Over the past few years, artificial intelligence (AI) has emerged as a powerful economic and cultural force. While human creativity is still valuable, and expertise has more influence than ever before, smart computer systems continue to transform every aspect of society. AI and associated technologies are having a profound impact on digital marketing, with software systems increasingly used to predict exposure patterns, refine delivery mechanisms, and scale content creation.
Along with grunt work, the recent emergence of ChatGPT (Chat Generative Pre-Trained Transformer) has reignited interest in the creative applications of AI. It creates realistic text that appears — at least at first glance — to have been produced by a living and breathing human. ChatGPT raises interesting questions about the nature of creativity and depending on how it’s used, it also has potential real-world applications.
How is AI used in marketing?
Before we review the benefits and detriments of AI in digital marketing, we need to conduct a sober analysis of AI’s current capabilities. This exciting field often features the polarised views of zealots and sceptics, but like most things in life, the key to understanding lies somewhere in the middle. While there are tremendous opportunities for growth, AI is hardly a golden ticket. And while there are very real limitations, AI also holds great promise.
Along with ChatGPT, there are lots of great AI tools already out in the world. From hidden technologies in big-name products to specific AI-powered solutions, much of it works behind the curtains and needs to be augmented with human activity. Albert uses AI to optimise paid advertising campaigns, Cortex and Skyword are used to optimise content marketing, and Narrative Science and Automated Insights use natural language generation (NLG) to scale content creation.
AI currently does the following things very well in digital marketing:
Managing data
Computers are great at collating data, finding patterns, and uncovering relationships between diverse information fields. However, on a practical level, the value of AI depends on the availability of this data and the details of implementation.
Optimising messages
AI can be used to optimise all aspects of messaging and delivery. Personalisation has always been a key strength of digital marketing, with well-designed AI systems helping to optimise funnels and make things even more personal.
Predicting outcomes
As AI systems gain access to wider and more accurate information, they have developed an amazing predictive capacity. Modern computing systems have moved well beyond hard-coded rules, with statistical models now applied directly to predict outcomes.
Improving delivery
As we move further from general broadcast media to narrowcast social media, AI systems can be engaged to identify targets and deliver messages at the right times. While AI still struggles with creativity, it’s very good at delivering content.
Measuring results
Like many things in life, the success of digital marketing depends on constant tweaking. While AI systems lack self-awareness, they can make systems more efficient by altering relationships between inputs and outputs.
The creative use of AI
AI does some things extremely well, but there are severe limitations when it comes to actually creating content. While AI can produce usable marketing material, it creates a false impression of quality work and fosters a lack of human connection. ChatGPT and similar tools can be a great way to produce basic material fast, but real-world use always requires human intervention. Among other things, AI depends heavily on human expertise to load input material, shape working methods, and edit final results.
The following problems need to be addressed:
The creativity problem
Expectations surrounding AI are often unrealistic, especially when it comes to creativity. Despite initial impressions, even the best AI systems are completely incapable of anything that involves subjective thinking or conscious thought. The algorithms used by AI systems need to be designed, tested, and adjusted by humans; and without creative input, end results will be limited. For ChatGPT and other popular tools, this may present itself as a lack of emotion, lack of humour, lack of insight, or homogeneous structure.
The risk of plagiarism
Along with lacking creativity, ChatGPT and similar tools may also be risky. There’s a very real risk of plagiarism with AI, as all “new” content is actually generated from existing material. While humans often work in a similar way, actions like joining the dots, reading between the lines, or seeing the bigger picture are severely lacking in AI. For ChatGPT, intelligent “copying” is already affecting the education sector, and it could have serious commercial and legal implications in the months and years ahead.
Limits and inaccuracies
Along with a lack of creativity and risk of plagiarism, AI also has in-built limits. Many of the capabilities attributed to AI are fairly simplistic when it comes to real-world applications. While computing systems operate very efficiently when presented with information, they need instructions, adjustments, and controls delivered by human beings. ChatGPT may create endless content, but it’s always limited by data inputs and algorithmic structuring. Along with limitations, ChatGPT and similar tools may lead to rolling inaccuracies due to fast and efficient content proliferation.
AI systems are great at distributing and managing marketing campaigns. While AI can also be used during the creative process, generated material often feels like an imitation. AI content often lacks insight, humour, and emotion, which means people are much less likely to feel engaged. AI systems can be used successfully to build quick copy and generate new ideas, but the actual creative act of marketing is still very much in human hands.
Written by Ryan Jenkins.
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