Just a few years ago, businesses wrestled with artificial intelligence mainly in the abstract — a “future of work” problem they’d have to contend with down the line. Now? More than half the companies around the world are actively adopting AI. Although investments are particularly high in industries such as health care, data management and processing, cloud computing, and fintech, all types of organizations and functions have incorporated AI technology into their operations. And generative AI tools such as ChatGPT are forcing leaders to ask where and how AI can help their businesses.

Even so, most companies still view AI rather narrowly, as a tool that alleviates the costs and inefficiencies of repetitive human labor by automating mundane physical tasks (like moving merchandise in warehouses) and increasing organizations’ capacity to produce, process, and analyze piles and piles of data. But the technology can do much more than that.

Paired with “soft” inquiry-related skills such as critical thinking, innovation, active learning, complex problem solving, creativity, originality, and initiative, this technology can further our understanding of an increasingly complex world, allowing us to engage in more abstract questioning and shifting our focus from identification to ideation. In our research and workshops with executives, we’re finding that companies have much to gain by treating AI as a aknowledge-work collaborator in diverse areas such as product design, process efficiency, and prompt engineering. Partnering with the technology in this way can help people ask smarter questions, which in turn makes them better problem solvers and breakthrough innovators. We are also seeing the initial impacts of more context-aware AI systems (like ChatGPT), and as they continue to improve, the skill of asking questions (or creating prompts) will only become more valuable in the discovery process.

Although experts have recognized the need for software engineers to ask smart questions upstream, when developing automated tools (to bake in fewer biases and assumptions), little has been said about the flipside of the relationship between AI and inquiry: the technology’s potential to help people become more inquisitive, creative problem-solvers on the job. We aimed to correct this oversight through design-thinking sessions and extensive follow-up conversations with tech-driven business leaders from a diverse array of countries and industries. We also surveyed roughly 200 leaders, from more than 30 countries who participated in our executive education programs at MIT —to learn how artificial intelligence has affected questioning patterns and innovation behaviors and outcomes in their organizations. (For this research, we’ve defined “artificial intelligence” broadly to include machine learning, deep learning, robotics, and the recent explosion of generative AI.)

We have found two distinct, yet related, paths that leaders follow to strengthen their (and their teams’) inquiry muscles as they tap the power of AI in their question-asking work.

On the first path, they can use the technology to change the cadence and patterns of their questions: AI increases question velocity, question variety, and question novelty. Results from our ongoing research show that AI can significantly increase all three.

On the second path, AI can help transform the conditions and settings where people work so that questions that spark change — what we call “catalytic” questions — can emerge. This pushes leaders out of their comfort zones and into the position of being intellectually wrong, emotionally uncomfortable, and behaviorally quiet and more reflective, all of which, it turns out, promotes innovative thinking and action.

Let’s look at how each path can lead to breakthrough ideas.

Increasing velocity, variety, and novelty.

Partnering with AI to ramp up the velocity, variety, and novelty of questions requires companies to train algorithms to answer the basic, easy (yes/no) questions independently and to reveal deeply buried patterns in the data. When this foundation is laid, humans can start exploring the power of more context-dependent and nuanced questions that AI technologies are not yet capable of answering alone.

Question velocity

Algorithms can provide immediate answers to questions that leaders pose, in turn allowing them to ask more — and more frequent — questions. In our research, we found that 79% of respondents asked more questions, 18% asked the same amount, and 3% asked fewer.

At the cybersecurity firm Cybereason, researchers rely on AI and machine learning to immediately answer the basic questions about what happened in an apparent breach so the team can more quickly turn its attention to formulating deeper questions about why it happened. In the past, CEO Lior Div said, findings were more black-and-white: “It’s an attack. It’s not an attack. It’s good or it’s bad.” But the speed with which AI filled in those blanks opened up a whole new line of questions around intent — and what hackers are really after in a given situation.

Of course, there are risks to using AI to generate rapid-fire questions. For one, people may keep asking more and more questions without working their way toward an actionable path, making it important to recognize when the process stops being productive. For another, more questions don’t necessarily amount to better questions, which means you’ll still need to exercise human judgment in deciding how to proceed.

Question variety

AI helps uncover patterns and correlations in large volumes of data — connections that humans can easily miss without the technology. Knowing they have this tool at their disposal frees up leaders to ask farther-ranging questions and explore new ideas that they may not have otherwise considered. In our research, we found that engagement with AI led respondents to ask different questions than they otherwise would have 94% of the time.

