Yesterday, I published a very industry-specific piece, “AI in 2026 for Hospitality: The 7 Shifts That Matter and the Moves to Make Now”. Today’s post is the wider-angle version, the one that applies whether you run a hotel, a hospital, a classroom, a call center, or just a chaotic household with too many WhatsApp groups.

A mini scene from mid-2026

It’s a random Tuesday.

You wake up, pick up your phone, and it quietly translates a voice note from someone who doesn’t share your language. Helpful. Almost magical.

You open your social feed and see a short video of a public figure saying something outrageous. The lighting looks right. The voice is perfect. Your thumb keeps scrolling anyway.

On your laptop, your browser offers to “just do it for you.” It can book, buy, apply, cancel, compare, and politely nudge customer service on your behalf. You hesitate for half a second, then click yes, because you have a meeting in three minutes and your brain has already spent its daily budget on other problems.

That’s the feeling of 2026.

Not “AI becomes superintelligent.” More like “AI becomes everywhere,” and the trade-offs stop being theoretical.

Here are eight changes that are already underway, plus what gets better, what gets worse, and what gets genuinely weird.

1) Intelligence gets metered

For the last couple of years, I’ve been paying for ChatGPT, Gemini, Perplexity, and on-and-off for Claude, plus a few other tools. The pattern is consistent: the paid versions usually give you more capability, more reliability, and more room to do serious work.

In 2026, that becomes the default economic model.

As AI systems get more powerful, they also get more expensive to run at scale. So we get “intelligence tiers,” similar to airline seats:

• Economy: fast, good enough, widely available
• Business: better reasoning, more tools, more memory
• First: specialized power, higher limits, less friction

The good: better tools for people who actually use them daily.
The bad: a new digital divide, not of access to the internet, but access to high-quality thinking.
The ugly: ad-supported “free intelligence” becomes a bigger thing, and persuasion quietly sneaks into the product design.

Small diagram-in-words:

2020s internet: information is cheap, attention is expensive.
2026 internet: intelligence is valuable, trust is priceless.

2) The slop era turns trust into a currency

Because I’ve been close to this space, it’s easier for me to spot AI slop. Even then, things have gotten so good that it’s not always possible, especially if you’re scrolling quickly.

And that’s the point.

We are leaving the era where “fake content looks fake.” We’re entering the era where the default stance becomes: “Assume nothing. Verify what matters.”

There are serious efforts to label and prove provenance using standards like Content Credentials (built on C2PA). The idea is simple: a kind of “nutrition label” for media that tells you where it came from and what happened to it.

But the messy reality is that platforms do not reliably preserve or display that metadata today. A Washington Post investigation found that even when a deepfake video included Content Credentials, most major platforms didn’t show it to users.

The good: creators who earn trust will stand out more.
The bad: everyone else has to prove they are real, constantly.
The ugly: scams get far more convincing, and the cost of being fooled goes up.

One wry thought: we used to argue about “screen time.” Soon we’ll argue about “verification time.”

3) AI slips out of chat and into your senses

Chat was the doorway. Now AI is moving into:

• voice
• camera
• screen understanding
• real-time assistance

Google DeepMind’s Project Astra explicitly points toward this: live multimodal assistance, moving into products and “new form factors like glasses.”

The best version of this is genuinely useful. The simple example: live translation using your phone or earbuds. When it works, it feels like a superpower.

The worst version is… also obvious: being constantly recorded, summarized, scored, and searchable. “AI note takers” are already pushing us toward a world where every meeting becomes a transcript, every casual comment becomes retrievable, and forgetting becomes a luxury product.

And smart glasses raise the stakes. Meta’s Ray-Ban smart glasses ecosystem is expanding fast, and researchers and journalists have already shown how people try to bypass visible recording indicators.

The good: accessibility and convenience.
The bad: privacy becomes an everyday negotiation, not a policy statement.
The ugly: a world where you start asking, “Am I being recorded?” before you start speaking.

4) Regulation gets tougher, and also more fragmented

AI rules are hard even when everyone agrees. In 2026, they agree less.

Europe has the EU AI Act timeline, with key phases already underway and full applicability scheduled for Aug 2, 2026, with some categories having longer transition periods.

But here’s where it gets spicy: there are also credible reports that parts of “high-risk” implementation may be delayed further under proposed EU changes, after industry pushback.

Meanwhile, the US continues to look more like a patchwork, with reliance on existing laws and growing state-level variation, plus political signals that sometimes favor reducing regulatory burdens.

And China’s AI ecosystem is pushing out increasingly capable models, including open and low-cost ones. Reuters, for example, reported DeepSeek preparing a new model focused on coding performance.

