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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 four: Customer & employee experience.
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 four: Customer & employee experience.
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 four: Customer & employee experience.
Today, every product is a digital product—and every company is selling a digital experience. Regardless of industry, all businesses are now competing with the digital experiences that have redefined consumer expectations. And the competition is steep.
Hyper-personalization is now the high bar, as customers demand targeted offers, relevant recommendations, and seamless customer service. But bespoke interactions aren’t enough. Experiences must also be intuitive, serving up what users want before they’ve even asked for it.
Generative AI promises to elevate these expectations—and give companies the tools to meet them. In fact, global executives say that generative AI is the top trend they expect to disrupt the way their organizations design experiences going forward.
For example, an online retailer could use generative AI to streamline its search function. Rather than using categories and filters, customers could ask for what they want in natural language—typed or spoken—specifying key details, such as color, size, or material. They could even include their budget and target delivery date to refine search results. In this instance, not only do customers get what they need easily, they provide valuable data the retailer can use to inform future business decisions.
This is just a single use case, but the possibilities are endless. In this environment, every experience should incorporate AI and every application of AI should be an experience—the two are inextricably linked.
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Originally published 29 August 2023
You can’t please all of the people all of the time. Or at least you couldn’t before generative AI.
The hyper-personalized journeys created by generative AI promise to revolutionize how companies connect with customers and employees. Using true 360-degree customer data from across sales, marketing, and service functions, it can tailor experiences and determine the “next best action” that will help a company engage a specific customer.
For example, a financial services company could use generative AI to rapidly analyze their own customer data—as well as data from social sources and partner organizations—to determine which customers are most likely to take various actions, from opening a new checking account to investing assets to applying for a loan. Generative AI can then help bankers achieve true one-to-one marketing with a personalized strategy and automated, point-in-time customized offers, translated into the customer’s preferred language.
Globally, 62% of executives say generative AI will disrupt how their organization designs experiences—and personalization is at the core of this evolution. In fact, the combination of better content quality and personalization is the #1 benefit driving organizations to reinvent their experiences with generative AI.
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But how organizations will get there is still a bit hazy. While 78% of executives say their organization has an approach for scaling generative AI into customer and employee experiences, most are still figuring out how to ensure consistent quality. More than half (56%) say they don’t have a process in place to review generative AI output and resolve issues.
One way to control quality is to use a proprietary generative AI model that’s trained on approved materials, programmed to meet specific performance benchmarks—and accessible only to employees. These models can be integrated seamlessly into an organization’s existing infrastructure, which provides a more cohesive user experience.
What you need to do
Find the friction and obliterate it
While generative AI is accessible to all, how CEOs choose to use this capability can be a differentiator. By analyzing large amounts of user data, generative AI can identify common pain points and design experiences that are intuitive, engaging, and unique. Make this your moonshot to deliver stellar results.
- Push designers to become content curators. Augment content creation with generative AI to create adaptive designs that automatically adjust based on how users access and interact with content. Apply the human touch to the details that can make all the difference.
- Prioritize everything proprietary. Not all users interact with experiences the same way. Complement open models with deeper investments in proprietary data to help generative AI identify patterns that are unique to your customers and employees. Generative AI can also use proprietary data to personalize, refine, and improve experiences over time.
- Don’t create your own problems. Use generative AI to make the complex simple, not the other way around. Establish use-case-specific guidelines to proactively identify where friction exists and how generative AI could improve experience design. Identify and mitigate risks before rolling out each generative AI application. Balance urgency with prudence.
Generative AI can give customers what they want faster than ever before—but that convenience is only valuable when it’s built on a foundation of trust.
When generative AI offers up personalized recommendations, it limits the number of options on the table. This is, of course, by design. But if customers don’t think the suggestions they receive are aligned with their interests or values, personalization can harm rather than help customer relationships.
Striking the right balance is crucial, but CEOs also feel pressure to act fast. To keep up with the pace of change, organizations are rapidly rolling out customer-facing generative AI in several areas:
- Voice: 27% of organizations are deploying generative AI-powered voice conversations with customers today, and 75% predict they’ll be offering this by 2025.
- Chat: 42% of organizations are using generative AI text-based chat bots with customers, with 84% expected to do so by 2025.
- Outreach: 33% are using generative AI for customer outreach, and 81% plan to do so by 2025.
But 80% of business leaders see explainability, ethics, bias, or trust as a major concern on the road to generative AI adoption. And half say their organization currently lacks the governance and structures needed to manage generative AI’s ethical challenges.
Some organizations may cut corners to move ahead quickly, but most are committed to responsible action. In fact, 72% of executives say they’ll step back from generative AI initiatives if they think the benefits could come at an ethical cost. In this case, less is more. These same organizations are 27% more likely to outperform on revenue growth than others.
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What’s behind this revenue bump? It comes down to maturity. Because the landscape is precarious, those who tread carefully will get farther faster. Avoiding pitfalls and building customer trust are top priorities for CEOs who want to build generative AI capabilities for the long haul. In uncharted territory, radical transparency is necessary to build inherent trust.
