But jokes aside, AI is undoubtedly one of the most important transformational forces of a generation. Jobs are being reimagined, processes automated, and workstreams accelerated. There isn’t a single industry that isn’t enthusiastically trying to explore and figure out how to integrate it into their existing business flows – with new use cases being discovered as quickly as there are platform updates, as everyone aims to be the most talked about brand in the space.
So that brings us to the topic at hand. How are our fellow marketers currently utilizing it to their advantage? Interestingly, according to data from Hubspot, 72% of marketers say that they believe AI and automation will make teams more productive, but only 35% are actually putting money where their mouths are by actively experimenting in the space.
So why the disconnect? There’s a whole laundry list of reasons, but the three at the top of the list include:
- Fear around privacy and copyright issues (that’s a whole other debate that we’ll cover off in a future blog post, but it’s like the Wild West out there currently – with the exception of a couple of good eggs like Adobe Firefly, Getty Images, and Shutterstock who are proactively taking steps towards prioritizing ethical generative AI development, ensuring fair compensation for creators, and setting the standard for the entire industry), with antiqued copyright laws and regulation desperately trying to play catch up with the speed of the constantly evolving technology.
- Lack of technical knowledge in effective prompting or being able to keep up with all the different AI offerings out there, leading to lackluster outputs versus their original expectations.
- Bias can creep into its code. This happens when the data used to train the model is not representative of the reality it’s meant to model. Google’s Gemini team recently had to apologize for what it described as “inaccuracies in some historical image generation depictions.”
But for those early adopters that have embraced the technology, here’s what three such marketers that I interviewed shared about how they’ve been using it in their daily workstreams:
- Improving customer targeting profiles by asking ChatGPT to build a persona of a C-suite executive that they are trying to reach, and then including detailed attributes from 1st party non-confidential data on what they should consider while building said profile.
- And then taking it one step further, by creating personalized content at scale for ABM campaigns by utilizing said personas. The difficulty in running ABM campaigns usually stems from the sheer amount of content that needs to be created for it, but generative AI can help with most of the heavy lift on this front.
- Using Midjourney to bring to life creative or production concepts to internal stakeholders that are more visually driven to get internal sell in for budgets.
- Time consuming research by asking tools like Adobe to summarize and extract key highlights from PDF documents like market reports.
- Ad optimization by creating and testing various sets of copy and creative through automation in performance marketing campaigns.
And the above is just the tip of the iceberg of potential use cases. As with all things in life, will it be perfect? No. Will it be biased? Maybe. But it’ll help you get the job done – hopefully faster and with a little less pain, so that you can free up time to focus on other higher-priority deep-thinking tasks.
So what’s the key to leveraging all of this? First and foremost is to identify the problem that you’re trying to solve for, then try to find the right technology solution to help bridge said gap and execute in the most efficient way to get the best output.
Need a helping hand in navigating the space? That’s what we at Futures Hub are here to help marketers like yourself do. Reach out to us at [email protected] for a chat about the above and more!
