AI Adoption Trends in Customer Service

The past two years have seen a massive surge in artificial intelligence, especially generative AI and large language models (LLMs), leaving companies and customer experience leaders to rethink how they create exceptional experiences. With the huge amount of personalization that AI enables, it’s now possible to anticipate customer needs and address them across channels. Today, conversational AI chatbots, human agent-assist copilots, automated workflows, and business intelligence analysis of engagement data are helping brands level up their contact center capabilities.

One of the hottest trends is the use of predictive analytics for customer experience (CX), to anticipate customer issues and provide solutions before problems escalate. However, obtaining accurate, relevant data with strong predictive power is crucial. Companies often focus on predictive analytics before having their data structures in order, which rarely yields results. Consolidating existing tooling to develop consistent sources of truth for every step of the CX journey is essential.

AI might provide the biggest quantum leap in predictive analytics for CX in history, and we’ve barely begun to scratch the surface. Unstructured data is a major problem in CX, and AI offers a great solution. Popular LLMs and small language models provide the necessary tools to understand unstructured data and create meaningful structured data points quickly and efficiently. Financial service firms use predictive AI to evaluate customers’ behaviors, payment patterns, and interactions to proactively determine when they might be at risk of falling behind on payments.

Predictive AI involves gathering and analyzing relevant customer data from various sources. Though technically possible before the current age of AI, today’s technology does it much quicker and easier. AI helps with causal inference to understand and predict customer behavior. Causal inference techniques are changing how companies analyze customer data and identify the underlying factors that drive customer actions and preferences. By understanding cause-and-effect relationships, businesses can predict future behavior more accurately and make informed decisions to enhance customer satisfaction and loyalty.

The AI market is projected to reach $407 billion by 2027, experiencing substantial growth from its estimated $86.9 billion revenue in 2022. AI is expected to contribute a significant 21% net increase to the United States GDP by 2030, showcasing its impact on economic growth. ChatGPT’s remarkable adoption rate is evident as it garnered 1 million users within the first five days of its release. It is expected that 10% of vehicles will be driverless by 2030, as the global market of self-driving cars is forecasted to increase from 20.3 million in 2021 to 62.4 million.

The power of personalization is only going to become more important as we move into 2024. Businesses will need to achieve this on a grand scale. According to Adobe, 89% of marketers report a positive ROI when using ultra-tailored personalization techniques. Imagine a retail clothing store using AI tools to analyze customer data, identifying individual fashion preferences and sizes. This could allow them to tailor email marketing campaigns to each customer, recommending items that align with their unique style and fit.

Customers interact with businesses through multiple channels, expecting a seamless experience across all touchpoints. The omnichannel customer experience approach has been preached as a best practice for a while, yet many businesses continue to struggle with its practical application. The year 2023 has experienced a dramatic transition in AI, presenting it as a critical year of evolution for enterprises and individuals alike. In the face of rapidly emerging technologies and the era of generative AI, now is the time for strategic adoption.

At Born Digital, we are constantly investigating the latest AI trends in customer service. Knowledge Base Advisors operate without artificial intelligence, following a predefined path. These chatbots are effective in handling closed-ended questions and are cost-effective and simpler to implement compared to conversational AI chatbots. However, their reliance on a rule engine makes them susceptible to challenges in navigating the complexities of human language.

The drive for personalization is stronger than ever, with 73% of customers expecting customer service representatives to understand their specific needs. Analytics play a critical role in decoding customer behaviors, enabling hyper-personalization in service delivery. AI tools are becoming adept at predicting customer needs and customizing interactions based on past interactions and preferences. By leveraging these insights, companies can deliver a bespoke service experience that exceeds customer expectations.

Visual AI, particularly in the form of digital humans or personas, is redefining the customer experience by adding a human touch to digital interactions. These AI-driven personas can simulate human emotions and expressions, providing a more engaging and personable interaction than traditional chat or voice interfaces. In the digital landscape where brands are fighting for consumer engagement, digital personas represent a fusion of technology and human-like interaction, projected to be embraced by brands aiming for AI-based selling and superior customer experience.

Drive innovation with intelligent AI and secure blockchain technology! Check out how we can help your business grow:

Blockchain App Development

AI Software Development

Discover how our expertise can help your business grow and thrive in today's digital landscape!