Editorial
Guide
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The Gist
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AI adoption is outpacing AI readiness. McKinsey reports that 88% of organizations now use AI in at least one business function, yet Gallup finds only one in four employees say their organization has communicated a clear AI strategy. The technology is moving faster than most organizations can build the skills and guardrails to support it.
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Standing still carries more risk than moving imperfectly. Competitors are already deploying AI at scale, customer expectations continue to rise, and waiting for certainty risks falling behind both.
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CX leaders don't need expertise to start, they need momentum. The path forward is the same one that's always defined great CX leaders: experiment, learn, adapt, and apply AI to the customer and business problems you already know how to solve.
Uncertainty is nothing new to customer experience leaders. Over the past two decades, we've navigated economic downturns, digital transformation, evolving customer expectations and the ongoing challenge of proving the business value of CX. We've adapted to new technologies, new methodologies while continuing to justify investments and prove our value.
AI feels different.
The pace of change feels unlike anything we've experienced before. New capabilities emerge constantly, organizations are racing to adopt AI and expectations are shifting faster than many teams can adapt. Yet there is no established playbook, no agreed-upon maturity model and no clear roadmap for what successful AI adoption looks like in CX.
The data reflects this tension. According to McKinsey's 2025 State of AI report, 88% of organizations now use AI in at least one business function, up from 78% the previous year, while 79% report using generative AI, compared with 71% in 2024.
Simultaneously, Gallup reported in February that only 13% of U.S. employees use AI daily in their work, 28% use it a few times a week or more and only one in four employees say their organization has a clear plan for integrating AI into their jobs.
The paradox is clear: AI adoption is outpacing AI enablement. Expectations are rising faster than guidance, and AI literacy is becoming increasingly important as best practices continue to evolve.
If you're feeling uncertain, you're not behind. You're experiencing the same reality as many seasoned CX leaders: building new capabilities while the technology continues to evolve. Fortunately, navigating uncertainty has always been part of our profession. This is simply the next chapter.
What Matters Here: How Wide Is the Gap Between AI Adoption and AI Enablement?
McKinsey found 88% of organizations use AI in at least one function, while Gallup found just 13% of employees use it daily and only one in four say their company has a clear AI plan.
Why Delaying AI Adoption Is Riskier Than Experimentation
The greatest risk may not be making the wrong move. It may be making no move at all.
AI is no longer a future capability. It is rapidly becoming part of how organizations operate and how work gets done. While many CX leaders are still determining where AI fits into their strategy, other teams are already incorporating it into their daily workflows.
Customer support is one example. According to Salesforce's State of Service report, 85% of service organizations now use at least one form of AI, and 66% are using agentic AI in 2026, up from 39% the previous year.
AI can help CX teams synthesize customer feedback, analyze behavioral data, identify friction points and connect customer sentiment with operational and financial outcomes. It can also bring together information from multiple enterprise systems, giving CX leaders a more complete view of what customers are experiencing and what the business is already doing to address those issues.
Customers are moving just as fast. They expect experiences that are highly personalized and anticipatory in real time (80%), seamless across digital and physical touchpoints (72%) and AI-powered while still feeling human and brand-aligned (60%). Standing still means falling behind the expectations your own customers already have.
Waiting for best practices to emerge may feel like the safest approach, but the profession is evolving in real time. The practitioners building confidence today are not necessarily the ones with the deepest technical expertise. They are the ones willing to experiment, learn and discover where AI can strengthen the work they are already doing.
Standing still doesn't preserve today's skills. It simply delays building tomorrow's.
Related Article: Before You Scale AI in Customer Experience, Fix These 5 Things
What Matters Here: What Percentage of Service Organizations Now Use Agentic AI?
Salesforce reports 66% of service organizations use agentic AI in 2026, up from 39% the prior year, while customer expectations for real-time, AI-powered service keep rising.
How CX Leaders Can Build AI Confidence Without a Roadmap
No one knows exactly how AI will reshape customer experience. There is no universal roadmap, no proven formula and no agreed-upon definition of what success looks like one year out. Even the people writing, speaking and consulting on AI are learning alongside the rest of us.
The data backs this up. 72% of leaders say AI literacy is important for day-to-day work, but only 35% report having a mature, organization-wide AI literacy program. Organizations know AI matters. Few have built the systems to use it well.
That gap isn't a reason to wait. Start where you are. Explore. Experiment. Test ideas, try new approaches. Learn what works in your environment and what doesn't. AI proficiency isn't built by reading articles or watching demos. It's built through regular use, thoughtful experimentation and continuous refinement.
The more you work with AI, the better you get at framing questions, providing context, evaluating responses and improving output. Confidence grows through practice, not perfection.
You don't need certainty to move forward. Progress comes from learning, testing and adapting.
What Matters Here: What Share of Organizations Have a Mature AI Literacy Program?
Only 35% of organizations report a mature, organization-wide AI literacy program, even though 72% of leaders say AI literacy is important for day-to-day work.
Why CX Leaders Should Start Learning AI Before They Feel Ready
The goal isn't expertise. The goal is momentum.
Adopt a beginner's mindset. Focus on learning, not mastery. You don't need to become an AI expert. You're already an expert in understanding customers, identifying friction and connecting customer experience to business outcomes.
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Build a habit of continuous exploration. Experiment with synthesizing customer feedback, connecting sentiment with behavioral and financial data, automating repetitive tasks, strengthening executive storytelling or uncovering insights that once took hours to find.
Forty two percent of employees expect their role to change significantly because of AI within the next year, and 79% believe they'll need new skills to keep pace. The pressure to learn isn't hypothetical. It's already here.
You don't need to know everything before you begin. The practitioners who build momentum today will be far better prepared than those waiting to feel ready. Curiosity, experimentation and continuous learning have always been hallmarks of great CX leaders. Those strengths are still what matter most. AI simply helps us apply them in new ways.
What Matters Here: How Many Employees Expect AI to Change Their Role Within a Year?
42% of employees expect their role to change significantly because of AI within the next year, and 79% believe they will need new skills to keep pace.
FAQ: Getting Started With AI in Customer Experience
Editor's note: These questions address common concerns CX leaders raise about starting with AI without a formal strategy or technical background.
How to Apply AI to Everyday CX Tasks
The fastest way to learn AI is to use AI.
You don't need to redesign your CX program overnight. Start with the work you already do every day and look for opportunities to make it more efficient, insightful or impactful.
Begin with tasks that save time. Use AI to summarize customer feedback, identify recurring themes, review survey responses, draft communications, prepare meeting summaries or accelerate research. These are low-risk opportunities to build confidence while freeing time for higher-value work.
As your confidence grows, expand into more strategic applications. Use AI to synthesize large volumes of customer feedback, connect customer sentiment to behavioral and financial outcomes, identify emerging patterns, strengthen executive storytelling and develop recommendations that drive business decisions.
Finally, make learning part of your routine. Follow trusted sources such as Anthropic, OpenAI, Google and other industry leaders. Set up alerts for AI developments, experiment regularly with new capabilities and continue refining how AI fits into your own workflow.
The technology will continue to evolve. Your advantage will come from your willingness to keep learning, adapting and applying AI to solve real customer and business problems.
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