Thought Leadership
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After 14 years working in customer engagement, I've learned that the difference between a vendor and a partner comes down to one thing: how well you listen.
That sounds simple, but it's become harder than ever. In an era where AI can analyze sentiment, predict churn, and personalize at scale, many organizations are automating communication – confusing data collection with genuine listening.
Real listening means paying attention to what clients say and what they don't say. It means catching the casual mention of a challenge and asking follow-up questions. It means recognizing when someone's tone shifts in a meeting and checking in afterward.
These are the things AI can’t do – or at least, can’t do in ways that build trust. As automation becomes table stakes in customer engagement, this human capability becomes a sustainable competitive advantage.
The role of customer engagement has evolved significantly, and AI is accelerating that evolution in contradictory ways. We're not just the people who answer when clients call with problems. We're strategic partners who understand what drives their success, anticipate their challenges, and help them achieve outcomes they didn't know were possible.
AI promises to make all of this easier. Predictive analytics can flag at-risk accounts before your gut instinct would. Automated workflows can ensure nothing falls through the cracks. Machine learning can surface expansion opportunities you might have missed.
But what many organizations are discovering is that AI is brilliant at efficiency and terrible at intimacy. It can tell you what is happening but not why it matters. It can scale communication but not genuine connection. It can detect patterns but not understand context.
The risk isn’t that AI will replace customer engagement professionals. The risk is that organizations will use it as a substitute for the messy, inefficient, deeply human work of actually understanding their customers.
Here’s what many organizations miss: customer engagement isn't about managing accounts or optimizing metrics. It's about building relationships that create value on both sides. When clients see you as a partner rather than a vendor, everything changes. They bring you their challenges before they become problems. They involve you in strategic planning. They think of you first when new opportunities arise.
This transformation doesn't happen by accident, or through automated touchpoints or AI-generated insights alone. It requires intentional strategies, consistent execution, and genuine commitment to your clients' success – the kind that can’t be programmed into an algorithm.
Technology should enhance this work, not replace it. The question is how.
Through years of working with clients across different industries, I've found that successful customer engagement rests on three core activities: health checks, business reviews, and expansion initiatives. But each needs to evolve for a world where clients expect both high-tech efficiency and high-touch relationships.
Health checks are your regular opportunity to assess how things are actually going, not how you think they're going. These informal conversations create space for honest feedback and early problem identification.
Here’s where the AI changes everything and nothing. Yes, machine learning should monitor usage patterns, flag anomalies, and alert you to declining engagement. That’s valuable, but not the insight – it’s the prompt for a conversation.
When AI flags a problem, that’s when the human work begins. The questions remain straightforward: What are we doing well? What could we improve? What challenges are you facing that we should know about? What's coming down the pipeline that we can help you prepare for?
But now you’re asking them at exactly the right moment, with data-informed context, in ways that feel proactive rather than reactive. You’re demonstrating something important: you’re paying attention in ways that matter.
These conversations should happen frequently. Daily check-ins for active projects, deeper dives when situations warrant it. When you conduct regular health checks, you're demonstrating something important: you care about their success beyond the contract terms. This builds trust in ways that formal meetings simply cannot.
Business reviews take a broader view. These quarterly meetings examine the overall relationship, assess performance against goals, and ensure strategic alignment.
A good business review includes hard data—usage metrics, outcomes, return on investment. But it also includes strategic conversation. AI can generate these reports automatically, creating real-time dashboards that make quarterly data dumps obsolete.
But here’s what shouldn’t change: business reviews need strategic conversation. Are we still aligned on goals? Have your priorities shifted? What opportunities should we be exploring together?
The difference between a health check and a business review remains the same. Health checks ask "How are things going?" Business reviews ask "Are we achieving what we set out to achieve, and where should we go from here?"
The difference in an AI-augmented world is that you’re having these conversations from a foundation of continuous insight rather than point-in-time analysis. You’re not reviewing what happened last quarter – you’re co-creating what should happen next, informed by data but driven by shared vision.
Expansion is where strategic relationships become revenue generation. But here's the critical point that becomes more complicated with AI: you don't hunt for expansion opportunities. You listen for them.
Clients often tell you exactly what they need if you're paying attention. A casual mention of a challenge they're facing. A question about whether you offer a particular service. A comment about what another department is working on. These are signals, and your ability to recognize and respond to them determines whether you're truly a strategic partner.