Consider this example: Kli Pappas, the director of predictive analytics at Colgate-Palmolive, told us that his team tapped AI to understand how charcoal became a wildly popular ingredient in consumer products so they could “find the next charcoal.” Their algorithm generated and answered thousands of questions based on their initial search for data, sketching out a decades-long trajectory from charcoal scrubs in South Korea 20 years ago to charcoal appearing in face washes in the U.S. and then in all kinds of products around the world. The AI-generated data led the team to ask hundreds of less-obvious questions to spark creative thinking about future trends that may be lurking in unexpected places. “We look backwards across categories and try to see how do trends move between categories from hair care, to skincare, to oral care,” Pappas said. “Just doing that puts you a decade or more ahead of the curve.”

Question novelty

AI also facilitates deeper insights by helping users arrive at novel, “category jumping” questions — the gold standard of innovative inquiry — that apply understanding from one area to a completely different space. Our research shows that AI led respondents to ask unique questions that changed the direction of their team, organization, or industry 75% of the time.

When you know a technology can sift through much more data, and connect more dots, than you could ever do alone, it gives you license to ask wilder questions — things you would never ask if you had to answer them on your own, because they are intractable for the human brain or somehow go against entrenched cognitive biases.

While category-jumping questions will not arise in every encounter with AI systems, being open to the possibilities and allowing for freedom of inquiry can pave the way for more instances. Here’s how Mir Imran, a medical innovator and founder of InCube Labs, described the upside when we spoke: “AI can take really obscure variables and make novel connections. When these hidden connections come together, it causes you to reframe your question and deliver disruptive innovations.” In other words, AI’s novel connections can spark your novel questions, which in turn can lead you to investigate solutions others haven’t dreamed of yet — like the robotic pills that Imran’s team recently created to replace external injections with internal ones.

Creating conditions for better questions.

AI can take leaders out of their usual mode of operation and force them to cede control over where their questions will take them. That’s a good thing. Increased question velocity, variety, and especially novelty give facilitate recognizing where you’re intellectually wrong, and becoming emotionally uncomfortable and behaviorally quiet — the very conditions that, we’ve found, tend to produce game-changing lines of inquiry. Jeff Wilke — former CEO of Amazon Consumer Worldwide, now a cofounder of Re:Build Manufacturing — has embraced these conditions not only in his day-to-day work as a tech executive but also throughout his career, continually revising his mental models while moving from role to role. When we spoke, he had this to say: “If you seek out things that you don’t know, and you have the courage to be wrong, to be ignorant, to have to ask more questions and maybe be embarrassed socially, then I think you build a more complete model, and that model serves you well over the course of your life.”

But there’s a hitch to teaming up with AI: Research suggests that it can be challenging for people to do so congenially because AI’s superhuman capabilities and unpredictable moves may prevent them from fully trusting and engaging with the technology. That tracks with what we’ve observed in organizations and learned from our conversations with leaders.

Distrust of the technology is hardly conducive to creative inquiry. So, look for ways to offset that, and don’t just leave it to AI to produce the conditions for breakthrough thinking and problem-solving. Consider how else you might create them. Where is there room in your problem-solving processes for synthesizing things that don’t seem related? How might you use those opportunities to throw people off balance so they’ll generate questions that reach beyond what they intellectually know to be right, what makes them emotionally comfortable, and what they are accustomed to saying and doing? At the same time, how can you create psychological safety for people in your organization to ask far-ranging questions and to use AI more effectively to learn from them, ultimately leading to asking better questions? When psychological safety is present, people can say, without repercussion, “I am wrong,” “I am uncomfortable,” and “I am still thinking”?

Rather than neatly resolve all those tensions, leaders and teams must learn to sit with the uncertainty that comes from asking questions that take them into new territory. While the process isn’t easy, the results are exciting, which is perhaps the most important benefit of collaborating with an AI system. Excitement provides momentum and motivation to push through a tough process, fueling further creativity.

Mitigating AI’s Weaknesses with Human Strengths

Artificial intelligence may be superhuman in some ways, but it also has considerable weaknesses. For starters, the technology is fundamentally backward-looking, trained on yesterday’s data — and the future might not look anything like the past. What’s more, inaccurate or otherwise flawed training data (for instance, data skewed by inherent biases) produces poor outcomes.

