Artificial intelligence (AI) has dominated conversations in the marketing industry perhaps more than any other topic over the past year. With the rise of easily accessible AI tools such as ChatGPT, it has gone from just a buzzword to a legitimate capability that has captured the attention of forward-looking advertisers and fundraisers. Nevertheless, the overwhelming confusion and misconceptions around AI need to be addressed.
So we spoke with a panel of experts from across the Wiland team—Will Clayton (SVP, Digital Products), Cameron Popp (VP, Solutions and Innovation), and Hayley Howard (Director, Predictive Client Solutions)—to gain their perspectives on the role of AI in data-driven marketing. They discussed how Wiland is using AI to create high-performance marketing audiences and enhancement data, what marketers and fundraisers need to consider to ensure the ethical use of AI, and what the future may hold for this exciting technology.
How have you seen perceptions about AI evolve in recent years?
Cameron: “AI has been in use for decades, but the recent conversation around it doesn’t always reflect the reality of its evolution in marketing and other use cases. This is evident in how many misconceptions remain, such as AI being synonymous with ChatGPT, that AI is a new technology, or that AI will be taking people’s jobs. It’s amazing how rapidly AI has come into focus in recent years not just as a tool, but as a cultural phenomenon. It will be interesting to see how the AI conversation will change over the next twelve months.”
Will: “Think back to when IBM taught its ‘Watson’ to play (and win) on the TV game show Jeopardy in 2011, which was a paradigm-shattering moment for AI. I think that AI had been considered a limited technological agent prior to that. But then people started thinking more about the potential for AI to move beyond reacting to ‘if’ and ‘when’ statements and better understand and ‘speak’ human language. AI has been used in the marketing industry to analyze data for a long time, but that interest has spiked recently because of advances in ‘consumer-grade’ AI. Recent Generative Pretrained Transformer (GPT) systems from OpenAI and others are showing signs of what we’d actually call intelligence within very user-friendly products.”
Hayley: “I agree. AI may have just burst into the zeitgeist in recent years with the introduction of easily accessible public tools, but the recent popularity of the term also draws attention to how AI has been used with great success in optimizing marketing solutions for many years.”
Is there misinformation about AI that you think needs to be corrected?
Hayley: “Yes. The over-use of ‘AI’ as a term has created a lot of confusion and oversimplified a very complex topic. There are multiple forms of AI that are used to solve many different problems.”
Cameron: “The biggest hurdle for responsible AI adoption right now is confusion about what AI can do and how to harness its capabilities. For instance, AI doesn’t ‘do’ anything by itself. Instead, it does what its creators have programmed it to do and what its users instruct it to do. Thinking of AI as a broader set of tools is the first real step to fixing misunderstandings about how to use it.”
Will: “I think that the biggest misconception about AI is that it will take away people’s jobs. This type of fear has accompanied every major technical advancement in recent history, and the opposite ends up being true. As with other technologies, AI can help with handling the ‘heavy lifting’ of many tasks for operators, which will actually help them move up the labor value chain and devote more of their time to strategic thinking and product enhancement.”
How would you define AI and machine learning?
Cameron: “This is a great question, as AI and machine learning actually encompass a large variety of different specific technologies that roll up into these umbrella terms. It’s important that we use precise language to talk about AI.”
Hayley: “We actually discussed this in a blog post back in 2021, and the definitions used there are still accurate and relevant. In that piece, we defined AI as a software program that makes its own decisions about how to solve a problem or accomplish a task within a set of rules determined by a data scientist. There are two primary types of AI: Artificial General Intelligence (AGI) and Artificial Narrow Intelligence (ANI). AGI is the human-like intelligence that you often see in science fiction movies. ANI—also known as machine learning—is the real-world AI that operates within Wiland’s analytics platform. It is a crucial element in creating custom-modeled audiences with the highest likelihood to engage with and respond to a brand’s marketing. Essentially, machine learning is a type of AI that iterates on a task in massive cycles to improve performance.”
Within the realm of marketing and fundraising, who stands to gain the most from advances in AI?
Cameron: “Honestly, everyone! But it’s all dependent on two things: first, the quality of the underlying data sets being used, and second, how well the AI-driven solutions are implemented.”
Hayley: “I agree that any marketer or fundraiser can benefit from using AI-driven solutions. AI can be leveraged to target campaigns more effectively and make them more accurately personalized based on audience preferences and behaviors. This improved targeting drives more efficient marketing and helps organizations better reach the individuals most likely to engage. AI should drive ROI!”
Will: “AI stands to fill in large swaths of tactical analysis and marketing production tasks. But the organizations that stand to benefit the most from AI will be distinguished by two factors: strategic acumen and high-quality data. AI is not magic. It’s crucial that managers are able to understand how their teams can best use AI and then ensure that the AI is being applied to the most relevant, impactful data to achieve positive results and long-term success. In some cases, that means working with a partner who has the AI acumen or the data that a brand or nonprofit needs but may lack internally.”