Artificial Intelligence (AI) has gone mainstream when it comes to customer interactions, according to a new report from the Capgemini Research Institute. More than half of customers (54%) have daily AI-enabled interactions with organisations – a significant increase from the 21% reported in Capgemini’s 2018 research on the subject.
The report, ‘The Art of Customer-Centric Artificial Intelligence: How organisations can unleash the full potential of AI in the customer experience’, reveals the factors that have significantly contributed to AI adoption among customers, including increasing customer trust in AI; an increase in human-like AI interactions; increasing customer concerns arising from COVID-19; and organisations stepping up their AI deployments.
COVID-19 has accelerated customer adoption of non-touch AI-based systems, such as voice assistants and facial recognition – a shot in the arm for AI adoption. Over three-quarters of customers (77%) expect to increase the use of touchless interfaces to avoid direct interactions with humans or touchscreens during COVID-19, and 62% will continue to do so post-COVID. This figure is even higher in countries such as Germany (73%) and Brazil (71%). The fact that touchless interfaces are becoming integral to the customer experience in a health and safety-conscious world is also recognised by organisations: 75% believe that increasing customer appetite for non-touch practices will persist even in the post-pandemic world.
Customers have significantly increased their preference for AI-only interactions; Kelly Anderson, Director, Data Science and Artificial Intelligence at Procter & Gamble confirms this saying, “I believe that customer expectations have evolved to the point where they almost expect for interactions to be AI. So, when you actually put a human in the loop, they are very pleasantly surprised and sometimes shocked. This clearly shows that chatbots / Natural Language Processing /AI are making progress and have evolved.”
From a sector perspective, Automotive (64%) and Public Sector (62%) stand out as the strong performers. The widespread usage of in-car voice interfaces explains the dominant position of automotive, in part. For instance, BMW, which has been deploying its own in-car AI based voice assistants for many years, plans to make them more natural, with gesture recognition or gaze recognition capabilities for its 2021 series[1].
Trust and human-like interactions have improved
Trust was identified as an area for improvement in 2018 and the latest research reveals that organisations have made great strides in this area. Over two-thirds (67%) of customers trust the personalised recommendations and suggestions provided by AI-enabled interactions. Moreover, close to half of customers (46%) find AI-enabled interactions to be trustworthy – compared to 30% in 2018, while the share of customers who say that they do not trust machines with the security and privacy of their personal data has dropped to 36%, down from 49% in 2018.
Customers also wanted more human-like AI interactions, and organisations have progressed here too. Overall, 64% of customers believe that their AI interactions are more human-like (compared to 48% in 2018). China (74%), Australia (72%) and the US (70%) lead in the percentage of them who believe that their AI interactions are more human-like. Organisations have been consciously trying to build human-like features into AI applications: 72% of organisations agreed that they are actively trying to make their AI interactions more human-like.
“Context-aware” AI use cases hold the key to dropping customer satisfaction levels
While customers have increased their AI interactions since 2018, their level of satisfaction has dropped. Overall, 57% of customers are satisfied with AI interactions, compared to the more than two-thirds (69%) who were satisfied in 2018. Additionally, 51% of customers say they will consider an AI experience to be positive if it provides a unique experience beyond their expectations.
The research found that more customers are satisfied with “context-aware[2]” use cases and receive greater benefits from them than those with the rest of the use cases. Examples include autonomous parking of cars, detecting fraudulent banking transactions, and making payments authenticated through biometric scanners.
Most organisations measure AI performance in customer experience with basic KPIs
Few customers have experienced AI in a way that far exceeded their expectations. This can be linked back to the fact that a majority of organisations (73%) only follow a basic KPI (key performance indicator) for measuring customer experience, which only looks at the number of customers served by AI interactions. Organisations must add measurement and feedback management into AI design and development, cites the report, so that AI systems can deliver their true potential of learning and improving over time.
The future of customer experience
Capgemini’s study from 2018 found that most organisations (93%) had less than 30% of customer interactions enabled by AI. Today, only 10% of organisations are at that low bar, with 80% saying that 30% to 50% of customer engagements are AI-enabled. According to the report, in two to three years’ time, the vast majority (80%) will have more than half of their interactions enabled by AI.
“Usage of AI for customer experience is clearly here to stay. COVID-19 has been a catalyst in moving organisations towards AI implementation, and changes in customer behaviour mandated by the crisis have created a clear opportunity to scale AI implementations,” says Darshan Shankavaram, Head of the Global Digital Customer Experience Practice at Capgemini. “However, it is integral that businesses focus on using AI to delight their customers and create better interactions and experiences, rather than simply using it to address volume or as a technology innovation. Going forward, we expect to see customer satisfaction improve and their openness to using AI further along the customer journey increase.”
To read a full copy of the report and its recommendations, click here.
Research methodology
The Capgemini Research Institute surveyed 5,300 customers across twelve countries: Australia, Brazil, China, France, Germany, India, Italy, Netherlands, Spain, Sweden, the UK, and the US. It also surveyed 1,060 business leaders from large organisations with at least $1 billion in 2019 annual revenue across a range of sectors and countries. In addition, the Institute also conducted in-depth interviews with industry executives and two virtual focus group discussions with end-customers.
About Capgemini
Capgemini is a global leader in consulting, digital transformation, technology and engineering services. The Group is at the forefront of innovation to address the entire breadth of clients’ opportunities in the evolving world of cloud, digital and platforms. Building on its strong 50-year+ heritage and deep industry-specific expertise, Capgemini enables organisations to realise their business ambitions through an array of services from strategy to operations. Capgemini is driven by the conviction that the business value of technology comes from and through people. Today, it is a multicultural company of 270,000 team members in almost 50 countries. With Altran, the Group reported 2019 combined revenues of €17billion.
Visit us at www.capgemini.com.
About the Capgemini Research Institute
The Capgemini Research Institute is Capgemini’s in-house think-tank on all things digital. The Institute publishes research on the impact of digital technologies on large traditional businesses. The team draws on the worldwide network of Capgemini experts and works closely with academic and technology partners. The Institute has dedicated research centers in India, Singapore, the United Kingdom and the United States. It was recently ranked #1 in the world for the quality of its research by independent analysts.
Visit us at https://www.capgemini.com/researchinstitute/
[1] Source: Techcrunch, “BMW makes interacting with your car’s AI system more natural,” February 2019.
[2] Context-aware use cases are defined as the use cases that customers find more personalized, empowering, and effortless to use.