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Artificial intelligence is a hot topic right now, and industries from finance to healthcare to retail are rushing to adopt it or risk being left behind. But as a business professor, I think some companies are jumping the gun.
Our recent research shows that service providers shouldn't automatically jump on the AI bandwagon, but rather make choices based on strategy. In other words, when it comes to AI and service companies, more is not better.
Why service providers face a different calculation
Are you a manufacturer? If AI can reduce costs without compromising quality and give you the return on investment you need, give it a try.
But service businesses — businesses that do things for customers rather than making a physical product — are different. Unlike manufactured goods, services are “co-produced” by customers, who can make something as simple as ordering a pie complicated.
Customer interactions are subject to what scholars call customer interaction uncertainty, and that uncertainty stems from two sources: the scope of the interaction with the customer and the fact that customers may want different things and therefore the range of services offered may vary widely.
For example, think of a restaurant: customers order what they want, combine different dishes to their liking, and eat the food when it arrives. The customer may make a wrong decision, but the restaurant has no choice but to comply.
If you allow customers to interact with the server, or even worse, the cook, they might ask for substitutions, ask questions about ingredients, or try to convince you to make something special. That doesn't happen if you limit customers to choosing from a set menu on a tablet. Continuing with this analogy, restaurants can offer a few standard dishes or many dishes that customers can customize.
If you're in the service industry, you've already made different choices based on your customer interaction strategy. For example, say you run a financial services company. Is your office designed to be comfortable and convenient for your customers and accommodate lengthy meetings to discuss their needs? Or do you limit the time you spend with customers and handle them over the phone or an app?
Similarly, do you limit the services you offer so that you pretty much know what you'll do with each customer? Or do you vary your services significantly depending on the customer's needs and choices? For example, consider a CPA and a tax preparation app.
Doing business in an uncertain world
How much uncertainty are you willing to allow your customers to introduce into your production process? This will be one of the main factors in deciding whether to adopt AI in your service business.
To understand why, let's take a brief detour to what scholars call information processing theory. This research suggests that organizations deal with uncertainty by leveraging knowledge to mitigate risk. A central challenge for service firms is to leverage knowledge in service production.
Individual knowledge (also known as human capital) reduces uncertainty in service production by allowing human workers to solve problems and meet customer needs. But there's a problem with human capital: it belongs to the employee, not the company, and it's not scalable. On the plus side, customers still value human interaction.
The other form of knowledge is called “organizational capital” – codified knowledge that is owned by the company itself. Organizational capital has inherent advantages: it belongs to the company and it is scalable. AI, as a form of organizational capital, clearly has these advantages.
Information processing theory offers three approaches to organizing knowledge to deal with uncertainty.
The first is having rules and programs, which is a form of organizational capital. The second is having a hierarchical structure, where front-line employees escalate complex problems to more knowledgeable managers. The third is goal-oriented coordination, where companies can deal with uncertainty by giving lower-level employees decision-making autonomy based on overarching organizational goals. The last two rely on knowledgeable and experienced employees – human capital.
Here's how this applies to service strategies: Most often, companies with few consumer choices and limited customer interaction use organizational capital. Today, that usually means rules and programs plus technology solutions. Companies with a broad product offering but limited customer interaction use hierarchical structures in which challenges are passed up the chain. And companies with both a broad product offering and high customer interaction use front-line knowledge workers aligned by targets or goals.
Technology may enhance the latter two modes, but offering a wider range of services and greater customer choice comes at the cost of making companies more reliant on human knowledge workers.
Strategic Use of AI
AI is a sophisticated form of organizational capital that can reduce uncertainty in customer interactions. Companies can own and scale AI. But AI is still bound by rules and datasets, and there are uncertain areas where human capital still has an advantage: finding creative solutions, connecting disparate concepts, and understanding the nuances of human interactions.
The challenge is to drive all of this strategically, combining customer strategy with human and organizational capital in an integrated way. We've come up with four rules that we think will help:
- Strike a strategic balance. For predictable tasks like payments, automation improves efficiency and is rarely sacrificed. But complex and diverse customer needs require human expertise and the flexibility and empathy that comes with conversation. The best approach is often a balanced integration of the two, with automation supporting routine tasks and humans handling the nuances that automation can't handle.
- Leverage your strengths. Use AI to navigate tasks like data analysis and decision-making processes where objectivity and comprehensiveness are crucial. This ensures accuracy and reliability in services like finance and healthcare, where mistakes can have big consequences. But prioritize human interaction to build and maintain strong customer relationships in services where trust, personal relationships, and reputation are crucial.
- Look for opportunities for synergy. Foster a dynamic interplay between human capabilities and AI technologies, allowing them to learn from each other. This not only enhances current operations, but also fosters an environment in which both humans and AI can evolve. This allows your company's knowledge base and ability to adapt to continually expand, giving you a sustainable competitive advantage over your competitors.
- Consider the situation. Evaluate your customers' specific needs and values to determine the right mix of human and technological resources. Recognize that this balance may change over time as technology advances and customer expectations change.
By following these guidelines, service companies can navigate the complexities of integrating AI into their operations and leverage the best of all worlds to meet customer needs effectively and sustainably.
David Cohen is an associate professor of management and business at Skidmore College.
Christopher Meyer is a lecturer in the Zicklin College of Business and an adviser to the Lawrence N. Field Entrepreneurship Center at Baruch College, City University of New York.
Sudheer Nair is Associate Professor of Business at Victoria University.
