Use of artificial intelligence (AI) in marketing isn’t a new phenomenon with over half of marketers in the UK currently using it (51%), and 27% expecting to deploy AI technology in 2019.
Indeed, PwC predicts that use of AI could add $15.7 trillion to the global economy by 2030, so it’s a tool that marketers need to take seriously.
To the uninitiated, this new technology can sound a bit complex and inaccessible, so what is it and how can it be used for the benefit of business?
AI marketing leverages large amounts of data using computer and algorithm learning, or machine learning, in order to achieve certain marketing goals.
By using machine learning, deep learning and natural language processing (NLP), AI is becoming an increasingly important tool for marketers in the data-driven decision-making process.
When it comes to targeting existing or potential customers, particularly time-poor millennials, being able to produce more personalised, bespoke content is essential. By being more targeted with marketing in this way, marketers can gain a competitive edge whilst creating a more bespoke consumer experience of their brand.
AI is also used in sentiment analysis to glean information from websites and social media interaction to improve a customer’s experience of a product or wider brand. Not only this, it can improve business processes and efficiency by automating some of the more burdensome of business processes.
This allows resources to be deployed effectively elsewhere within businesses, improving workflow and, ultimately, benefitting the customer.
Provided marketers can lobby for the investment necessary to deploy AI effectively, the benefits of it are clear. However, it can also present businesses with a number of challenges and threats too.
Take Microsoft’s AI chatbot ‘Tay’, for example. In 2016 it took Twitter less than 24 hours to corrupt the chatbot into posting racist and inflammatory posts, based on its interactions with people on the social media platform.
More recently, Amazon’s Alexa recorded a private conversation its ‘owners’ were having and emailed it to one of their acquaintances without them knowing.
These examples of AI ‘taking control’ demonstrate that there is clearly an awful lot for us still to learn about it, what it does and shouldn’t learn, and how the knowledge it amasses is used.
Not only this, very little has been done to explore the ethical boundaries of AI in terms of what is and isn’t ethically acceptable when using the data derived through AI.
Take the example of US retailer, Target, which using AI in its customer tracking, inadvertently alerted a father to the pregnancy of his teenage daughter.
With the help of statistical genius Andrew Pole, Target helped to predict whether a customer was pregnant by identifying 25 products, which bought together, would indicate a woman was likely pregnant.
This allowed Target to send coupons to the pregnant women – except that in the case of the teenager, it was the father who discovered them and her subsequent pregnancy!
Where does this fit ethically in terms of privacy and data protection? Is it acceptable for retailers to use AI to sell to customers in this way? Where do we draw the line on what is an acceptable level of intelligence to derive through AI and how this is manipulated for the benefit of business?
These are all questions which make deployment of AI within businesses a harder sell for marketers to senior management, especially those who are more reactive to change.
However, there are early adopters out there who are willing to embrace this innovative technology and many businesses are putting AI at the heart of their marketing strategies, such as Sony’s new Chief Executive, Kenichiro Yoshida, who recently commented:
“The data mega players [such as Google, Amazon and Facebook] are so powerful they are capable of doing all kinds of things…The big challenge for our survival lies in the extent to which we can take control of data and AI.”
With the right evidence and a strong business case, there’s no reason why AI can’t be leveraged to some extent by businesses – small or large.
However, more empirical research around ethical boundaries in AI is needed, alongside proper regulation which will help to reassure marketers and their senior management teams that investment in this technology will reap the right reward.