The advent of generative artificial intelligence is creating exciting innovations and experiences for consumers. Nonetheless, it also worries those who fear for data privacy and addiction to software robots. Moreover, these concerns are particularly acute in sectors where customer interactions and data privacy are essential, such as banking or healthcare.
Intrinsic risks that cause anxiety
It should be noted that a certain level of anxiety generally accompanies breakthrough technologies. In this case, it is natural to be concerned about technology that mimics human intelligence. However, with the emergence of a new category of large language models, most organizations have placed model risk, accurate results, and ethical data use at the heart of their concerns. Regulatory frameworks aim in particular to ensure the responsible use of new AI technologies.
However, the risk of businesses giving up customer experience to models and robots that are designed to extract value in the short term, not to foster long-term customer loyalty, is less appreciated. Businesses could increasingly combine traditional AI and machine learning models with generative AI to deliver messages and offers to customers in a more human way. If we are not careful, robots, algorithms, and profit-seeking predictive models could indeed lead to dystopian experiences.
The scope of customer relationships
Even in The world of AI, the customer relationship is fundamental. Traditional measures of customer sentiment, such as Net Promoter Score (NPS)), may start to change, but one principle will remain: each interaction improves or decreases the customer's perception of the company concerned.
Informing each decision in order to enrich the user experience will be a reliable path to an AI-based future that will create more value for customers, employees, and shareholders.
Personalization as a guideline
Orienting AI towards the customer requires a fundamental rethinking of objective functions. Most existing algorithms optimize the return on investment at a given point in time rather than the whole experience. AI-based customer engagement promises the business to learn more from each interaction and to find more ways to create value. In fact, this is a good sign, as customers increasingly expect personalized and relevant experiences and are ready to share their data in return.
One of the ways in which AI refines personalization is through digital assistants for customers, as evidenced by emerging efforts in banking and payments. For example, The Royal Bank of Canada is using an AI-powered assistant called NOMI to personalize the digital management of its customers' money. This includes timely advice, personalized budgets, and savings recommendations based on spending behavior and cash flow. Generative AI digital assistants also help employees strengthen their relationships with customers, strengthening places where the human touch can be a source of differentiation.
Large-scale language models will usher in a new era of personalization. Machine learning techniques are already transforming each customer's digital interaction model into a unique behavioral “fingerprint,” and recent advances in AI will now allow these fingerprints to include voice and text interactions.
Helping your employees help your customers
It is recommended that you start with a few concrete examples to make your organization feel comfortable using generative AI technology. These cases typically use AI to help employees who report aspects of the customer experience so that humans can verify the results of the model. These may include, for example, suggestions to relationship managers for the next conversation with a customer, based on a recent engagement, or specific actions for dealing with collections with customers in financial difficulty.
The next wave of cases would include AI integrated into standard operating procedures for employees. Some promising cases include predictive routing of a customer's request to the agent best equipped to deal with a particular problem or real-time script recommendations for relationship managers.
In a few industries, such as retail, technology based entirely on AI is beginning to take over customer relationships. Over time, this digital front line could provide service with the same empathy as traditional human teams. Little by little, robots will learn to offer relevant products and information to customers., as the best employees have always done. The best uses of AI could even completely reimagine the overall experience.
To conclude, in this period of high inflation and a tense economy, some leaders may be tempted to use generative AI technology only to reduce costs and improve efficiency. That would be a mistake. While generative AI has the potential to bend the cost curve in many industries, the greatest value will come from businesses that focus on enriching the lives of their customers.
About StoryShaper:
StoryShaper is an innovative start-up that supports its customers in defining their digital strategy and the development of automation solutions tailor-made.
Sources: StoryShaper, Harvard Business Review.
