Artificial intelligence (AI) has begun to dramatically change the relationship between an organization and its customers. If it is implemented responsibly and ethically, AI can be used by organizations to increase the value provided to customers, patients and citizens through building a better understanding of prospects, personalizing interactions with customers and customizing products and services. According to a recent report from IBM, 77% of outperforming organizations cite customer satisfaction as a crucial value driver for AI. However, recent high-profile media and regulatory incidents emphasize the need for a responsible approach to both AI deployment and the underlying customer data. It is important that boards understand how radically customer expectations are shifting – both in terms of the service and personalization they are learning to expect from AI-powered firms and in terms of their sensitivity to what they see as corporate abuse of the same power.
Companies are using AI to improve their customer proposition by:
- Targeting the right customer at the right time with the right product: Traditional mass marketing is reaching its limits. AI means segmented and personalized propositions can be offered at scale. Prediction tools powered by AI help companies reach out to those customers who are more likely to buy their products at the right time. Online advertising platforms use AI to optimize and refine their targeting, placement and pricing propositions – driving new revenue for them and superior outcomes for corporate marketing teams. H&M has launched an AI-powered chat platform where customers can receive clothing item recommendations based on completing a short questionnaire.
- New service and product offerings: AI enables the creation of new businesses – for example, those offering medical diagnosis or superior recommendation engines. It can radically improve existing businesses, such as taxi services or hotel bookings, and provides new customer interfaces, for instance, the voice interactivity of Alexa. The use of AI to increase efficiency and effectiveness – to detect fraudulent activity on customer accounts, for example – will provide faster services, better products and, ultimately, lower prices. This will help create significant business model challenges for organizations.
- Augmenting workers: AI improves customer interactions through human and machine collaboration. Chatbots provide a low-cost opportunity to scale service (and sales) channels, but the customer experience is optimized by having human staff in the loop for more complex interactions. While AI is better at processing large amounts of data for analysis, human staffers are better at judgement and interaction with customers. As an example of AI supporting people, a Japanese clothing retailer improved its sales by 10–30% through using AI to optimize staff allocation.
However, there are growing concerns over transparency and privacy: The very detailed insights that AI offers companies in regard to their customers inevitably also raise challenges. There are two elements to this. First, concerns are evident in certain markets when data about individuals is not used responsibly or fails to meet privacy expectations. Second, the outcomes from AI-driven processes can be problematic, particularly if the AI’s process and output are not readily explicable. For instance, a customer might imagine that his or her loan was denied because an AI algorithm was biased. An organization using AI should consider not only how to increase customer satisfaction but also how to build customer trust. Emerging regulation, such as the GDPR, is a reminder that ethical and legal questions are especially focused on this aspect of AI.
This module will help board directors ensure management are examining AI’s potential to build better customer propositions, target them more effectively, deliver stronger service experiences and achieve higher levels of customer satisfaction. It provides directors with frameworks and questions to evaluate management’s actions independently in response to AI’s customer opportunities and challenges, the need to behave ethically and responsibly, and to prioritize the actions the board can take.
This section includes three tools to help directors oversee management’s competitive AI customer strategy and implementation.
The knowledge assessment tool helps board members rate whether they possess, or have access to, the knowledge required to independently judge management’s knowledge and leadership on AI customer strategy.
The performance review tool consists of questions boards can ask management about their knowledge of AI and customer strategy and the progress and performance of their actions. It offers the SCEPTIC framework to help directors assess the answers they receive.
The guidance tool offers possible suggestions for further action in an “If, then” format.
Ways to broaden board thinking
Feel the AI customer’s experience. Seeing/hearing is believing. After directors step outside the boardroom to discover what customers experience for themselves, hold a workshop on reimagining the customer experience.
Bring customers into the board meeting. Millennials could provide the boards with insights for the future.
Game alternative customer competitive scenarios. For example, what would the organization do if an AI-enabled, data-driven high technology firm (such as Google) targeted the customers in our industry (what would their playbook be? why would customers find this attractive? how would we react? what can we learn?). Alternatively, try to design the data-enabled “killer start-up” from a customer perspective.
Test for PR exposure. Consider what the worst-case scenarios would be for the organization in terms of data privacy and AI outcomes. How defensible – in front of a regulator, court or public opinion – are our positions? Bring in someone with journalistic or legal experience to see how these scenarios might play out.