Artificial intelligence (AI) can significantly enhance productivity and performance in service industries, as recent use cases demonstrate. To harness its benefits, service companies must ensure that AI is complementing the way their employees work, not disrupting it. Several challenges exist, including ensuring quality results, navigating regulations, and implementing AI at scale. In this Viewpoint, we share steps CxOs can take now to drive innovation and competitiveness through human-AI interaction.
In today’s dynamic business landscape, service industries grapple with substantial challenges, notably a prevailing labor shortage. As an example, the ifo Institute reported in August 2023 that a striking 75.3% of legal and accounting firms in Germany struggle to secure qualified staff as demographic shifts and other factors intensify the dynamics of the labor market. At the same time, 43.1% of German service companies face a shortage of skilled labor, underscoring the need for streamlined processes to enable specialists to focus on high-value tasks. Similarly, the US Chamber of Commerce reports that in the US, “Even if every unemployed person with experience in the financial activities or professional and business service sectors were employed, only 42% and 44% of the existing job vacancies in these industries would be filled, respectively.”
Rising customer expectations for quick responses, digital interfaces, 24/7 service, and personalized experiences further amplify the pressure. Amid these challenges, AI offers the means to enhance productivity and performance to navigate a fiercely competitive marketplace.
AI has evolved from conventional e-commerce applications to become an essential tool for optimizing processes in service industries. Recent breakthroughs in generative AI (GenAI) and large language models (LLMs) have expanded its applications, allowing automation to extend into creative and more complex tasks — and to take over the sphere of conversations. With these technological advances, a Goldman Sachs report estimates that up to 44%-46% of tasks in administrative and legal professions could be automated in the future. This transformative potential empowers service organizations to tackle industry challenges, providing a competitive edge by propelling productivity and facilitating continuous improvement.
To harness AI’s benefits, companies must ensure that AI is complementing the way their employees work, not disrupting it. But where can service companies get started? This Viewpoint highlights several use cases of early adopters in service industries that have leveraged AI to support daily operations and unlock substantial productivity potential, as well as key challenges and ways to overcome these when embarking on the AI journey.
AI is not a distant vision; it’s a present reality for today’s service industries. The critical question is not whether to adopt AI but how to harness its capabilities effectively. Pioneering companies have embraced AI, demonstrating its potential to revolutionize operations, boost productivity, and drive growth through a diverse range of applications.
In the insurance industry, where efficiency and accuracy are paramount, AI is reshaping the claims processing landscape. Early adopters have integrated AI and machine learning (ML) to streamline and enhance the speed of claims processing.
An innovative digital insurance company revolves its system around AI-powered chatbots. Using natural language processing, these chatbots accurately extract and categorize key details from policyholders’ descriptions and incident reports, enabling rapid processing of simple claims and ensuring quick payouts.
AI-driven systems improve accuracy in data analysis, minimizing errors in claim evaluations. This precision not only enhances the overall claims process but also boosts customer satisfaction. Additionally, the automation reduces manual work, allowing productivity gains and enabling specialists to focus on value-adding instead of transactional activities.
In the competitive landscapes of insurance and banking, personalization is a key differentiator. AI is enabling early adopters to enhance customer engagement by tailoring insurance plans to meet individual needs. Indeed, some global providers of insurance and financial services are harnessing AI-driven customer engagement to create a personalized experience. Analyzing customer data, including financial behavior, life events, and risk profiles, AI algorithms recommend insurance plans aligned with individual customer needs. For instance, approaching retirement age prompts recommendations for retirement-focused insurance products.
As AI-driven personalization can enhance customer satisfaction by meeting individual needs, it fosters long-term relationships and improves customer retention. Moreover, by analyzing customer data, early adopters of AI gain insights for more informed decision-making and targeted marketing strategies.
In the complex world of finance, data-driven decision-making is critical for success. A leading financial company is leveraging AI to revolutionize investment decisions. It is incorporating AI and ML to transform investment decision-making. Using AI-driven predictive analytics and alternative data sources like satellite imagery and social media sentiment, the company identify emerging trends to make informed decisions reacting to market movements. It also applies AI to algorithmic trading, executing trades at optimal times based on real-time data analysis.
AI-driven investment decision-making based on real-time analytics offers substantial benefits, such as increased decision accuracy, improved risk management, and streamlined portfolio adjustments. Furthermore, tailoring investment options to individual clients enhances trust and fosters strong client relationships.
These are just a few examples of many opportunities for service companies to utilize AI to yield quantum leaps in productivity (see Figure 1). The horizon of AI applications expands well beyond the use cases highlighted here, with GenAI as a potent tool for accelerating the enhancements of service processes and their back-end operations. Such future-oriented solutions demonstrate AI’s versatility and potential impact.
One such application involves conducting a meta-analysis of customer interactions with sales representatives. AI, through transcribing and analyzing extensive conversation data, identifies recurring patterns in customer buying behavior. This strategic insight aids in optimizing sales techniques and enhancing conversion rates, fostering successful sales interactions.
In another example, a forward-thinking European health insurance company is developing an AI-based knowledge management support system. Tailored for customer service representatives, this system leverages an extensive knowledge base, intelligent search options, and an intuitive interface to provide guidance on complex care situations. The outcome is a tangible improvement in efficiency and employee and customer satisfaction.
Another leading technical services provider harnesses GenAI to revolutionize knowledge management for intricate workflows. By transforming voluminous data and documents into standardized, user-friendly work instructions, including operating procedures and technical illustrations, this approach establishes a comprehensive knowledge base for field technicians. AI-generated guides seamlessly integrate with mobile SAP (Systems Applications and Products) systems, offering a systematic checklist for service tasks. Technicians can leverage the interactive human-to-AI interface for instant access to detailed service guidance, ensuring accuracy, optimizing performance, and adapting smoothly to evolving customer needs.
Although the potential is great, many service companies are encountering hurdles in realizing AI benefits. The inherent complexities and limited understanding of AI systems can erode trust, limit a focused implementation, and — in the worst case — introduce new critical business risks. Therefore, companies must understand four key challenges shown in Figure 2 and address them early on to ensure a successful AI scaling to create maximum value:
To overcome these risks and challenges during initial AI implementations, it is essential for companies to proactively define suitable strategies focusing on AI, including human-AI collaboration. In the following section, we outline six steps for CxOs to navigate these challenges and embark on a successful AI journey.
As the potential of AI continues to burgeon, CxOs must take decisive steps to seamlessly integrate AI into their organizations. Here are six key actions CxOs should take to begin their journey of AI implementation (see Figure 3):
By taking these first steps, CxOs can successfully integrate AI into their organizations to drive productivity, performance, and innovation and thereby stay ahead of the competition.
In a world where service industries face unprecedented challenges, AI emerges as an opportunity to enhance daily operations and revolutionize customer experience. The goal is not workforce replacement but capability augmentation, enabling growth, innovation, and competitiveness. This Viewpoint explores human-AI collaboration in service industries, highlighting the potential benefits, practical applications, and challenges for AI implementation. Service industry CxOs can harness AI’s power to:
By Marius Romanescu, Ronja Berger, Ronja Kallhammer, Max Adis