Business of AI: Who Participates and Who Gets Left Behind? | Brim

The business of AI is becoming a question of who participates and who gets left behind

In a recent episode of The AI Opportunity podcast, Zac Engler described this moment as "civilisation Max-Q". The point in a rocket launch where the pressure is highest, everything is shaking, and nobody is fully sure what happens next. It is a good description of where we are with AI right now.

The business of AI is no longer just about which model you use or which software you buy. It is about whether your business is ready for what happens when AI becomes part of everyday work.

Why does the business of AI suddenly feel so urgent?

The business of AI feels urgent because the pace of change is accelerating faster than most companies can keep up with. Two years ago, most businesses were experimenting with ChatGPT for content and research. Today, businesses are using AI to automate reporting, summarise meetings, analyse customer data, and support decision-making.

The next stage will be even faster. AI is moving from answering questions to completing work. Companies are not competing on access to AI anymore. Everyone can access the same models. The difference is in how effectively businesses apply them.

The businesses that build AI into workflows, operations, and decision-making will move faster than the businesses still treating AI like a side project.

Why are so many businesses still struggling with AI adoption?

Most businesses are struggling because they are approaching AI as a tool rather than as an operating model. They buy licences, run a few workshops, ask teams to test ChatGPT, and then wonder why nothing changes.

The issue is not usually the technology. It is that the AI sits outside of the real work.

A sales team might use AI to help write emails, but somebody still has to research the account, decide who to contact, update the CRM, and manage follow-up.

A finance team might use AI to summarise reports, but someone still has to gather the data, clean the spreadsheet, and interpret the results.

That is why so many businesses experiment with AI and then stall. They see some value, but not enough to change how the business runs.

What happens when some people adopt AI and others do not?

One of the most interesting points from the podcast was the idea that AI could create a major gap between people and businesses that adopt it early and those that resist it.

Some people will lean in. They will use AI to learn faster, work faster, and make better decisions. Others will avoid it completely.

That divergence is already starting.

Zac Engler gave the example of building his own Claude-based AI system despite coming from an HR background and not being technical. That is exactly the kind of shift happening right now. People who are curious and willing to experiment are suddenly able to do things that previously required technical skills or large teams.

That has huge implications for the business of AI.

Two companies with access to the same AI models can end up in very different places. One uses AI occasionally to save time. The other uses it to redesign workflows, speed up decisions, and scale without hiring at the same pace.

Over time, those businesses stop looking similar.

What should businesses do now?

Most businesses do not need to move faster for the sake of it. But they do need to start learning.

Start by identifying the work that feels slow, repetitive, and frustrating. Reporting, admin, CRM updates, project tracking, and internal communication are usually good places to begin.

Then focus on education. The businesses that benefit most from AI are usually the ones where people understand what it can do and where it actually fits.

It is also important to think beyond tools. The long-term value does not come from having access to ChatGPT or Copilot. It comes from building AI into your own workflows, knowledge, and business context.

The business of AI is not really about software. It is about participation. The businesses that benefit most will be the ones that learn quickly, build capability early, and use AI to rethink how work gets done.

The ones that wait for certainty may find that the market has already moved without them.

AI is not just changing work. It is changing who gets ahead.

Check out the podcast for a deeper dive into this topic. 

‍