The Next Play for Support Teams

An unprecedented change is happening in the world today. Teams are getting smaller while producing more value than ever before. In many ways, this phenomenon enforces the spirit of technology—ruthless efficiency, outsized impact, and surgical execution. And yet one critical function—customer support—remains stuck in the past.

While this change is sweeping across the world, adoption necessarily occurs in phases. And at each stage, brief windows open where sharp operators can exploit information asymmetries and market inefficiencies before the landscape evens out again.

Legacy Support is Broken

We are in such a moment in customer support. The industry has gone through a slow evolution over the years. Let’s spotlight banking as a case study. Banks supported customers by stationing tellers in physical branches, requiring customers to travel just to be served. This model was constrained by geography, hours of operation, and headcount.

As technology evolved and modern lines of communication developed, banks expanded their support channels to include mediums like phone, email, and social media. Companies like Zendesk and Intercom positioned themselves as the middleware that connected customers seeking support online to service providers.

The march of progress continued, and banking shifted decisively into mobile app experiences. This evolution has allowed a significant reduction in the friction and effort that characterized traditional banking—the result today is a near-perfect experience for all consumers. It’s blazing fast, seamless, and intuitive.

Like all seismic technological shifts, the playing field eventually levels out, and what was once heralded as revolutionary, becomes the baseline. Today, there is a minimum threshold of quality that banking providers must meet up to just to compete. This recalibration has raised the bar—consumers now expect speed and convenience as the standard, not the differentiator.

But while product experiences are largely efficient, they are far from flawless. It’s never been easier to start a technology business, but it’s powered by clouds, rails, and screens: a fragile web of third-party services, each introducing its layer of complexity, interdependency, and risk.

When things fall through the cracks (and they inevitably do), support owns the process of fixing and correcting. In an era of lightning-fast product experiences built for internet scale and speed, the demands on support have soared.

Despite this, many support teams continue to operate with unoptimized tooling and clunky workflows that fail to keep up with the pace, standards, and expectations of the modern internet. While teams like product, growth, and engineering have unlocked new ways to scale and punch above their weight, support often stays bogged down in bottlenecks and inefficiencies. Consequently, they remain a growing line item that feels like a cost center instead of a strategic asset, and businesses miss out on unique opportunities to delight and retain their customers.

AI Breaks the Linear Model

The fact that this is the norm at scale signals a market inefficiency to exploit and a new frontier to compete on. Until now, business growth was limited by customer support headcount: more customers meant more tickets, and to keep up, you had to throw people at the problem – or risk damaging your newfound popularity with poor customer experiences.

Thanks to AI-first customer service, this linear growth model has finally been broken. Support teams no longer have to grow their team at pace to meet demand; instead, they can rely on AI tools to manage support volume without compromising on CX.

Because it is cheaper than ever to deliver high-touch, high-quality service at scale, companies can afford to treat every customer like a VIP. AI agents will answer all questions, autonomously resolve customer issues, and take action on behalf of the customer, mirroring the quality and exceeding the productivity of the most seasoned agents.

Consider this: as customers onboard on platforms today, many hit moments of friction and confusion. But because the path to getting help, which involves exiting the current flow, switching channels, and describing their issue in detail, is so high effort, many silently drop off, costing the business in unrealized revenue and wasted marketing spend. What’s worse? There’s no feedback loop to fix what is broken.

To fix this, support teams can partner with engineering to embed help directly within the product. By linking existing systems—like AI agents and troubleshooting workflows—to user behavior and product events, teams can deliver proactive support right at the point of friction, before drop-off turns into lost revenue.

For instance, the system can be configured to listen for signals like repeated failed attempts to add a BVN, and if this happens, an AI agent is launched offering to help the user, with a human-in-the-loop ready to take over if needed. It’s rapid, proactive support that matches the pace and progress of the modern world.

Execution is Hard

In many ways, support teams finally have the tools to level up. but there’s still a significant gap between AI hype and real-world deployment. The market is saturated with AI tools, but they require a steep learning curve and significant setup time to deliver any real business value, leaving many organizations stuck between promise and performance. There are simply no magical plug-and-play solutions; any suggestion otherwise is marketing theatre.

The truth is that successfully integrating AI agents into real workflows demands a deep understanding of business processes and the AI tech stack: the tooling, the logic & the integrations. People who understand both are rare and almost impossible to hire for. It’s also challenging to train people for the role because while the knowledge exists, it’s fragmented—scattered across forums, docs, and niche communities—not diffused into accessible and neatly packaged formats like courses or books.

For the most part, people with the knowledge acquire it through real-world implementation, trial and error, and synthesis of scattered insights into a direction that works. The reality is that most teams won’t get this opportunity because they are short on time, attention, and incentive. Like most late adopters in any tech wave, they don’t act when it is a strategic advantage; they only do when it is the new baseline, and the advantage is gone.

This is Operational Arbitrage

This is the gap, the information asymmetry that has created this temporary market inefficiency. Teams have a short window to capitalize before the advantage disappears and the playing field resets. The same way “Product Managers weren’t a thing in most companies pre-2010, Growth wasn’t a real job before 2013, DevOps was fringe before 2015, we’re now at the early end of a curve where AI deployment in support will become standard, companies will need specialists who understand customer ops + LLMs + structured flows, they'll realize that automating support is both a retention strategy and a margin unlock.

But the steps required to seize the opportunity right away are numerous. Support teams need a fundamental mindset shift. Thinking of themselves solely as service deliverers is reductive; they must become system designers and architects, crafting scalable workflows and driving measurable impact linked to revenue, just like their peers in product and engineering.

This culture shift takes time and effort. It’s more likely teams will not be ready to lead the initiative right away, but that doesn’t mean you can’t move in on this opportunity fast today.

However, make no mistake, the window is closing fast. For the bold and earnest, the advantage is real. And in a world that moves as fast as ours, the future may arrive sooner than we expect.

Implementation partners like Metacare, with rare, practical insight, are here to help forward-thinking teams move fast and capitalize on this narrow window of operational arbitrage. We’ll help you exploit the gap between AI’s real capabilities and the market’s lagging adoption. The good news is you have access to all the tools already. Reach out to the founders today.