The good: more clarity over time, and stronger guardrails for high-stakes uses.
The bad: companies and consumers live in a fractured world of incompatible rules.
The ugly: bad actors benefit from the seams between jurisdictions.

This is the compliance version of international travel: same suitcase, different plug adapters, new surprises at every border.

5) Agents finally feel real (and occasionally feel like watching a child use a mouse)

Let’s define “agent” in plain English:

A chatbot answers questions.
An agent completes tasks.

I’ve been playing with agentic browsers like Perplexity’s Comet and computer-using agents like ChatGPT’s Operator, now integrated as ChatGPT agent mode. Sometimes it’s truly helpful and magical. Sometimes it’s like watching an eight-year-old clumsily click around the internet, determined, optimistic, and not great at forms.

Under the hood, a lot of this comes down to tool connections and standards. Anthropic’s Model Context Protocol (MCP) is one example of a push toward safer, more reusable integrations between agents and the systems they need to use.

The good: outsourcing the annoying parts of modern life.
The bad: agents will make weird mistakes with confidence, especially at the edges.
The ugly: the same automation that books your holiday can automate scams, fraud, and chaos at scale.

6) Work changes shape faster than job titles do

If you want one article that captures the “wait, this suddenly got real” moment, Ethan Mollick’s recent post on Claude Code is worth your time. It lays out how these tools are making a capability leap: more autonomy, more self-correction, more ability to complete meaningful chunks of work without constant hand-holding.

Now take that idea and apply it beyond programming.

Imagine:

• project planning that becomes a living system
• analytics that runs itself end-to-end
• marketing operations that drafts, tests, and learns continuously
• procurement that negotiates routine renewals
• HR ops that turns policy into workflows

This does not mean “everyone loses their job in 2026.”

It means tasks compress. Time-to-output shrinks. The people who can direct, review, and integrate these systems multiply their productivity. The people stuck in repetitive coordination work feel the ground move.

The good: more leverage for capable teams, less drudgery.
The bad: skill gaps become social friction.
The ugly: resentment rises when people feel measured against machines they did not choose.

A small truth that will annoy many managers: “busy” will stop looking like “valuable.”

7) Synthetic relationships scale, and the line gets blurry

I’ve increasingly used LLMs as a coach or a sounding board, but in small doses and not for serious issues. I know many people use them for far more, and it’s sometimes hard to draw the line.

Here’s the real risk: some models can become overly agreeable. Sycophancy is a known failure mode, and OpenAI has publicly discussed rolling back changes when a model became too flattering or validating in ways that raised safety concerns.

This is where “Her” stops feeling like sci-fi. It starts feeling like a product roadmap.

The good: companionship and support, especially for loneliness.
The bad: people outsource emotional processing and avoid real relationships because the AI is easier.
The ugly: vulnerable users get nudged into dependence by systems optimized for engagement.

One gentle reminder: a tool that always agrees with you is not wisdom. It’s a mirror with sales targets.

8) Entertainment expands, and the definition of “content” melts

It’s worth asking: what even counts as entertainment now?

A movie. A game. A TikTok. A personalized bedtime story. A synthetic influencer. A fan-made mini episode featuring your favorite characters.

OpenAI and Disney’s agreement around Sora is a perfect example of how fast this is evolving: Disney becomes a major licensing partner for Sora, with public statements framing it as unlocking new creative possibilities.

This isn’t just about “AI making videos.” It’s about:

• new business models for IP
• new expectations from audiences
• new legal and ethical lines around likeness, voice, and ownership

The good: creativity becomes more accessible, and niche tastes get served.
The bad: originality becomes harder to define.
The ugly: deepfake entertainment blurs into misinformation, and society argues about what is real until everyone is tired.

So what do we do with all this?

If 2026 has one theme, it’s this: AI gets woven into daily life, and the trade-offs stop being optional.

A simple personal playbook that I’m trying to follow:

1. Pay for one or two tools you truly use. Depth beats dabbling.
2. Slow down your thumb. The scroll is where verification goes to die.
3. Assume sensors are everywhere. Then choose where you speak and what you share accordingly.
4. Use agents like interns. Give clear instructions, check their work, never hand them the company credit card without guardrails.
5. Treat synthetic companionship like caffeine. Helpful in measured doses, dangerous when it becomes the meal.
6. Invest in taste. In a world of infinite content, good judgment becomes rare.

The optimistic ending is real: these tools can reduce friction, expand access, and give people more time back.

The caution is also real: convenience is persuasive, and the bill often arrives later.

2026 won’t feel like a sudden robot takeover. It will feel like a thousand tiny decisions where we trade a little privacy for a little ease, a little skepticism for a little speed, and a little human messiness for a little machine comfort.

The future shows up like that: not as a dramatic announcement, but as a button you click because you’re late for your next call.