4 Things Marketers Need to Know About AI

**As AI-powered technologies like ChatGPT and Dall-e dominate the news, predictions show that AI is set to contribute a staggering $15.7 trillion to the global economy by 2030. As a result, marketers are already looking at how they can work hand-in-hand with machines to simplify processes and focus human energy on more impactful activities. But thinking about AI as a true business tool — 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.

1. Marketers must consider the right AI use cases As we wrote recently, talking about use cases for AI 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, there do exist clear use cases for the AI of today, not tomorrow. When it comes to thinking about where a business should leverage AI first, look for ways to improve or automate tasks that are at least one of the following:

• Data-driven
• Repetitive
• Making a prediction (based on set data/trends) If you're interested in diving deeper into use cases for AI, Click here to download our full Four Essential AI Use Cases guide.

1. Build an AI roadmap for your company 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, asking ChatGPT to generate taglines or web copy — it's about making strategic decisions and investing for the long haul. Roetzer recommends working to define how to infuse AI across key areas of your business — while remaining human-centric. Businesses should build a full roadmap that outlines the right types of projects for AI optimization in current and future state. C-suite direction and buy-in is critical here for building a truly AI-emergent organization.
2. Create an internal AI Council Responsibility is paramount with regard to AI implementation. Roetzer suggests that every company exploring AI 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.
3. Focus on education and training for your teams — now 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. Looking for a resource on these types of action items? Click here. CTA For more tips on setting your organization up for success in the AI future, check out The CMO's Guide to Innovating with AI.**