In my conversations with hundreds of support leaders across the globe, I sense a palpable tension. On one hand, there is unprecedented pressure. Economic headwinds have forced a renewed focus on retention and efficiency, placing support squarely in the crosshairs of the C-Suite.

On the other hand, there is an overwhelming sense of technological opportunity. Generative and Predictive AI promises to revolutionize everything we thought we knew about customer support.

Yet, despite the pressure and the promise, the vast majority of support organizations are stuck. They are trapped in what I call the “Incremental Game”. They are using revolutionary technology to achieve evolutionary gains like shaving a few minutes off handle time, deflecting 5% more tickets, or boosting CSAT by half a point. These are not failures; they are improvements. But in today’s landscape, incremental improvement is a fast track to irrelevance.

When I wrote Support Experience, my goal was to challenge the deeply entrenched notion of support as a necessary evil, a reactive cost center whose primary goal is to make problems go away quietly and cheaply. Today, that message is more urgent than ever.

If your strategy for the next two years is to “do what we’re doing now, but slightly faster with AI,” you aren’t just missing the boat; you are actively endangering your company’s future retention.

It is time to stop optimizing a broken model. It is time to reimagine support entirely.

The Incremental Trap

Why is incrementalism so seductive? Because it’s measurable, it’s safe, and it fits neatly into a spreadsheet that the CFO already understands.

Historically, support has been defined by efficiency metrics: Mean Time to Resolution (MTTR), First Contact Resolution (FCR), and Cost Per Ticket. When a new technology arrives, the knee-jerk reaction is to apply it to these existing metrics.

We see this happening right now with Generative AI. Many enterprises are rushing to deploy bots with the aim to improve these metrics. Is that useful? Absolutely. Does it change the game? Absolutely not.

If you use AI to close a ticket faster, you haven’t improved the customer’s experience; you have only improved your own operational efficiency. You are still operating in a reactive posture, waiting for something to break so you can fix it.

The danger of incrementalism is that it gives you the illusion of progress while the underlying foundation of customer loyalty erodes.

AI Lessons from the Field

There’s a massive gap between the hype of AI in the enterprise and the reality of its implementation.

Boston Consulting Group (BCG), in their analysis of corporate AI adoption, has repeatedly emphasized that the real value of AI doesn’t come from isolated task automation. It comes from reimagining end-to-end processes.

A recent BCG perspective noted that while many companies are successfully piloting GenAI for specific tasks (like drafting content), few are scaling it to transform core business functions. The trap is using powerful tools to patch over structural weaknesses.

If your support process is fundamentally frustrating for a customer—requiring them to repeat information, bounce between departments, or wait days for a substantive answer—adding AI to the mix just means they might get a frustrating answer faster.

McKinsey & Company echoes this, suggesting that the companies that will win with AI aren’t just looking at cost reduction; they are looking at revenue generation and customer lifetime value enhancement.

If support leaders only present AI use cases focused on “deflection” and “headcount avoidance,” they are cementing their status as a cost center. They need to present use cases focused on intelligence gathering, churn prevention, and product innovation.

The Blueprint for Reimagined Support

So, what does a reimagined support organization look like? And how do you move beyond tracking incremental improvements to CSAT, and MTTR to become the central nervous system of customer intelligence for the enterprise?

Here are three key pillars of this reimagination:

1. Reimagine the System of Record

To move beyond incrementalism, we have to address the “elephant in the room”: the Support CRM. I’ve outlined on this blog, why we are seeing a massive shift toward a CRM-less architecture.

Support CRMs were built as static databases and were never designed to handle the unstructured, and emotional data that lives within a support interaction. Unfortunately, many support organizations are still trapped into reactive workflows driven by metadata.

You wait for a human agent to manually update a field correctly before you can “see” a problem. A reimagined support organization leverages a System of Intelligence as the foundation and not the legacy System of Records. You no longer have to rely on Salesforce Service Cloud or ServiceNow CSM or Zendesk as your system of truth, instead you can start leveraging a true data lake like Snowflake.  

