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Challenges and Risks

Implementing even the simplest AI applications can present difficulties. Stand-alone task-automation AI, despite its lower technical sophistication, can still be hard to configure for specific workflows and requires companies to acquire suitable AI skills. Bringing any kind of AI into a workflow demands careful integration of human and machine tasks so that the AI augments people’s skills and isn’t deployed in ways that create problems. For instance, while many organizations use rule-based chatbots to automate customer service, less-capable bots can irritate customers. It may be better to have such bots assist human agents or advisers rather than interact with customers.

As companies adopt more-sophisticated and integrated applications, other considerations arise. Incorporating AI into third-party platforms, in particular, can be tricky. A case in point is offered by Procter & Gamble’s Olay Skin Advisor, which uses deep learning to analyze selfies that customers have taken, assess their age and skin type, and recommend appropriate products. It is integrated into an e-commerce and loyalty platform, Olay.com, and has improved conversion rates, bounce rates, and average basket sizes in some geographies. However, it has been harder to integrate it with retail stores and Amazon, third parties that account for a high percentage of Olay’s sales. The Skin Advisor is not available on Olay’s extensive store site on Amazon, hampering the brand’s ability to deliver a seamless, AI-assisted customer experience there.

Finally, companies must keep customers’ interests top of mind. The smarter and more integrated AI applications are, the more worries customers may have about privacy, security, and data ownership. Customers may be skittish about apps that capture and share location data without their knowledge or about smart speakers that may be eavesdropping on them. In general, consumers have shown a willingness (even eagerness) to swap some personal data and privacy in exchange for the value that innovative apps can provide. Concerns about AI applications like Alexa seem to be dwarfed by appreciation of their benefits. Thus the key for marketers as they expand the intelligence and reach of their AI is to ensure that its privacy and security controls are transparent, that customers have some say over how their data is collected and used, and that they get fair value from the firm in exchange. To guarantee those protections and maintain customers’ trust, CMOs should establish ethics and privacy review boards—with both marketing and legal experts—to vet AI projects, particularly those that involve customer data or algorithms that may be prone to bias, such as credit scoring.

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While marketing AI holds enormous promise, we urge CMOs to be realistic about its current capabilities. Despite the hype, AI can still accomplish only narrow tasks, not run an entire marketing function or process. Nevertheless, it’s already offering substantial benefits to marketers—and in fact is essential in some marketing activities—and its capabilities are rapidly growing. We believe that AI will ultimately transform marketing, but it’s a journey that will take decades. The marketing function and the organizations that support it, IT in particular, will need to pay long-term attention to building AI capabilities and addressing any potential risks. We urge marketers to start developing a strategy today to take advantage of AI’s current functionality and its likely future.

 
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