Leaders and their teams must manage such limitations if they are going to treat AI as a creative-thinking partner. How? By focusing on areas where the human brain and machines complement one another. Whereas AI increases the volume of data we can process and the degree of complexity we can manage, our brains work in a reductive manner; we generate ideas and then explain them to other people. Whereas machines lack imagination and moral judgment, we can tap those critical skills as AI helps us increase the velocity, variety, and novelty of the questions we’re asking to solve problems in our organizations. Such differences are the stuff of fruitful collaboration — and optimizing them can reduce the threat of AI to human labor.

With humans and AI working to their respective strengths, they can transform unknown unknowns into known unknowns, opening the door to breakthrough thinking: logical and conceptual leaps that neither could make without the other. Harnessing this potential will require leaders to look at artificial intelligence in a new light — one that is less about cost savings, efficiency, and automation and more about inspiration, imagination, and innovation. It will also require building a culture that supports, incentivizes, and rewards asking big questions — and not necessarily knowing the answers.

Disruption used to be an exceptional event that hit an unlucky few companies — think of the likes of Kodak, Polaroid, and Blackberry. But in today’s complex and uncertain world, as we face challenges ranging from climate change to digitization, geopolitics to DEI, organizations must treat transformation as a core capability to master, as opposed to a one-off event.

At the same time, leaders must recognize that transformation is fraught with risk. In 1995, John Kotter found that 70% of organizational transformations fail, and nearly three decades later, not much has changed. Our own research, in which we spoke to more than 900 C-suite managers and more than 1,100 employees who had gone through a corporate transformation, showed similar results: 67% of leaders told us they had experienced at least one underperforming transformation in the last five years.

Considering that organizations will spend billions on transformation initiatives over the next year, a 70% failure rate equates to a significant erosion of value. So, what can leaders do to tilt the odds of success in their favor? To find out, we interviewed 30 leaders of transformations and surveyed more than 2,000 senior leaders and employees in 23 countries and 16 sectors. Half of our respondents had been involved in a successful transformation, while the other half had experienced an unsuccessful transformation.

So what tactics did the leaders of successful transformations use to manage the emotional journey? To find out, we built a model to predict the likelihood that an organization will achieve its transformation KPIs based on the extent to which it exhibited 50 behaviors across 11 areas of the transformation. This model revealed that behaviors in six of these areas consistently improved the odds of transformation success. Organizations that are above average in these areas have a 73% chance of meeting or exceeding their transformation KPIs, compared to only a 28% chance for organizations that are below average. Our research suggests that any organization that can effectively implement these six levers will maximize their chances of success.

Our research also found that a key difference in successful transformations was that leaders embraced their employees’ emotional journey. Fifty-two percent of respondents involved in successful transformations said their organization provided the emotional support they needed during the transformation process “to a significant extent” (as opposed to 27% of respondents who were involved in unsuccessful transformations).

Transformations are extremely difficult on a personal level for everyone involved. In the successes we studied, leaders not only made sure their teams had the processes, resources, and technology they needed — they also built the right emotional conditions. These leaders offered a compelling rationale driving the transformation, and they ensured employees had the emotional support they needed to execute. This meant that when the going inevitably got tough, employees felt appropriately challenged and ultimately energized by the stress.

By contrast, leaders of the unsuccessful transformations didn’t make the same emotional investment. When their teams hit the inevitable challenges, negative emotions spiked, and the team entered a downward spiral. Leaders lost faith and looked to distance themselves from the project, which led employees to do the same.

The Six Key Levers of Transformations

So what tactics did the leaders of successful transformations use to manage the emotional journey? The six levers that maximize the chances of success, according to our research are:

1. Leadership’s own willingness to change

Many people believe that a leader’s job is to look outward and give others guidance, but our research suggests that to help their workforce navigate a transformation, leaders need to look inward first and examine their own relationship with change. “If you are not ready to change yourself, forget about changing your team and your organization,” as Dr. Patrick Liew, executive chairman at GEX Ventures, told us.

In our interviews, leaders spoke of working on their own development, including engaging more with their emotions and becoming accustomed to the discomfort that accompanies personal growth. Leaders needed to “look into a mirror,” as one told us, and realize that they were part of the problem before the shift to a positive trajectory could take place. They needed to remove their own fear before they could help their employees get through this change.

“As someone who was tasked to lead this [transformation], if I’m being honest with you, it was pretty unsettling at the start, because I think by nature most of us like to know the path we’re going on,” as one COO from the automative industry told us. And a senior vice president in the global business services industry described needing to become more vulnerable and honest on their path to self-discovery: “I think I became even more aware of myself, who I am.”