Consider wearable tech. Apps powered by generative AI can capture data about users’ exercise habits, sleep patterns, diet, and biometrics, and summarize results, including areas for improvement or concern, which users can query in natural language. But first, users need to opt-in to have their data collected and analyzed. Clearly explaining how generative AI will protect and process their data and making it easy to provide feedback can foster customer engagement and loyalty as they get more comfortable with generative AI.
What you need to do
Create ethical journeys that build customer confidence
Lead with empathy to build trust while you speed toward innovative new experiences. Prioritizing ethics and inviting customer feedback can help organizations engage customers, identify pain points, and pivot as their demands evolve.
- Empathize with customers to build trust. Make empathy a guiding design principle for customer experience. Win customer trust by developing your generative AI ethics in accordance with their concerns. Hold ecosystem partners to the same standards.
- Turn data provenance into data wealth. Present customers with trustworthy experiences and gain data in return. Iterate to improve and personalize products and services for growth and greater ROI.
- Hyper-personalize marketing once and for all. Build generative AI into customers’ experience from their first brand encounter. Earn trust by powering personalized marketing campaigns, targeted advertising, and direct customer outreach with generative AI—and encourage continual customer feedback.
Generative AI promises to transform jobs across sectors, automating tasks that were previously too complicated for a machine to handle. But business leaders don’t plan to replace human talent wholesale. On average, 87% of executives expect job roles to be augmented, rather than replaced, by generative AI.
Developing human-machine partnerships that will engage employees—not enrage them—is an organizational change challenge on steroids. And those that get it right have a lot to gain: Organizations that deliver top employee experiences outperform on revenue growth 31% more than others.
A great experience is also the ultimate change management tool, as it inspires employees to adopt new ways of working. When organizations automate tedious tasks, such as translation or device optimization, it can boost employee productivity and satisfaction by letting humans focus on higher-value work. These productivity gains are ultimately what will allow teams deliver innovations that both differentiate the organization and make their jobs more interesting.
However, automating all the easy tasks could leave humans to handle only the hardest, most frustrating work. To strike the right balance between efficiency and engagement, CEOs must carefully consider where to insert AI into the value chain. They need to rethink the operating model with an eye toward embedding generative AI in ways that will do the most to improve employees’ lives.
For example, organizations can use generative AI to provide a seamless conversational interface for back-office systems, rooting the employee experience in natural language. Headless experiences, which separate front-end user interfaces from back-end processing and storage, hide the complexity of underlying systems and streamline user interactions.
The end goal is to give employees a one-stop-shop for managing their daily tasks. Rather than logging into separate digital platforms, such as time tracking, HR management, recognition, and performance management, headless experiences let them do more within a single tool they’re already using, such as Slack. As companies migrate between systems, the employee experience remains unchanged, smoothing the historical disjointedness as processes move between functional silos—which is a revolution in and of itself.
Centering generative AI around improved ways of working can also help organizations realize better returns. For instance, organizations that manage how employees use generative AI more formally say their employee experience investments yield returns that are 46% higher than their peers. Yet only 37% of organizations have a formal approach in place.
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For their part, workers are up for the challenge. Although 54% are concerned new technology will make their jobs obsolete, 84% are confident in their ability to keep pace with advances in technology at work. They’re also eager to get hands-on. Almost half of employees would be willing to take a pay cut to work for an employer that would give them the opportunity to work with the latest technologies.
Even so, some CEOs are pushing forward without fully considering their employees. Only 28% have assessed the impact of generative AI on their workforce, 43% have already reduced or redeployed workforce due to generative AI, and 46% have hired additional talent.
What you need to do
Give your workers what they want—and more
Use generative AI to put your employees in the operating model of tomorrow. Developing effective human-machine partnerships can create more value than either can alone, as long as employee engagement stays top of mind.
- Activate the ultimate change management tool. Make a good impression with generative AI by showing employees how it can boost their efficiency and productivity—and what that could mean for their careers. Give employees a voice to remediate negative experiences.
- Convert talent challenges into operating model opportunities. Integrate conversational AI, hybrid cloud platforms, intelligent workflows, and agile ways of working in a way that empowers people to perform at the top of their game.
- Expand the remit of human workers. Lean on employees to help design human-centric experiences and determine which tasks are ripe for generative AI. Pair human workers with digital assistants. Start with HR touchpoints and build out.
The statistics informing the insights on this page are sourced from four proprietary surveys conducted by the IBM Institute for Business Value in collaboration with Oxford Economics around perspectives relating to customer and employee experience and generative AI. The first was asked to 212 design leaders in the US, UK, Canada, India, Australia, and New Zealand during July 2023. The second was asked to 300 US-based executives in May 2023. The third was asked to 369 executives in the US, UK, Australia, Singapore, Germany, and India in April–May 2023. The fourth was asked to 21,056 employees across 23 countries in December 2022–January 2023.
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Originally published 29 August 2023