Marketing teams must own AI, or workslop will take over

AI is now the main driver of increased martech budgets, but the adoption of AI tells a different story. Research on martech performance finds that only 49% of martech tools are actively used, and only 15% of organizations qualify as high performers — those who meet strategic goals and demonstrate a positive ROI. 

This has a downstream effect on marketing teams, what Greg Kihlstrom, writing in MarTech, calls “workslop.” This proliferation of low-quality, generic output occurs when marketing teams are pressured to use AI to deliver more volume with less time allocated to quality control and critical thinking. 

The expectation that AI will act as a silver bullet to solve all of marketing’s problems has created operating conditions that impose unrealistic performance pressures, flooding channels with mediocrity rather than boosting productivity. 

A big part of the problem is that leadership often fails to define how to use AI and what success looks like. Marketing departments need to step up to the plate to take ownership of AI adoption themselves.

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Who owns AI adoption?

When the C-suite doesn’t own AI adoption, they aren’t accountable for its outcomes, leading to confusion over who is responsible for what.

But even if marketers do receive a clear executive mandate, they still need to be in charge of decisions about how AI functions within their departments, even though they face many challenges.

Deciding who is responsible for AI and its outcomes often isn’t the marketing department’s responsibility. Questions on security and access may be under the discretion of an IT department, questions on productivity and tools by an operations department, and so on, all without the input from marketing.

Additionally, marketing departments are often only consumers of tools and programs, not their designers. When a platform doesn’t do what’s needed or intended, marketers often aren’t able to fix the platform on their own. 

But marketing departments can help guide the use and implementation of AI by being more involved in decision-making early in its adoption.

What owning AI requires

Think big when adopting AI and treat it as a transformative tool that can unlock new products, customer relationships, and categories of work. Here’s how you can own AI adoption in your company as a marketer.

Run an AI usage audit

Create an inventory of how AI is being used in your marketing team right now: who uses it, on which workflows, with what data, and what budget to see where your company and department currently use AI before scaling up with it.

Write a one-page marketing AI charter

This mission statement will give a marketing department a blueprint for using AI, a solid plan to bring to the executive table when AI is discussed and planned.

Draw clear boundaries 

In your organization, establish a clear handoff line and state which decisions marketing is responsible for, as well as those of IT, legal, procurement, and other departments. Ambiguity in who is responsible for what will lead to workslop.

Start a cross-functional AI working group

Get all departments involved in AI adoption so no one works in a silo. If a cross-department group doesn’t exist in your organization, start one. Templatize operations and assign clear roles so everyone knows what their job is and there’s no confusion as to who is responsible for what.

Build, buy, wait 

A fail-safe strategy for using AI involves building brand equity, optimizing for AI-mediated discovery, and increasing marketing speed through capability investment. 

This strategy is constantly evolving as AI advances, but it’s important that marketing owns and implements it. Otherwise, they won’t have a say in their department’s involvement and may inherit a strategy that’s not suitable for them.

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Own AI and make a game plan now

Marketers need to own AI adoption, regardless of whether leadership does. Marketers have the ability to prevent workslop from happening and to create an AI strategy with measurable outcomes. It’s important to get involved at the beginning of the adoption process to help shape and decide what and how AI is used.