3 AI Trends That Will Separate Winners From Burnouts (+ Your AI Playbook)
Read time: 6 minutes
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Hey guys,
I haven't published any article in three weeks.
I couldn't make time for it. Lots of workshops, training and my personal AI overwhelm with all the recent developments.
I don't do AI slop. You get my actual thoughts or nothing.
Finally, I'm back. And a lot has happened.
From The Trenches
Last week I ran an AI Trends Workshop with 12 managers at a large insurance corporation. We ran the biggest developments through my SIGNAL Framework and translated them into action.
Most trends looked great on a slide. But the room went quiet when it came to "what do we actually do with this?"
The reason I keep seeing:
- overwhelm
- lack of capacity
- lack of expertise.
...And an uncomfortable irony: AI, the thing that's supposed to give us back time, is burning people out.
So here are 3 trends you must be aware of. Not ten to drown in. Three that passed my SIGNAL test.
FYI: The SIGNAL Framework is how I help leadership teams cut through AI noise. For every trend or tool, we score it on six dimensions: Strategic relevance, Implementation readiness, Governance need, Near-term business value, Advisory implications, and Leadership implications. If it doesn't score on at least three, we park it. More on this in a future issue. |
3 Shifts That Passed the SIGNAL Test
1) AI Agents Are Real. But They're Not Ready for Your Business.
Everyone is pitching "AI agents" right now. Autonomous systems that handle your customer service, manage your pipeline, process your invoices.
Sounds great.
The reality is more nuanced.
As MIT Sloan puts it: AI agents are entering what Gartner calls the "trough of disillusionment".
Research from both Anthropic and Carnegie Mellon found that agents still make too many errors for any business process involving real money.
Meanwhile, surveys show 68% of small businesses are already using AI regularly.
The gap between adoption and effective adoption is growing fast.
The pattern I see: the companies winning with agents aren't deploying them broadly. They're picking one narrow, boring, repetitive workflow and automating that.
- Lead follow-up emails
- Appointment scheduling
- Data entry from invoices
- Not "autonomous decision-making across the enterprise."
2) The EU AI Act Hits in August. Most SMEs Have No Idea They're Affected.
August 2, 2026: That's the enforcement deadline for the EU AI Act's high-risk AI rules.
If you use AI for screening job candidates, assessing credit, prioritizing customer service, or making decisions that affect people's access to essential services: you may be operating a "high-risk" system under the Act.
The penalty is up to 7% of global annual revenue. Let that sink in.
Most SME leaders I speak with haven't even heard of it.
The good news: the EU has built in protections for smaller companies. SMEs get priority access to regulatory sandboxes (free of charge). Simplified documentation templates. Proportionally lower fines. The European Commission will even publish simplified compliance guidelines specifically for SMEs in the coming months.
But "lower fines" still means fines. And "simplified documentation" still means documentation.
The smart move: find out if you're affected before regulators find you. It takes ten minutes with the EU's own AI Act Compliance Checker (free, online, at artificialintelligenceact.eu).
3) The AI Shakeout Is Here. Vendor Choice Now Has Ethical and Strategic Weight.
Something shifted in March.
2.5 million users abandoned ChatGPT after OpenAI's Pentagon deal.
The #QuitGPT movement saw app uninstalls spike 295%. Claude jumped to #1 on the App Store.
At the same time, Oracle announced 20,000 to 30,000 layoffs to fund AI infrastructure. Block cut 4,000 employees, with the CEO explicitly saying AI made those roles redundant.
This isn't noise. It's the industry sobering up.
For SME leaders, this means two things.
First: your choice of AI vendor now carries ethical weight. Your employees, your customers, and increasingly your partners are paying attention to which platforms you build on and why.
Second: the workforce conversation just got real. IMD predicts a 10-20% reduction in traditional middle-management roles by end of 2026. Not mass layoffs. But a quiet compression of roles built around information routing, reporting, and basic coordination.
The question isn't whether AI will change your team structure. It's whether you're leading that change, or being surprised by it.
What Most People Are Missing
This isn't a technology problem. It's a leadership problem.
PwC's 2026 predictions say it plainly: the companies getting real results have top-down AI strategies focused on a few high-value workflows. Not crowdsourced experiments. Not "let's see what happens."
Harvard Business School is warning about something deeper. We're so focused on the first-order effects of AI (efficiency, speed, cost) that we're ignoring the second-order effects: how AI is changing the meaning of work.
When the routine, analytical parts of someone's job get automated, what's left?That's a question most leaders haven't started asking.
IMD's faculty put it even more sharply: the most successful organizations in 2026 will stop treating AI as a technology race and start treating it as a management revolution.
In my experience training 3,000+ leaders, the companies that stall share the same symptoms. It's never "we can't find the right tool."
It's always: unclear priorities, no dedicated capacity, and a leadership team that treats AI as an IT project instead of a strategic one.
The real risk in 2026 isn't falling behind on AI. It's burning out your people while falling behind on AI.
That's the trap I saw in last week's workshop. Twelve smart managers, drowning in AI noise, with no time to think clearly about what actually matters for their business.
The antidote?
Ruthless prioritization. Not more tools. Not more pilots. Fewer bets, placed with conviction.
THE PLAYBOOK: What You Can Do This Week
1. Run a 10-minute AI Act check. Go to artificialintelligenceact.eu and use the free Compliance Checker. Answer the questions for your most common AI use cases (recruitment, customer scoring, content generation). Know where you stand before August.
2. Pick your ONE agent use case. Don't try to "deploy agents across the business." Find the single most painful, repetitive workflow your team complains about weekly. Scheduling? Follow-up emails? Data entry? Start there. One use case. One tool. One month to test.
3. Have the workforce conversation before it has you. Block 30 minutes with your leadership team. One question on the agenda: "Which roles in our company are built primarily around information routing, reporting, or basic coordination?" Those roles will change first. Plan for it now, on your terms, not reactively.
4. Apply the SIGNAL test to any "trend" someone pitches you. Before investing time or money in any AI trend, run it through these filters: Strategic relevance for your business? Implementation readiness today? Governance needs? Near-term business value? Leadership implications? If it doesn't score on at least three, park it.
THE MONDAY TEST
This week, try this: Open the EU AI Act Compliance Checker and run your top 3 AI use cases through it. Takes ten minutes. You'll either confirm you're fine, or you'll discover you have five months to prepare. Either way, you'll know. And knowing beats guessing.
My honest Take
The Burnout Paradox
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We're in a strange moment. The technology that was supposed to give leaders breathing room is instead creating a new kind of overwhelm. Not "I have too much work." But "I have too many possibilities and no way to evaluate them all." The leaders who will thrive aren't the ones adopting the most AI. They're the ones with the discipline to say no to 90% of it. |
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Talk soon,
Alex