The System of Intelligence and Ambient AI Agents sit on top of the data lake and help:

• Deflect tickets
• Route cases to the right engineer
• Provide real-time knowledge assistance for human agents
• Automatically coach human agents in real-time
• Draft new KB articles
• Provide a hyper-personalized customer portal experience

This is a true transformation of customer experience, not just operational efficiency. Your CFO and CIO will also thank you for significantly reducing the TCO of maintaining legacy ticketing systems.

2. Reimagine the Process

The challenge with these processes is that they are often designed as failsafe mechanisms as opposed to optimizing for support experience. Barry Schwartz in one of my favorite TED talks – “Our Loss of Wisdom” makes a compelling case on why strict rules and processes assure mediocrity.

“The problem with relying on rules is that they are often intended to prevent the bottom from falling out… But in the process of protecting against the bottom, we ensure mediocrity for everybody else”

Barry recommends applying practical wisdom and common sense as the remedy. A well-trained AI model can provide this wisdom at scale. AI models are not rules-based, and they can make exceptions where the model predicts a good outcome. Often these could be counter-intuitive but the underlying data can support it.  A good example of this is Intelligent Case Routing. Traditional case/call routing systems use keywords or case categories for assigning cases. Unfortunately, they are inefficient and miss the big picture. An AI-based case routing systems accounts for the agent’s backlog, familiarity with the account, demonstrated skillset, timezone compatibility, current availability, and more. Taking a holistic approach to case assignment avoids customer frustration, unnecessary handoffs and escalation paths.

When you are implementing AI, it is time to rethink your current process. Applying AI without changing your process will only yield incremental results. Be bold and eliminate unnecessary steps and processes. Often many of them won’t be necessary or can be greatly simplified. If you have a lengthy process for tiered support, consider eliminating tiered support altogether.

3. Reimagine the Role of Support

Support teams know more about the product’s failings than the product team. They hear the unfiltered truth every day. In Support Experience, I emphasized that support should have a seat at the product table. Instead of just reporting bug counts, reimagined support uses AI to aggregate unstructured feedback into actionable insights.

They don’t just say, “We have 500 tickets about the new dashboard.” They say, “Our analysis indicates that the new dashboard complexity is causing high anxiety among our mid-market segment, leading to a 15% increase in negative sentiment and putting $2M of ARR at risk.”

That is not cost-center language; that is business-strategy language.

The obsession with “deflection” is toxic. It implies the customer is an adversary trying to breach your defenses. Reimagined support uses self-service and AI bots not just to save money, but to guide customers toward success.

When a human agent is needed, they are armed with the full context of the customer’s history, sentiment, and potential revenue value. AI shouldn’t just draft an answer; it should suggest the right tone based on the customer’s current emotional state. It should alert the agent that this customer is up for renewal in 30 days and has had three bad experiences in a row. That is relationship protection.

“Support Experience” as a Paradigm Shift

In my book, Support Experience, I argue that we need to stop talking about “Customer Support” and start talking about “Support Experience (SX).” This isn’t just semantic wordplay; it’s a fundamental shift in philosophy.

Traditional support is transactional. It’s about closing tickets. Support Experience is relational. It’s about understanding the customer’s journey and emotional state.

As I wrote in the book:

“We must move away from the concept of ‘support’ as a function that reacts when things go wrong, to an ‘experience’ that proactively ensures things go right. The goal isn’t to be apologetic for product failures but to be a trusted advisor focused on the relationship.”

When we view support through the lens of SX, our priorities shift dramatically. We stop obsessing over how fast we closed the ticket and start obsessing over what the ticket tells us.

Every interaction is a signal. Every piece of unstructured data within a support conversation—the sentiment, the urgency, the specific feature mentioned—is gold. Yet, in the incremental model, we treat this data as exhaust fumes, discarding it once the ticket is marked “solved.”

Reimagining support means building systems that mine this “exhaust” for intelligence that the rest of the company needs to survive.

The technology to achieve this isn’t science fiction; it is available today. The barrier isn’t technical; it is cultural.

As a support leader, you have a choice. You can continue to fight for scraps of budget by promising incremental efficiency gains, ensuring you remain a back-office function.

Or, you can seize this moment of technological disruption to reimagine your role. You can take the principles of Support Experience, leverage the true power of AI, and transform your organization into an indispensable engine of customer retention and product intelligence.

Don’t settle for better tickets. Demand a better experience.