2. A shared vision of success

Creating a unified vision of future success is another all-important foundation point of a transformation. In our research, 50% of respondents involved in successful transformations said the vision energized and inspired them to go the extra mile to a significant extent (as compared 29% of respondents in low-performing transformations).

Employees must understand the urgent need to disrupt the status quo. A compelling “why” can help them navigate the inevitable challenges that will arise during a transformation program. Many of the workers who took our survey said that they “wanted” and “needed” the vision to be communicated clearly. When leaders share a clear vision, the workforce is more likely to get on board. But if people don’t understand the vision or need for transformation, success is hard to achieve.

“It’s not about me telling people ‘This is what’s going to happen,’” as a managing director in the medical device industry told us. “It’s about me creating this shared sense of ownership…and then [coaching] my team on what they need to achieve. We very consciously want our teams to really buy into this is how we, as a collective, want to work.”

3. A culture of trust and psychological safety

Trust and care from leaders can make a difficult transformation more emotionally manageable. At the most basic human level, we all know what it feels like to be seen, listened to, and heard by another person. It can validate our effort, motivate us to work harder, and help assuage emotions like doubt, fear, anger, and sadness. Workers in our study shared that they wanted leaders who were patient and who also had, in the words of one employee, a “calm and teachable spirit.”

In a workplace with a high degree of psychological safety, employees feel confident that they can share their honest opinions and concerns without fear of retribution. When trust and psychological safety are missing, it’s difficult to persuade your workforce to make necessary changes. For example, one senior leader told us that employees at their company were extremely fearful of the transformation and didn’t feel that they could speak up about the problems they saw. Not surprisingly, the transformation did not go well.

4. A process that balances execution and exploration

Transformations obviously need disciplined project management to drive the program forward. But our research showed that leaders of successful transformations created processes that balanced the need to execute with giving employees the freedom to explore, express creativity, and let new ideas emerge. This empowers the workforce to identify solutions or opportunities that better meet the long-term goals of the transformation.

“Innovation requires the right people and processes,” said one respondent to our anonymous survey. “Both are critical to encourage collaboration and experimentation.”

We also found that creating space for small failures can ultimately lead to big success, whereas fear of any failure can lead to missed opportunities. Forty-eight percent of our respondents involved in successful transformations said the process was designed so that failed experimentation would not negatively impact their career or compensation to a significant extent. By contrast, only 29% of respondents in unsuccessful transformations said the same.

5. A recognition that technology carries its own emotional journey

The leaders in our study ranked technology as the biggest challenge they faced in their transformation efforts. There are a lot of emotions to manage when new systems or technology are introduced, from stress over how it works to fear about whether it will cause job loss or slow down the system.

In the underperforming transformations we studied, we saw the narrative shift away from the vision to focus on the technology itself. Whereas in the successful transformations, leaders ensured that technology was seen as the means to achieve the strategic vision. Furthermore, they prioritized quick implementations of new technology — focusing on a minimum viable product rather than perfect implementation. Lastly, they invested resources into skill development to ensure the workforce was ready to create value using the new technology.

“There were kickoff sessions with our senior managers to bring them in at the beginning of the process,” a vice president of a company in the media/advertising industry explained. “These sessions aimed to show them that what was being built was something that they had helped design, rather than something that was presented to them as a fait accompli…This minimized the numbers of active detractors.”

6. A shared sense of ownership over the outcome

In the successful transformations we studied, leaders and employees worked together to co-create an environment where everyone felt a shared sense of ownership over the transformation vision and outcome.

A prime example of this is many companies’ rapid shift to virtual and remote working during the pandemic. Because of the speed and urgency of the change, leaders needed to collaborate closely with the workforce to create new ways of working and be much more responsive to their views on what was or wasn’t going well. This mass co-creation helped build a sense of pride and shared ownership across both leadership and the workforce.

“In a transformation, things pop up all the time,” as Christiane Wijsen, head of corporate strategy at Boehringer Ingelheim, told us. “When you have a movement around you, supporters will buffer it and tweak it each time. When you don’t have this movement, then you’re alone.”

. . .

To conclude, it’s worth reiterating that all transformations are tough. Even during successful programs, there will come a time where people start to feel stressed. The skill at this difficult stage is being able to energize your workforce and turn that heightened pressure into something productive, as opposed to letting the transformation spiral downward into pessimism and underperformance.

