Artificial intelligence (AI) has become a popular and sometimes controversial topic of late. Most people have found themselves leveraging AI capabilities in some manner already. However, questions about the efficacy of applying AI to business are still very much at the forefront of our conversations.
From customer service chat bots to automated recommendations based on search histories, AI is already a richly integrated part of the marketing landscape. Understanding how it is being used and the impact AI is making on purchasing behavior is of great value. While some companies may fear AI and the changes it is bringing to our industry, others have been harvesting the potential of AI from its early stages.
While AI offers unique possibilities for marketing and has incredibly powerful capabilities, it has equally significant implications for consumer privacy and data security. What do both sides of AI look like and how can we balance them?
The Harvard Business Review published an article in 2021 on AI’s marketing capabilities, breaking down how AI is used within the marketing and customer service industries. While a lot has evolved with artificial intelligence in the last few years, HBR’s overview offers a bird’s eye view of AI and its applications across business. It divides AI applications into four quadrants ranging from more advanced to less advanced AI and then isolated or integrated AI. Let’s look more closely at each.
- Less advanced, isolated AI: The most basic level of AI usage is less advanced, isolated AI which is made up of stand-alone task-automation apps. This includes services such as content production, customer service chat bots or email automation systems, which most consumers are already familiar with.
- Less advanced, integrated AI: The next level of AI includes less advanced, integrated AI systems. These involve inbound customer call routing or CRM-linked marketing automation systems. These systems are used to complete manual, repetitive tasks for customer relations, and they tend to increase productivity so human employees can focus on more complex, demanding tasks.
- Advanced, machine-learning apps: Next there are more advanced, stand-alone machine learning apps. Examples are the Behr color-discovery app or the Olay Skin Advisor, which are able to color-match customers’ specific wants and needs in a quick and automated way. These are employed within their own app rather than being integrated into a website or other application.
- Advanced, integrated machine-learning: The final level of AI systems and the most complex are the more advanced, integrated machine-learning apps. This includes software like e-commerce product recommendations, predictive sales-lead scoring in CRM, or programmatic digital ad buying. These platforms are able to greatly increase sales and offer personalized advertisement experiences for consumers.
Overall, Harvard Business Review finds that AI marketing tools are something brands should embrace rather than resist because they can improve sales, efficiency, and customer satisfaction. AI marketing systems can target specific consumer needs and wants, using machine-learning and data collection. . AI systems can accommodate customer service needs 24/7 without tiring or impatience, providing greater customer satisfaction. They can also motivate customers to complete a purchase and digital cart abandonment.
AI services can increase conversion rates by fivefold or more. -Harvard Business Review
It’s safe to say that AI marketing systems can be profitable and efficient for business, but concerns remain about the ethics of AI tools. Forbes released an article in 2023 bringing into question how businesses intend to balance AI’s need for data while also protecting consumers’ privacy and data security. While over 70% of customers expect a personalized experience, they also are wary of sharing their personal data and value privacy. This provides a strange dilemma for several businesses as they use AI tools to collect data but also aim to respect customer privacy.
As consumers become more aware of the value of data sensitivity, businesses must work harder to ensure their AI systems are ethical and respectful. Many consumers are also growing weary of data breaches, and while AI usage is increasing exponentially, more consumers are sharing their data with the world. As a solution, marketers are beginning to use services such as data clean rooms, which provide aggregated and anonymized user information so they can protect the privacy of their customers. There is also legislation in the works which may restrict AI usage of data and provide more security for consumers.
Whether you’re curious about artificial intelligence, already dabbling in its applications, or fully integrating it into your business or marketing services, it’s necessary to stay current with the latest advancements and implications to learn to use AI responsibly.