4 Things Marketers Need to Know About AI

As AI tools like ChatGPT and Dall-e dominate the news, AI is predicted to contribute a staggering $15.7 trillion to the global economy by 2030. As a result, marketers are looking to AI in marketing to simplify processes and focus human energy on more impactful activities.

But thinking about AI as a tool for marketing — rather than a buzzword — can be challenging. It's with this in mind that we recently welcomed Paul Roetzer, founder and CEO of Marketing AI Institute, for a virtual event centered around how AI will revolutionize work — and what marketers can do today to prepare.

Read on below for four key takeaways from the discussion.

Talking about use cases for AI technology in 2023 is a bit like talking about use cases for the computer in 1970. If, in 1970, you had tried to explain the potential use cases for computers, you might have come up with examples like performing mathematical calculations on large data sets — which, of course, sells computers far short.

That said, clear use cases for AI in marketing do exist today – but they may not be the same as tomorrow's. When it comes to thinking about the best AI tools for marketers today, look for ways to improve or automate tasks that are at least one of the following:

• Data-driven (for example, using AI to gather zero-party data for the cookieless future of marketing)

• Repetitive

• Making a prediction (predictive analytics are most accurate when based on set data/trends)

Once you've identified use cases for AI, you can look into the type of AI solution that's best suited for your needs.

Read more onhow to identify the best use cases for AI here.

It isn't enough to explore an AI use case or two in an ad hoc manner. Future success with AI isn't (just) about, say, using generative AI to write taglines or web copy — it's about making strategic decisions and investing for the long haul.

Roetzer recommends working to define how to use AI-powered tools across key areas of your business — while remaining human-centric. AI should be a partner to marketers, not a replacement for them.

Businesses should build a full roadmap that outlines the right types of projects for AI optimization in current and future state. This may look different based on your industry; government agencies may have different use cases than commerce or financial services. No matter what industry you're in, C-suite direction and buy-in is critical here for building a truly AI-emergent organization.

Responsibility is paramount with regard to leveraging AI. Roetzer suggests that every company exploring AI use cases create a council charged with developing policies and best practices.

Doing so works to standardize an AI approach across the company and helps ensure your business is adequately considering the impact of AI across all functions.

Curious about this topic? Check out The Marketing AI Institute's Responsible AI Manifesto for Marketing and Business here, which is written by Roetzer.

Roetzer shares that it's hard to envision a "knowledge work" job that isn't impacted by AI in some way over the next several years.

The range of automation or assistance may vary – some might see 10% of their job altered, and others more like 50% - 80% — but a change is coming. It's a shift that we have every reason to be optimistic about, but setting up a successful future requires company preparation. Roetzer recommends that all businesses look at the people within their organization by job function and assess how AI might impact them.

The next step is to be proactive about education — upskilling and reskilling workers, as well as redistributing their time to valuable work as AI starts to play more and more of a role in rote activities. AI can be a net positive for both top-line business and individual workers, but that comes from responsible education and preparation. Partnership on AI is a great resource for these action items.