What we saw throughout our research is that leaders who are truly working with their employees are much more successful. They acknowledge and manage emotions, rather than pushing them aside or ignoring them. The best leaders create vision across the organization and a safe environment to work together and listen to each other.

“You’ve got to be very, very respectful of people at a working level,” as Thomas Sebastian, CEO of London Market Joint Venture at DXC Technology, told us. “You’ve got to understand the emotional side and consider a completely different perspective, such as how is this transformation going to make their life easier.”

Success begets success. Once a workforce has undergone a successful transformation, they will be ready to go again. And given the pace of change in the world, organizations have got to be ready to go again.

The last few years have brought disruption after disruption to bear on the ways companies and customers interact. Arguably, the company-to-customer connection has been more disrupted than supply chains or operations, and more affected by disruptors like Covid and technology than any other key relationship. Think of the rise of e-commerce — which hockey-sticked during the pandemic; or the sudden (or seemingly sudden) ubiquitousness of self-checkout kiosks at grocery stores and pharmacies; or the ever-greater prevalence of voice response systems, to which you must listen closely because the “menu options have changed.” Or, recall the Covid-19 shutdowns and subsequent bounce-back, which altered everything from how diners eat to how sales reps call on B2B customers.

These trends and sudden swings have created significant difficulties for middle market companies and — as we will see — a very important challenge and opportunity for their growth ambitions.

With all of this change has come a dramatic upsurge in customer dissatisfaction. Actually, that’s understating it; we’ve seen an upsurge in customer rage. The newest edition of the Arizona State University W.P. Carey School of Business survey of customer rage found that last year 74% of customers said that they have experienced problems with a product or a service — up from 47% two decades ago. The survey goes on to note that customers are getting angrier and angrier about how they are treated when they deal with companies — and are far less reluctant to express their rage not just to companies, but on social media for all to see. Some of that rage may reflect a rise in general incivility, rather than any specific company failure. But companies bear a good share of the blame; after all, the #1 customer frustration is being unable to talk to a person when they have a problem — and the #2 complaint is that they can’t even find out how to contact the company at all.

From Leaders to Laggards — How Most Companies Are Failing Their Customers

Why? Our analysis suggests that many companies have fallen victim to what they see as a zero-sum game between high-quality service and low cost. Indeed, according to a nationwide survey we conducted, just 15% of companies successfully combine both — i.e., high levels of efficiency and advanced data and analytics combined with high levels of proactive outreach and service — and we call them “Leaders.” Amazon, Amex, and Apple come to mind, and get an “A” in our book.

Go too far in one direction, and you are a “Big Spender,” putting more money into customer service, support, and success than you are getting back in terms of profitability and loyalty. Go too far in the other, and you’re a “Miser,” penny-wise and pound-foolish, frustrating and ultimately losing customers because you don’t connect with them on a level that matters to them.

Surprisingly, 41% of the companies we surveyed fall into the unfortunate “Laggard” category, where they see customer support as a downstream cost center requiring minimal investment, and suffer from low customer satisfaction ratings and high customer churn.

Addressing this tension between cost efficiency and customer intimacy is important for companies of any size, but it’s especially important for midsize companies, particularly those upper-middle-market companies with ambitions to rise to the top of their industry. In many cases, they built their brand, and their differentiation from the big guys, on the idea of personalization — of being closer to their customers than their multinational rivals can be — while also offering more sophistication, a broader offering, and more underlying service capability than small businesses can.

Herein lies the core challenge: to grow, they need to build customer capabilities that are scalable, but if they do that at the expense of proactive connection with customers, they will lose their identity and a big piece of their competitive edge.

Escaping the Zero-Sum Game Approach

We don’t think service and scale are a zero-sum game. On the contrary, we’ve seen company after company make it work, often realizing results in the first year. For example:

• A mid-market payroll solutions provider (with ~2,000 employees) working in a niche part of the industry reduced their servicing cost by 30% and set-up a “Customer Success” team to nurture client relationships and enhance loyalty. The result: a 650% increase in their net promoter score and a substantial increase in wallet share, helping them to gain an edge over the competition in just one year.
• A $500M revenue data storage and protection company reduced its customer-service operating costs by 20% by eliminating duplicate systems and reducing complexity and cost-to-serve by improving the alignment and communication among sales, renewals, and services teams. Revenues rose by 10% in the first year after implementing a Customer Success program that was laser-focused on proactive customer contact, improved wallet share, and improved loyalty.
• A cybersecurity company with ~1K employees increased its use of automation to reduce support costs by approximately 15%; but the same system improved call routing to serve customers better and faster, resulting in a substantial increase in its customer satisfaction score. NPS nearly doubled and customer attrition dropped by 5%, increasing Net Retention Revenue (NRR).

