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- Generative AI is unlike any technology that has come before. It’s swiftly disrupting business and society, forcing leaders to rethink their assumptions, plans, and strategies in real time.
- To help CEOs stay on top of the fast-shifting changes, the IBM Institute for Business Value is releasing a series of targeted, research-backed guides to generative AI, on topics from data cybersecurity to tech investment strategy to customer experience.
- This is part two: Customer service.
Generative AI is unlike any technology that has come before. It’s swiftly disrupting business and society, forcing leaders to rethink their assumptions, plans, and strategies in real time.
To help CEOs stay on top of the fast-shifting changes, the IBM Institute for Business Value is releasing a series of targeted, research-backed guides to generative AI, on topics from data cybersecurity to tech investment strategy to customer experience.
This is part two: Customer service.
Generative AI is unlike any technology that has come before. It’s swiftly disrupting business and society, forcing leaders to rethink their assumptions, plans, and strategies in real time.
To help CEOs stay on top of the fast-shifting changes, the IBM Institute for Business Value is releasing a series of targeted, research-backed guides to generative AI, on topics from data cybersecurity to tech investment strategy to customer experience.
This is part two: Customer service.
No single area of an organization provides a better foundation to demonstrate generative AI success than customer service.
The interplay between AI tools, human agents, and customers offers CEOs a distinctive opportunity to generate value while building operational proficiency in new ways of engaging.
The IBM Institute for Business Value has identified three things every leader needs to know:
1. Customer service has leapfrogged other functions to become CEOs’ #1 generative AI priority.
2. 85% of execs say generative AI will be interacting directly with customers in the next two years.
3. Piloting generative AI in customer service can speed a successful enterprise-wide rollout.
And three things every leader needs to do right now:
1. Turn human agents into heroes by giving them generative AI tools.
2. Use generative AI to learn more about your customers than you ever thought possible.
3. Exploit successes and learnings in customer service.
An updated version of this chapter with 2024 data is now available in the latest edition of the IBM Institute for Business Value's book, The CEO's Guide to Generative AI.
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Originally published 01 August 2023
1. Strategy
+ Generative AI
What you need to know
Customer service has leapfrogged other functions to become CEOs’ #1 generative AI priority
Only three short months ago, CEOs told us research, innovation, marketing, and risk compliance were the most immediate and valuable use cases for generative AI. Today, customer service has jumped to the top of the generative AI implementation list, cited by more CEOs than any other organizational function or service.
In part, that’s due to the pressure on CEOs to implement generative AI coming from all stakeholders. Almost half say they’re feeling demands from customers to accelerate use of the new technology. Customers want personalized answers, fast and without hassle, which means AI-powered customer service bots are not only useful, they’re essential.
Executives recognize the power of generative AI to deliver transformation in customer service. They anticipate a long list of benefits, with shortened response times and improved overall customer experience at the top.
But the path to all benefits starts with agents.
Nearly two-thirds of executives (63%) say that by the end of 2023 they will have already invested in generative AI use cases to serve agents directly, including deploying generative AI for agent training, and enabling agents to interact directly with tech applications to deliver improved instant assistance.
Whatever use cases are being adopted, customer service should always be designed around trust and reliability: Generative AI can be used to support engagement while agents add a deft, effective human touch at just the right moments.
What you need to do
Turn human agents into heroes by giving them generative AI tools
Freeing up human agents so they can pivot to more personalized customer engagement—where it matters most—is one of the most immediate ways organizations can offer enhanced value to customers, differentiate their brand, and begin transforming customer service from a cost center into a revenue accelerator.
- Prioritize use cases that improve the agent experience. Obviously, automate laborious manual tasks. And let agents tap generative AI to answer questions about products and services and offer recommendations. Give agents quick and easy access to call transcriptions and summaries. Use generative AI for instant translations. And enable agents to access the tech for coaching based on their personal analytics.
- Let generative AI manage the standard customer interactions and relay the more complex and sensitive queries to your human agents. Invest to create highly trained individuals and nurture them carefully. Along with empathy, ensure they have the business acumen to offer the white-glove service that can convert unhappy customers into brand loyalists.
