Most companies deploy AI with one goal in mind: cut costs. Deflect tickets. Reduce headcount.
It sounds efficient, but it’s the wrong goal. And it's why so many AI implementations miss the mark.
The better model treats AI and automation as layers of protection around your most valuable asset: your agents. Not to stop customers from reaching a human, but to make sure that when they do, the interaction actually matters.
Your agents are the core. They're the heart of the experience, the people responsible for turning a frustrated customer into a loyal one. Our job as CX leaders is to protect them from unnecessary friction and empower them to solve what only a human can.
That requires thinking in layers.
Layer 1 — Proactive Journey Design
Before a ticket exists, there's an opportunity to prevent it.
This requires cross-functional alignment: identifying friction in the customer journey and resolving it upstream. When done well, customers never know there was a problem. They complete their purchase, get their answer, move on and never need support at all.
Layer 2 — Demand Reduction (Upstream Protection)
When customers begin to feel friction, this layer catches them before it escalates.
This includes self-service that actually resolves issues, proactive communication around orders and outages, and AI that solves problems, not just deflects them.
The best ticket is the one that never gets created.
Layer 3 — Demand Shaping (Queue Protection)
This is where most organizations leave the easiest gains on the table.
The goal is to clean and structure the work that does come in: merge duplicate tickets, route by intent rather than channel, and create accurate queue visibility.
At Black Rifle Coffee, a single implementation within this layer dramatically reduced perceived backlog and gave agents and leadership a clearer, more actionable queue. Now, that solution scales regardless of season and reminds us every peak why we took the time to do it right.
Without this layer, teams don't work more, they just work on the same problems multiple times, often creating more customer confusion in the process.
Layer 4 — Agent Acceleration (Human Protection)
This is the make-or-break moment. Agents need to show up equipped.
That means AI-assisted replies, guided workflows, intent-based knowledge surfacing, and a full 360° view of the customer's journey. Agents shouldn't be hunting for answers. They should be delivering them.
Here's where most companies go wrong.
They invest in Layer 2 quickly, skip Layer 1 entirely, and jump straight to Layer 4 without realizing they've set their agents up to absorb the mess their incomplete rollout created. Layer 3, arguably the easiest place to demonstrate impact, gets skipped too.
The result? Agents are overwhelmed. Customers feel the friction from the start. And leaders start asking why AI isn't delivering on its promise.
It isn't. Because AI was never the fix; design is the fix. AI is just a tool in our ever growing arsenal.
A powerful support tool, but a tool applied to a broken system doesn't repair it; it just delays the reckoning.
The layered model isn't just about efficiency. It's about protecting the system that actually delivers your customer experience: your people.
Reduce unnecessary demand, and agents have space to think rather than just react. Clean up the incoming work, and they move faster with better information. Support them properly, and conversations shift from transactional to genuinely impactful. Customers feel that difference immediately.
Before you deploy your next tool, ask three questions:
- Why is this a need?
- How will you define success?
- Can it scale with you?
Your agents are not a last resort, they’re a key piece. Start protecting them and your customers before the interaction ever begins.
Author Bio
Beth Reedy, Manager of Integrated Systems & Customer Solutions, Black Rifle Coffee Company
Beth is a Customer Experience and Operations leader at Black Rifle Coffee Company, with over 5 years in CX and a degree in psychology, focused on scaling human-centered solutions at the enterprise level. Her work has driven measurable business outcomes, including over a quarter of a million in direct revenue impact and tens of thousands of customer interactions enabled through self-service and retention-focused initiatives. Known for turning complexity into clarity, Beth blends data, technology, and cross-functional collaboration to build scalable CX solutions spanning chatbot development, system design, platform optimization, and leadership grounded in empathy and long-term impact.
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