How do they do it? By undertaking three things simultaneously and with a get-stuff-done sense of urgency:

Have a strategic point of view about who you want to be to your customers.

There can be reasons to spend big on personal touch (for example, in a new industry or for a luxury product or service), and reasons to under-invest (e.g., you are in a commodity business where price and availability are more important than anything else). But most companies should seek a competitively advantaged sweet spot where the right kinds of hands-on, proactive attention meets the right kinds of automation and efficiency. You need strategic clarity about what that sweet spot is — and to back that up with the right measurements and incentives.

Do the research to understand your customers’ biggest frustrations and pain points.

What is your brand promise that customers expect you to deliver? Is it a high-touch white glove service (think a Four Seasons hotel) or is it transactional support focused on saving you time (like a Motel6). How do customers perceive the value of your brand, what do they expect to be delivered, and where are your failure points? Use that knowledge to identify a handful of key initiatives that can make a difference in the next six months. For example, rather than forcing self-service or automation on all of your clients, you might be able to meet them in their preferred channel of choice e.g., self-service for tactical queries (or digitally-savvy customers), vs. white-glove customer care for others.

Update your understanding of the art of the possible.

Advances in AI and machine learning in just the last three years have transformed customer relationship management, just as they have rendered (on the upstream side of things) a lot of old ERP systems obsolete. You can now quite inexpensively get real-time customer data at a granular level and build individualized profiles of customers’ needs. It is also easy to route the most valuable or unhappy clients to the most senior or tenured customer care specialists. And the landscape continues to evolve quickly with newcomers like ChatGPT.

Midsize companies especially need to continually explore these options for two reasons: First, because these evolving digital enablers give companies the edge they need to move up from “Laggards” to “Leaders” with more customer insights, views into Customer Lifetime Value (CLV), propensity to churn (improving loyalty), and customer sentiment. Second, your competition is using it, and the bar is rising for everyone.

It Can Be Done: How Winning Companies Are Realizing Tangible Value

As companies continue to navigate this uniquely disruptive environment, we are seeing more leaders protecting their customer base by optimizing customer experience and loyalty. For midsize companies especially, when acquiring new customers or expanding market share becomes increasingly unpredictable, investing in enhancing customer experience, Customer Lifetime Value (CLV) and Net Retention Revenue (NRR) becomes a powerful way to preserve and expand revenue.

Investing in systems and processes won’t be enough. We have found that to win, companies need to focus on three key things to achieve real change:

Elevate customer success to be a core part of the business strategy.

Increasingly, customer experience is seen as a competitive differentiator, especially as more companies stumble in their attempts to shift to digital solutions. Investing in experience and loyalty can drive topline growth, but only if leadership agrees that customer success should have a seat at the table, right next to sales and marketing in terms of strategic importance to your brand’s growth.

Manage technology investments through the business first, not IT.

It is critically important to view digital solutions as strategic business investments, and not technology investments. Time and again we see winning companies frame their core challenges, solutions, vendor selection, and even operationalization as top-down, strategically aligned efforts where IT provides implementation support, rather than acting as the gate keeper. Don’t fall for the latest shiny object — remain true to the brand promise and core objectives.

Appoint a Customer Success leader to take ownership of measurable impact.

Real change will require a change in mindset, and most important, sustained commitment over time to implement needed initiatives, lead training efforts, integrate systems changes, and track financial impacts. Appointing a dedicated leader is critically important to have real ownership to keep Customer Success top of mind as a strategic imperative for growth, even in the most disrupted markets.

In this uniquely disruptive and uncertain environment, it makes sense for companies to invest in protecting their customer base by optimizing customer experience and loyalty. When acquiring new customers or expanding market share becomes increasingly unpredictable, investing in enhanced customer experience, Customer Lifetime Value (CLV) and Net Retention Revenue (NRR) becomes a powerful tactical lever to preserve and expand revenue.

It can be done. And, with rapidly evolving digital solutions, it can be done faster and more inexpensively than ever. More winning companies are converting this time of disruption into an opportunity to implement customer success solutions to expand revenue and gain a competitive edge. The only question now is: As we emerge from disruption, will you be a Leader, or a Laggard?