AI Didn’t Replace Your Job: The 4 Types of AI Workflows

AI Didn’t Replace Your Job. It Changed the Job.

Let’s start with a simple premise: Work isn’t monolithic. There are different kinds of work—each with its own purpose, friction points, and value drivers. If we’re going to understand how AI changes the way we operate, we first need to categorize what we do.

At AdVenture, we use a mental model that breaks work into four broad buckets:

1. Creative Problem-Solving
2. Visionary Design
3. Decision-Making
4. Execution
   

AI doesn't eliminate any of these. Instead, it changes the entry requirements and rewires the value chain.

1. Creative Problem-Solving

Think: ambiguous client requests, diagnosing tracking issues, untangling the logic of a dysfunctional ad account. This is the “figure it out” work. It doesn’t come with playbooks or SOPs. It’s messy, iterative, and rooted in judgment.

What AI does here: It’s the brainstorm partner who doesn’t get tired. You type in a hypothesis and get 10 ways to stress-test it. It doesn’t always give you the right answer, but it gives you momentum—and that’s often the hardest part.

The paradox is that AI makes problem-solving less lonely, not more automated. And when you’re deep in the weeds of a complex strategy doc, sometimes that’s exactly what you need.

2. Visionary Design

This is where strategy turns into scaffolding. You’re not solving a specific issue—you’re architecting something net-new. A reporting framework that actually reflects the business. A productized offering that didn’t exist last quarter. The blueprint of a campaign no one’s run before.

What AI does here: It’s the creative accelerant. AI tools like Midjourney, Runway, and ChatGPT don’t hand you a finished product. But they lower the cost of iteration to almost zero. That means you get to test ideas faster—and bad ideas die faster too.

In the past, Visionary Design required deep domain expertise and a decade of practice in execution. AI severs that dependency. You don’t need to be a seasoned After Effects wizard to storyboard a brand video. You just need taste, clarity of thought, and the nerve to ship.

3. Decision-Making

This is the everyday grind of leadership—resource allocation, campaign pivots, budgeting, team bandwidth. Most decisions are made in the grey area, with partial information.

What AI does here: It won’t decide for you. But it will organize the chaos. It can surface insights you missed, summarize feedback loops, or model outcomes. The goal isn’t to automate judgment—it’s to amplify it.

If you’re relying on gut instinct, AI gives you a second brain. If you’re stuck in analysis paralysis, it imposes structure. Either way, it lets you operate with greater velocity and less drag.

4. Execution

Clicking the buttons. Formatting the doc. Pushing the campaigns live. Historically, this is where most people spent most of their time. It’s also where most errors happen—and where most of the work is invisible.

What AI does here: This is the most obvious use case. Generating copy, cleaning data, writing code, building frameworks. Execution is where AI delivers pure efficiency. But that efficiency creates a new bottleneck: deciding what to execute.

In other words, if AI saves you 10 hours of execution, what are you going to do with those 10 hours?

So What Do You Do With This Model?

The most powerful teams we’ve seen aren’t the ones that automate everything. They’re the ones that know how they want to work. Solo, delegated, or in copilot mode.

• Delegation works best for repeatable execution.
• Copiloting works best when you bring your own judgment to the table.
• Solo work still matters—but you should know why you're choosing to go it alone.
  

Every task falls into one of these four buckets. The goal is to know which kind of work you’re doing—and decide what version of you (or your tools) is best suited for it.

That’s the real leverage of AI. Not in doing the work for you, but in letting you spend your time where it matters most.