AI can now predict these needs before clients articulate them – sometimes before they recognize them themselves. This creates both opportunity and ethical complexity. Are you being proactively helpful, or uncomfortably prescient? Are you solving problems or manufacturing needs?
The key is asking open-ended follow-up questions. When a client mentions a challenge, dig deeper. What have they tried? What's at stake? What would success look like? Often, these conversations reveal opportunities that benefit both parties.
But transparency matters more than ever. If your recommendation is driven by predictive analytics, clients should understand that. The goal is to be insightful, not invasive; to be strategic, not manipulative.
Customer engagement can't operate in isolation. The most effective professionals in this role are expert collaborators who know how to pull in the right resources at the right time – and AI is making this coordination more seamless.
When a client mentions their learning management system is missing features, you don't just note it down. You loop in the product team to understand what's possible, the sales team to explore expansion opportunities, and the implementation team to assess timeline and resources. AI-powered collaboration tools can now route those conversations automatically, track commitments, and ensure follow through.
When a client has a billing question, you don't make them navigate your organization. You connect them directly to finance and ensure the issue gets resolved. Technology can streamline these handoffs, but humans still need to own the relationship.
This role as connector and coordinator is what transforms customer engagement from reactive problem-solving to proactive partnership building. You become the client's advocate within your organization and your organization's eyes and ears with the client. Technology amplifies this capability – but only if you’re intentional about using it to enhance rather than automate human connection.
Strategic customer engagement isn't built on grand gestures or sophisticated AI implementations. It's built on consistent, small actions that accumulate over time.
Start meetings by genuinely asking how things are going and actually listening to the answer. Follow up on commitments within the timeframe you promised. Share relevant information proactively, not just when asked. Recognize and celebrate client successes. Introduce clients to colleagues who can help them, even if there's no immediate business benefit to you.
Use multiple communication channels strategically. Quick questions via chat. Complex discussions over video. Sensitive topics by phone. Important updates via email with follow-up confirmation. Technology can help orchestrate these touchpoints, but each interaction should still feel human and contextually appropriate.
Most importantly, be organized. Nothing undermines trust faster than dropping balls or losing track of commitments. Here’s where technology is unambiguously helpful: automated reminders, AI-powered CRM systems, and task management tools can ensure nothing slips through the cracks. Your clients need to know they can count on you to follow through.
Use AI for what it does best – tracking details, surfacing insights, maintaining consistency. Reserve your human energy for what machines can’t replicate: intuition, empathy, judgement, and genuine care about your clients’ success.
Organizations with engaged customers consistently outperform competitors. They see higher sales growth, better margins, and stronger customer loyalty. They spend less on acquisition because satisfied customers refer new business. They experience fewer escalations because problems get caught and solved early.
These fundamentals haven’t changed. What’s changing is how companies achieve them. The organizations winning at customer engagement are those using AI to be more human, not less. They’re leveraging data to be more responsive while protecting space for inefficient but essential conversations. They’re using predictive insights to anticipate needs while maintaining transparency about how they know what they know.
But perhaps the most compelling business case is this: in competitive markets where products and services become increasingly similar, the relationship becomes the differentiator. Clients stay with organizations where they feel heard, valued, and supported by actual humans who care. They leave organizations where engagement feels algorithmic, no matter how personalized the automation.
While companies are racing to implement AI solutions, human partnership cannot be replicated.
If you're responsible for customer relationships in any capacity, start by assessing your current approach through a critical lens. Are you conducting regular health checks or only reaching out when there's a problem? Are your business reviews truly strategic conversations or just status updates? Are you listening for expansion opportunities or waiting for clients to ask?
Pick one area to improve. Maybe it's establishing a regular cadence of informal check-ins. Maybe it's restructuring your business reviews to focus more on strategic alignment. Maybe it's developing your skills in asking better follow-up questions.
The most successful customer engagement professionals share one characteristic: they're genuinely curious about their clients' businesses and committed to their success. And in a world increasingly defined by AI, they use AI as a tool to be better partners, not as a replacement for partnership itself. If you approach every interaction with that mindset, the tactics and strategies will follow.
As I like to say, the world is heavy, and we lift what we can. Sometimes the most valuable thing you can offer a client is simply being someone who listens and helps them work through challenges.
Building true partnerships takes time, consistency, and genuine care. But when you get it right, you’ll build the one thing AI cannot replace – trust – and you’ll create relationships that drive business success for both parties.
Emily Holland is Vice President, Client Success at Kaplan North America
