A recent Gartner study found that 71 percent of Chief Marketing Officers (CMOs) lack sufficient budget to fully execute their plans. With their purse strings tied, many marketing leaders are being forced to explore new routes to success.
At this time, many have been looking to Artificial Intelligence (AI) to support more efficient growth, with more than forty percent of international marketers reporting AI has helped increase revenue and enhance performance.
In particular, there’s a lot of excitement about the impact generative AI could have on the industry. It’s been hyped extensively this year – and rightly so, with early adopters already unlocking benefits and suggesting exciting opportunities lie ahead. For example, estate agents in the US have been able to use ChatGPT to optimise their social media posts and enhance property listings. However, like in a game of baseball, if marketers don’t take a strategic eye to ensure all the bases are covered before they start to use ChatGPT in earnest, there’s a risk that a costly mistake will be made once the ball hits the bat.
Lining up the shots
Generative AI delivers a range of potential benefits for digital marketing. First and foremost is the amount of time and resources saved. Thanks to generative AI, many fundamental marketing processes, for instance, drafting advertising copy, can now be automated. In fact, 90 percent of marketers say AI is highly effective for content creation, and also saved employees just over three hours of their time on a single piece of content.
The technology can also dramatically increase audience engagement, by helping marketers to create more engaging campaigns through analysing customer preferences. This enables brands to focus on personalisation, so they can create a better customer experience. In fact, almost half of marketers noticed that content made with generative AI performed somewhat better than content created without.
All of this adds up to generative AI giving companies a competitive edge. By enabling more targeted marketing, it can help enterprises stand out from the crowd, and enable marketing departments to respond even quicker to changing customer demands.
While generative AI could transform key pieces of the digital marketing puzzle, it’s important that companies understand there are obstacles to overcome. As with any new technology, there’s a number of unique challenges that must be addressed.
One key underlying concern is bias and inaccuracy: generative AI models can unintentionally generate inaccurate content or sustain biases. One such example of AI inaccuracy occurring was when, as part of a research study by a lawyer, ChatGPT invented a sexual harassment scandal and named another law professor as the accused. It even went so far as to cite a fake Washington Post article as part of this completely fabricated claim.
AI bias or inaccuracies, as seen with this example, can have major consequences – not just reputationally, but also legally and financially. If an organisation is seen to perpetuate a certain bias or shares inaccurate data because of AI ‘hallucinating’, customer trust will be eroded.
There are also many ethical and legal compliance issues to consider. As generative AI models continue to evolve, there is a risk of data privacy violations, or generating inappropriate content. AI could also be used to generate content with malicious intentions – such as spreading disinformation.
The other big challenge is the implementation. It’s not uncommon for organisations to struggle when trying to integrate new technology with their IT infrastructure. This can lead to a massive outlay of resources and expertise to successfully deploy them. With generative AI being a new innovation, it’s likely there would be the same challenge. Lastly, generative AI requires human intervention and quality control, to ensure that AI-generated content is relevant, accurate and unbiased.
Covering all the bases
Granted there are a lot of challenges for businesses to guard against, but with the right approach they will be able to overcome them and unlock the benefits generative AI can bring to the digital marketing function. They should ensure they’re covering these four bases:
- Set clear goals: To make the most of generative AI, organisations should agree at a base level exactly what they want to achieve. This will make it easier to determine what function they expect generative AI to perform, and ensures it aligns with overarching marketing strategy.
- Fine-tune the model: For generative AI to perform at its best, it’s important the model is trained on an ongoing basis. They must feed the model the right datasets, and continuously monitor its performance.
- Focus on quality control: Any AI-generated material must be constantly tested and validated. This is crucial in ensuring accuracy and high-quality – it would be a huge mistake to simply wave it through, unchecked. To do this, organisations can use automation or have employees manually analysing and updating the model as needed. This involves evaluating performance metrics, user feedback, and other relevant data to ensure it’s always optimised.
- Combine AI with humans: Whilst generative AI will undoubtedly save time and resources, it’s important to combine it with human input to maintain quality, originality, and creativity.
Scoring a home run
For organisations that can harness generative AI such as ChatGPT effectively, the potential prize could be huge. They just need to ensure all the bases are covered so they don’t strike out by making simple yet costly mistakes that put them on the losing team. As with any new technology, the key lies in having a carefully considered strategy and roadmap for adoption, the support of business leadership to invest in new use-cases, and access to the skills and expertise needed to ensure success.
Those that get it right with ChatGPT will put themselves well on the path towards more efficient, effective, and engaging marketing campaigns that help to win the hearts and minds of their customers.