief. Correspondents covering China, Iran, and Turkey. The sports desk. The books section. The people who built trust with readers over decades.

All of that walks out the door, and no algorithm can replace it.

Here's what I think will happen next.

It will get worse before it gets better.

More companies will follow suit. More headlines about "AI-driven restructuring." More people treated as expendable.

But then, likely this year, these same companies will realise their expected return on investment isn't materialising. The AI didn't deliver the promised efficiency because they stripped out the very people who could have made it work properly.

They'll scramble to rehire. They'll rebuild teams they never should have dismantled in the first place. And the costs of that? Recruitment, onboarding, lost productivity, reputational damage? Much higher than what they "saved."

And the people caught in the middle Reader? The ones being treated like they're disposable? They're the ones paying the price for short-term thinking and poorly thought-through strategy.

Don't know where to start?

​Book a free consultation and let's chat!

THE ACTION STEP

What Responsible AI Integration Actually Looks Like

The future is technical, but it needs to be led by humans.

AI is in our hands, and WE get to decide what we do with it. We can choose to use it responsibly to let it enhance what we humans do best, or we can let it happen to us. Which will destroy trust and prioritise spreadsheets over people.

We all know this famous line from Spider-Man: "With great power comes great responsibility." Well, this is true here too.

So what does responsible AI integration actually look like?

It starts with a different question.

Instead of asking "Who can AI replace?" ask "What can AI support?"

Where are your people spending time on work that drains them? Think about repetitive admin tasks, data entry, reformatting documents, scheduling, and chasing approvals.

That's where AI should step in. Not to replace the person, but to give them back time to do the work that actually matters: The strategic thinking, the client relationships, the problem-solving that requires judgment and experience.

Here's a simple test for any AI integration decision:

Does this make someone's job better, or does it make them redundant?

If it's the former, you're on the right track. If it's the latter, you need to ask yourself if you're solving the right problem.

Involve your people in the process.

The teams doing the work are the ones who know where the friction is. They know what's broken, what's inefficient, and what would actually help. If you're rolling out AI without asking them, you're for sure doomed.

And when you do integrate AI, train people properly. Not a one-hour webinar. Real training. Give them the skills to use it well, to understand what it can and can't do, and to stay relevant as the tools change.

Accenture says they're training 70,000 employees in AI. That sounds impressive. But they cut 11,000 first. That's the wrong order.

Be honest about what's changing.

If roles are shifting, say so. If some tasks will be automated, explain what that means for the people doing them. Uncertainty is worse than hard news. And people can handle change when they're brought along, not blindsided.

Measure the right things.

If your only metric is cost savings, you're setting yourself up to fail. What about employee satisfaction? Retention? Quality of work? Speed of decision-making? Client feedback?

Responsible AI integration doesn't just save money. It creates capacity, improves quality and allows people do work they're actually good at.

That's a future worth building.

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AI MADE SIMPLE

Stop rebuilding slides from scratch!

There's a faster, cleaner way to do this now, and I'm genuinely excited to share it.

I discovered Gamma at the end of last year and thought it was brilliant. But what changed this year is a new beta feature they just launched called Remix.

Why? It solves one of the biggest problems with AI-created slides: Consistency.

Here's my situation: I create a slide deck for each of my Strategic Management courses at CIEE Barcelona, each class covers a different topic, but the structure and visual identity need to stay the same.

A problem you may have noticed is that when you ask AI to recreate slides (or anything) from scratch, it doesn't behave consistently. Layouts will shift, and colours will change.

You may have seen these videos going around on social media of people entering the same prompt to create a picture over and over, and the picture morphing into something completely different.

Remix fixes that:

1. I start with one solid slide deck in Gamma
2. I prompt Remix to keep the same layout and colour structure
3. Then I paste in the new slide outline for the next class and seconds later, the new deck is ready
4. From there, I only tweak content or add a slide if needed.

And tadaa! I have a consistent slide deck for my next class. If you create slides regularly, this is genuinely worth trying. You'll thank me later!😉

That's all for today Reader

Have a great weekend!👋🏼

Take Care

Maria

PS: If you want to explore what working together looks like, book a free call

PPS: If you enjoy these emails and want to do something nice, you can buy me a coffee 😉

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