AI in 2026: 10 Predictions for Businesses (and What to Do About Them)

Written By Loren Horsager

Every year, people ask me the same question: “What’s coming next with AI?”

And every year my answer gets a little more practical.

Because at this point, AI isn’t a “future trend.” It’s a business capability. In 2026, the winners won’t be the companies that talk about AI the most. They’ll be the companies that turn AI into repeatable systems—sales systems, service systems, operations systems, and leadership systems.

So here are my predictions for AI in 2026, written from the lens I care about most: how real businesses will actually use it to win.

1) “AI Strategy” will stop being a slide deck and become a weekly operating rhythm

In 2026, the companies getting real results won’t have some giant AI roadmap gathering dust. They’ll treat AI like continuous improvement.

That means:

  • A short list of outcomes (reduce cycle time, increase throughput, improve quality, reduce cost)

  • Weekly review of what’s working and what’s not

  • A backlog of automations and assistants tied to real roles

If you already run on something like EOS/Traction, this fits naturally: AI becomes part of your rocks, your scorecard, and your weekly problem-solving. The point isn’t “using AI.” The point is building a machine that uses AI.

Action: Create an “AI Opportunities” list with owners, expected impact, and next step. Review it weekly.

2) AI will move from “chat” to “do”

Right now, many teams are stuck in prompt land: asking questions, generating ideas, rewriting emails. Helpful, sure. But in 2026, the real advantage will come from AI that takes action.

Think:

  • AI drafts the proposal and creates the CRM record and schedules the follow-up

  • AI summarizes the client meeting and updates tasks and notifies the right team member

  • AI monitors inboxes and routes requests into the right workflow

This is where AI meets automation. Not flashy demos—boring, consistent execution that saves time and prevents things from slipping.

Action: Identify one workflow where requests come in (email, form, Teams message) and build an automated intake + triage process.

3) Every department will have its own “AI stack”

In 2026, the “company AI tool” will be less important than the department-specific stack.

Marketing will lean into content systems, research systems, analytics systems.
Sales will build prospecting systems, follow-up systems, proposal systems.
Ops will build SOP systems, QA systems, forecasting systems.
HR will build onboarding systems, policy systems, recruiting systems.

You’ll still want shared governance and security, but the winning teams will tailor AI to their actual workflows. The best AI implementation is never generic—it’s customized to the way your business runs.

Action: Map the top 5 repetitive tasks per department and pick one to systematize each month.

4) “Shadow AI” will become the biggest risk (and the biggest opportunity)

Employees are already using AI even when leaders aren’t paying attention. In 2026, this will accelerate—and companies will either fight it or harness it.

If you clamp down too hard, people will just do it anyway… badly and privately.
If you guide it well, you’ll unlock massive productivity safely.

The smart move is to set clear rules:

  • What’s allowed

  • What data is restricted

  • How outputs should be verified

  • Where AI work should be documented

Not complicated. Just clear.

Action: Publish a one-page AI policy and train your team on it. Then update it quarterly.

5) “AI literacy” will be a job requirement, not a nice-to-have

In 2026, AI literacy won’t mean “knowing what ChatGPT is.” It will mean:

  • Knowing how to frame problems clearly

  • Understanding what AI is good at (and what it’s terrible at)

  • Knowing how to verify outputs

  • Knowing how to build a simple workflow with AI + automation tools

Companies will start hiring for it. And people who refuse to learn it will feel the same pressure as someone who refused to learn email or spreadsheets.

Action: Train your team on a simple framework: Prompt → Evaluate → Improve → Automate.

6) The ROI conversation will get stricter

The early days were all experimentation, and that was fine. In 2026, leaders will want to see:

  • Hours saved

  • Cycle time reduced

  • Revenue impacted

  • Quality improved

  • Risks lowered

And honestly, that’s a good thing. AI should pay for itself.

The trap I see is companies buying tools without changing behavior. They pay for 50 licenses and usage stays low. Tools don’t create ROI—habits and systems do.

Action: Tie every AI initiative to a measurable metric before you build it.

7) “AI agents” will be everywhere, but most will be mediocre

Yes, agents are coming. Yes, they’ll be useful. But in 2026, most businesses will roll out agents that are basically:

  • A chatbot with a few integrations

  • Some automation triggers

  • A fancy interface
    …and not much reliability.

The businesses that win will treat agents like employees:

  • Clear job description

  • Defined inputs and outputs

  • Training data and examples

  • Performance monitoring

Agents will not replace leadership. They’ll replace repetitive execution—if you build them right.

Action: Start with one “agent role” like: Client Onboarding Coordinator or Sales Follow-Up Assistant. Keep it narrow and measurable.

8) AI will change management more than it changes technology

This is the one nobody wants to talk about.

In 2026, AI will expose weak management fast:

  • Vague expectations

  • Undefined processes

  • Missing documentation

  • Poor accountability

  • “Tribal knowledge” locked in people’s heads

AI thrives in clarity. If your business runs on chaos, AI won’t fix it—it will amplify it.

But if you run on clear processes and consistent feedback loops, AI will multiply your output.

Action: Document one core process per week. Seriously. Start with sales follow-up, onboarding, invoicing, or customer support.

9) Personalization will become the default expectation

Customers will expect faster responses, more tailored proposals, and more proactive service. Not because businesses suddenly got better—because AI made it possible.

The baseline experience is shifting:

  • Generic emails won’t hit

  • Slow follow-up won’t be tolerated

  • “We’ll get back to you” will lose deals

Businesses that use AI to personalize and respond quickly will feel like they have superpowers compared to competitors.

Action: Build a personalized follow-up system for leads and clients—based on role, industry, and prior interaction.

10) The best businesses will become “AI-native” without becoming tech companies

You don’t have to become a Silicon Valley startup to win with AI.

In 2026, the strongest businesses will:

  • Make decisions faster

  • Execute more consistently

  • Train employees better

  • Capture and reuse knowledge

  • Automate the boring stuff

  • Keep humans focused on relationships, judgment, and creativity

That’s what “AI-native” really means. Not that you build models. It means your organization runs with AI woven into the fabric of how work gets done.

Action: Ask this in every leadership meeting: “What’s one part of our business that should be systematized this quarter?”

My Bottom Line for 2026

AI won’t be the advantage. Implementation will be.

The businesses that win will not be the ones with the best prompts. They’ll be the ones with:

  • Clear processes

  • Strong leadership rhythms

  • Smart automation

  • A team trained to use AI responsibly

  • A focus on measurable outcomes

If you’re a business leader, your job in 2026 is simple (not easy):
Turn AI from a tool into a system.

And if you do that, you’re not just “keeping up.”
You’re building a business that scales with less friction, less burnout, and way more leverage.

Loren Horsager
Next

What’s Working (and What’s Not) in AI - 2025 Edition