If you've tried your hand at creating content with ChatGPT, you're not alone. According to a recent study, 48% of marketers now utilize AI for content generation.
Despite its impressive content generation capabilities, marketers must look beyond copywriting to unlock the full potential of Generative AI. Gen AI is a hugely powerful tool for marketing — and marketing budgets set to reflect this, with the IDC predicting that Gen AI investments will rise from $16 billion this year to a staggering $143 billion in 2027.
One major opportunity for Gen AI in the marketing process is in lowering the barrier to entry for advanced data analytics. While using ChatGPT for tasks like data collection, cleaning, and transformation might not be the most exciting use case, it's a boon for marketers. By automating these technical and mundane tasks, Gen AI can free up marketing teams to concentrate on more creative endeavors, while helping their marketing messaging to find the right audience.
In this blog we’ll explore the ways Gen AI could impact the marketing landscape, and the potential risks marketers need to watch out for. To hear more about the potential impact of Gen AI on marketing, you can check out the webinar we did with Forester on the topic here!
Five types of AI capabilities
With a host of mixed messaging around Gen AI, it can be difficult to differentiate between Gen AI and other forms of AI. So, let's draw a few practical distinctions between the different forms of AI capabilities that marketing is leveraging.
|
AI Capability |
Description |
|
Automation AI |
Automates repetitive routine tasks, functions, and workflows; individual capability and supporting element of other AI capabilities |
|
Perceptive AI |
Interprets and provides deep insights of existing data |
|
Predictive AI |
Makes quantitative predictions based on trends, patterns, correlations |
|
Prescriptive AI |
Recommends the next-best action based on context and historical data |
|
Generative AI |
Generates new content based on prompts and learned patterns |
Gen AI is particularly advanced because it has the capability to learn patterns and structures from training data, and create new content with similar characteristics. This breakthrough, driven by transformer-based networks in the early 2020s, led to the emergence of favorites like the Large Language Model (LLM), ChatGPT for chatbots, and Midjourney for text-to-image art.
Gen AI isn’t new, but it’s the most recent addition to this evolving set of AI capabilities. Where we really see Gen AI shine is in giving access to information on buyer behavior and preferences, and automating and orchestrating activities. However, before marketers get started using this powerful tool, they need to consider a few of the risks that come with it.
What are the risks of Large Language Models (LLMs)?
High-quality data is crucial for the accuracy and efficiency of Gen AI. It's not just about performance; it's also about mitigating risks. Let's break down the risks into input, model, and output.
1. Input risks
Gen AI models rely on vast amounts of data. Failing to comprehend and control factors like data security, privacy, and quality can pose serious risks. What you feed into these models determines the outcomes.
2. Model risks
These models may exhibit bias, toxicity, and disrespectful language if these elements are present in the training data. The inherent qualities of the data shape the behavior of the model.
3. Output risks
Poorly trained models fed with inadequate data can lead to leaked sensitive information, copyright infringements, and hallucinations—issues frequently making headlines. Such incidents not only create a negative experience for customers but also harm the brand and reputation.
The primary barrier to AI adoption is concerns related to data privacy and security. By understanding these risks, you can ensure your data is appropriately managed to control these issues, allowing you to confidently leverage the benefits of Gen AI for marketing.
Data governance is critical for an effective Gen AI strategy
The capability of Gen AI to identify patterns and trends and enable more informed decision-making is a huge opportunity for marketers. However, anyone using this technology before establishing excellent data quality will struggle.
The ability of Gen AI to extract meaning from existing data at scale is hugely beneficial — but it’s important to note that the quality of its outcomes is completely dependent on the quality of your data. It goes back to the old ‘garbage in, garbage out’ saying.
Marketers need to think carefully about their data governance strategies, particularly in regard to data ownership, quality, and security.
A few of the key questions marketers must consider before jumping into Gen AI implementation, include:
- Who’s going to be using the Gen AI tool and how can you ensure appropriate data access?
- Have you addressed data privacy and security concerns?
- Is your data of high enough quality for effective Gen AI implementation?
Gen AI models are trained on vast amounts of data, so evolving your data maturity and strategy is an essential step to get the value out of your Gen AI Investments.
How will Gen AI impact the future of work for marketers?
AI has been impacting the way we work for years and it will continue to do so with Gen AI. This is why we create and continue to improve technology — to make what we do and the work we produce better and easier to accomplish.
AI is such a powerful tool for helping organizations meet increasing audience demands for optimized engagement across multiple touchpoints and channels, and providing the insights that marketing needs so they can make smarter more accurate decisions. We're now seeing Gen AI starting to make much bigger strides in areas where it's been much less common before like CRM map and SEO. Marketers are starting to look beyond the content generation capabilities and are tapping into the full potential of Gen AI to solve some of their data challenges.
In so many ways we've been asking marketing to produce dynamic, real-time, personalized experiences at the speeds our audiences are demanding without giving them the tools that they need to be successful at this job. Gen AI will make these marketing tasks simpler. And while it might make some of our current marketing responsibilities and skillsets obsolete, it will create even more jobs and roles than we have now.
Gen AI is a tool for us to use. It doesn’t Implement itself, and it won’t do anything unless it's told to do so. It doesn't know if it did something right or wrong without a human in the loop, so humans will always be a part of this
So, with this in mind, the question we need to be asking isn't ‘How will Gen AI take my job?’, it's ‘How can we prepare our organizations with the right skills and insights to use this powerful tool?’. You can read more about this in our blog, 11 Skills Marketers Need To Unlock The Full Potential of Gen AI.
Tracking customer intent
Gen AI has the potential to significantly increase the value of intent data by including user prompts and making it easier to integrate intent into automated campaigns and content creation. In combination with other AI approaches, Gen AI will enable greater accuracy to track and evaluate contribution and engagement from different channels — which is a huge problem that marketers have been looking to solve. As the adoption of conversation intelligence widens we'll develop a stronger understanding of engagement strategies and weaknesses that will drive better coaching and training and development efforts to the specific needs of each individual.
Localization
Gen AI will likely also optimize the production of dynamic, real-time, modular content and offers, guiding marketing with specific engagement and messaging tailored to each scenario they're in. The increasing capability of dynamic localization of content will provide content owners with new options for this big problem that we see with supporting in region needs.
Conclusion
The way we interact with Gen AI will be a constant push and pull as new features evolve and we continue to test and gain more value from this technology. “Tech will inevitably become more marketer-friendly, and at the same time, marketers will become more data-savvy. First, we change the technology, then the technology changes us,” says Alexander Igelsböck, CEO of Adverity.
