AI and Automation
Building a crisis-ready support function with AI and WFM

Building a crisis-ready support function with AI and WFM

Kate Hutchinson
JUMP TO SECTION

Support teams rely on their tech stacks to deliver top-notch customer experiences. Without the right tools — ticketing systems, knowledge bases, and workforce management (WFM) platforms — even the most skilled teams struggle to meet customer expectations. But today, simply having the right tools isn’t enough to solve the most pressing challenge support teams face: resolving customer issues — especially when unexpected demand spikes hit.

Traditionally, the only way to scale support and meet rising customer demand was by adding more agents. With the help of forecasting and capacity planning, support leaders could anticipate volume and bring in the necessary in-house or outsourced agents. But here’s the catch: what looks good on paper doesn’t always translate to reality.

The unpredictable nature of support

Anyone who’s spent time in support knows the unpredictable nature of contact volume. A product goes viral, a major outage happens, or a high-profile influencer shares your brand — and suddenly your well-forecasted support demand explodes. Unplanned spikes in volume can throw even the best-prepared teams into chaos.

You’ve been there. Teams scramble to reassign agents, make frantic calls to BPO partners for more coverage, and individual agents push themselves to their limits. The sole focus in those moments? Resolving customer issues as fast as possible.

This is where your support tech stack and WFM tools come into play. But while WFM tech helps you manage staffing and respond to surging demand, it doesn’t solve the root of the problem: the resolution itself.

Workforce management: Your staffing command center

Workforce management (WFM) technology has long been the go-to solution for support leaders who need to track demand and allocate resources effectively. Think of it as the command center for staffing. Your WFM platform helps you pull levers to adjust schedules, redistribute agents, and make critical staffing decisions based on what the business needs.

But here’s the reality: even with great WFM tools, unexpected spikes can leave you stretched thin, scrambling to respond. More staff alone can’t always save the day. That’s where AI comes into play — the new lever that fundamentally changes how support teams approach issue resolution.

Rethinking issue resolution in the age of AI

Today, we’re no longer bound by a single lever (hiring more agents) to resolve issues during peak demand. Advances in AI have introduced a new capability: using intelligent automation to resolve issues without relying on human agents. This game-changer allows support teams to scale operations beyond human limits, transforming how they handle crises.

While you’ve likely heard that AI can automate repetitive tasks or streamline self-service, its true potential lies in its ability to resolve complex customer issues. AI-powered tools aren’t just making it easier to find answers, they’re taking things a step further by reasoning through multi-step resolutions — even in high-stress, high-volume situations.

Crisis management with AI: A real-world example

Let’s revisit those scenarios that keep support leaders up at night. A natural disaster causes a surge in insurance claims, or a viral product release overwhelms a retailer’s support team. Even with a WFM system helping you juggle staff and assignments, SLAs are slipping, and customers are getting frustrated.

With Assembled Assist, you gain a new kind of flexibility. You can design and deploy AI-driven workflows that automatically resolve customer issues in real-time. It’s like having a crisis support team available 24×7, ready to step in whenever demand spikes. Here’s how that looks in practice:

Take the overwhelmed insurance company after a natural disaster. With Assembled Assist, the team can quickly set up a resolution path that cross-references incoming emails with customer policy details and generates replies accordingly. The AI considers the type of policy, the tone of the incoming message, and the company's brand voice to craft the most appropriate response. Assist even allows you to test these automated replies against real tickets before deploying them, ensuring accuracy and alignment with your customer communication strategy.

Each reply comes with a confidence rating from Assist, and the support team can decide what level of confidence is required for an automatic response to be sent. For lower confidence levels, human agents can review the replies, adding an essential layer of oversight in high-stakes situations like insurance communications. This strategic balance between automation and human input means the team handles high volume efficiently without sacrificing quality or risking inaccuracies.

Now consider the clothing company dealing with viral demand. They set up a resolution path in Assembled Assist to handle returns and exchanges based on the sentiment of customer emails. If the AI detects that a customer is upset, it automatically initiates a return. For less urgent cases, it suggests an exchange instead. The beauty of Assembled Assist is that there’s no need for multiple, complicated branching paths — the AI reasons through the steps, connects to internal systems, and takes the necessary actions to resolve issues.

Rather than leaving customers waiting when agents are stretched thin, the support team can turn on this AI automation, adjust the confidence levels to their preference, and resolve issues at scale — even during a crisis. With Assembled Assist, the team ensures that no matter how high the demand spikes, customer issues are handled efficiently and empathetically. Crisis averted!

AI + WFM: The ultimate command center for issue resolution

When you combine the strategic power of WFM with the real-time problem-solving of AI, you create a command center that’s not just about managing staffing — it’s about resolving issues at scale. WFM helps you see where demand is highest, and AI gives you the ability to respond immediately, automating issue resolution to keep SLAs on track and customers satisfied.

In a world where demand is predictably unpredictable, adding AI to your support stack is like adding a new superpower. It’s not just about handling spikes — it’s about being ready for whatever comes your way. And in moments of crisis, it’s the lever you need to keep operations running smoothly and your customers happy.