- Don’t play “hide-and-seek” with your customers: Tell them when they are engaging with a generative-AI bot. And let them request human assistance at will, no questions asked.
2. People
+ Generative AI
What you need to know
85% of execs say generative AI will be interacting directly with customers in the next two years
Before the year is out, more than 60% of execs expect to be using generative AI for optimization, including reviewing, testing, and training conversational AI. It’s high stakes when businesses are putting generative AI on the front line where missteps with customers could be catastrophic for the brand.
It may be tempting to deploy generative AI with customers quickly, but it’s essential that leaders understand customer pain points generative AI can resolve best, and apply what they learn from agent interactions. Some concerns already top of mind for executives: Bot-based responses that are harmful or off-brand, issues with transparency or auditability, and compromised social responsibility goals.
At least in its early learning phase, unsupervised generative AI has the potential to create less-than-ideal outcomes. People—and for customer service, that means agents—can provide the guardrails. Agents enhance what AI brings while acting as a backstop for AI-generated misinformation. And as the technology becomes more sophisticated, agents can forge the emotional connections with clients that can yield new insights and opportunities. It’s about agents plus AI—a winning combination that can drive added value for the enterprise.
What you need to do
Use generative AI to learn more about your customers than you ever thought possible
To conquer high risks and capture high rewards in customer service, this tech deployment should be about listening, testing, and then capitalizing.
- Invest in direct engagement between customers and generative AI, but don’t do it blindly. Start by determining which challenges are most likely to pose the most risk for your organization and which generative AI use cases can be designed to mitigate those pitfalls.
- Use generative AI as a research tool to collect and analyze sentiment-based metrics for each customer service interaction. Start with low-risk, low-effort use cases that address key customer concerns. Stay mindful of what differentiates your brand today and how AI can enhance what makes your organization unique.
- Use generative AI not just for interactions and engagement, but for driving innovation. Use it to mine new opportunities with customers and track customer service success to see how automated applications influence sales and customer loyalty across the customer lifecycle. Refocus efforts around data governance.
3. Experimentation
+ Generative AI
What you need to know
Piloting generative AI in customer service can speed a successful enterprise-wide rollout
The call center continues to be ripe for transformation. During pandemic lockdowns, it became clear how much customer service could be automated—but we also suffered for the lack of human contact. With generative AI, organizations get the best of both worlds. By pairing automation with humanity, customer service becomes a proof of concept, demonstrating to the rest of the enterprise how new tech tools can improve employee satisfaction, impact customer engagement, and drive returns.
Using generative AI to make automated responses better and more conversational can quickly demonstrate how AI’s impact can be used to upgrade service elsewhere in the organization. And for most organizations, the need and opportunity is wide open. For example, a majority of businesses report their ability to review and retrain customer service bots is insufficient, and just half are able to proactively alert customers as soon as issues arise.
What you need to do
Exploit successes and learnings in customer service
Because generative AI is as much about your people as it is about technology, the very visible realm of customer service will serve to motivate change across the enterprise.
- Re-orient customer service from problem resolver to innovation hub. Foster outcomes-based generative AI experimentation that can be measured, optimized, and scaled. And package specific learnings that might be readily applied across other areas.
- Shout-out generative AI successes and share exemplary outcomes at individual and functional levels. Demonstrate to employees in other areas how they can benefit from generative AI by highlighting the ways in which new AI capabilities improve not just customers’ experiences but employees’ circumstances.
- Challenge and motivate your workforce to explore how generative AI can help in their day-to-day work—beyond the initial use cases. Create gamified opportunities for individual contributors to pitch use cases that can spark new ideas and applications.
The statistics informing the insights on this page are sourced from three proprietary surveys conducted by the IBM Institute for Business Value in collaboration with Oxford Economics regarding perspectives around generative AI. The first survey was answered by 200 US-based CEOs, while the second was answered by a broader range of 369 executives across the US, UK, Australia, Singapore, Germany, and India. Both surveys were fielded in April–May 2023. The third survey was answered by 108 executives in 18 countries and was fielded in July 2023.
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An updated version of this chapter with 2024 data is now available in the latest edition of the IBM Institute for Business Value's book, The CEO's Guide to Generative AI.
Additional content
Download report translations
Originally published 01 August 2023
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