Within just the last year, AI has made huge strides in its utility for support teams. More and more, customer support leaders are trying to stay ahead of the curve and add AI to their customer support arsenal. Our webinar discussed the changing roles of AI and adherence in unlocking productivity within customer service, and which investment might be the right decision for you based on your business needs.

What AI in customer service is used for

Customer support teams use AI primarily in four ways:

• AI as a co-pilot to auto-summarise tasks and threads and sum up the crux of a customer inquiry. If a customer submits a few paragraphs, an AI co-pilot can help an agent arrive at a solution faster, without spending so much time reading.

• AI as an onboarding assistant to onboard new agents helping reduce the amount of new information they need to learn, allowing them to ramp up faster and enabling them to focus on complex queries more quickly.

• AI to craft auto-responses for routine interactions. Rather than writing a response by scratch, AI can draft a response, reducing the agent’s job to simply making edits and approving the response. Responses drafted by AI save about 70% of agents’ effort, especially for simple tasks which don’t require much nuance or complexity.

• AI for wider coverage of both multilingual and out-of-hours requests. Wide coverage, especially with agents on late-night shifts, can be a challenge to hire for. Improved coverage using AI helps maintain SLAs by sending initial responses even when human agents are unavailable.

Impacts of AI on team structure

While not a lot of teams have shrunk after adopting AI, the integration of AI has led to headcount freezes, with many teams no longer needing to hire new agents. AI’s capability to handle basic queries reduces reliance on BPOs, cutting management overheads and costs. Consequently, human agents can now focus on more complex tasks, though this has increased average handle times due to a smaller proportion of human-handled interactions being routine inquiries.

AI also allows customer service teams to engage in proactive revenue-generating activities during low-volume periods, such as upselling or upgrading customers. Additionally, AI enhances fraud detection by identifying abnormal patterns in customer behaviour and escalating cases appropriately.

What can’t AI do in customer service?

Despite its advantages, AI has limitations. It struggles with full resolution of complex issues, often requiring back-and-forth interactions to collect necessary context. AI is less effective in handling ad-hoc solutions or understanding nuanced customer problems that need human judgement. Complex cases, such as billing disputes involving multiple factors, still require human agents to actively listen and grasp the core issues.

While the tools provided by AI have helped a lot of operations improve, the fact remains: customer service teams need humans. While AI augments customer service, fully replacing human agents is rare and challenging. The nuanced human touch remains essential for addressing complex issues, making human agents a critical component of customer service.

Managing human teams using adherence

Managing human agents strategically involves understanding expectations and performance monitoring. This is where adherence comes into play.

What is adherence?

Schedule adherence measures how well agents follow their scheduled tasks. It’s calculated by:

• Dividing the number of minutes an employee actually works on their scheduled activity by the number of minutes they were scheduled to work on that activity

• Then, multiplying that number by 100 to express the final adherence calculation as a percentage.

Businesses typically set adherence targets around 70% to 85%. A benchmark set too high creates an unrealistic expectation for agents, and a benchmark too low indicates that employees might not be maximising productivity

Surfboard’s WFM features adherence measurement as a core component to help manage your team the right way. Check out all of Surfboard’s capabilities here, or learn how Surfboard helped Grow Therapy to improve adherence by 19%.

Why adherence matters

Measuring adherence prevents backlogs by ensuring optimal scheduling and aligning with SLAs. It provides transparency in performance metrics, facilitating productive one-on-ones between managers and agents. Adherence helps in setting clear expectations and improving agent behaviour, boosting productivity by around 20-25% as soon as its measurement is implemented. It makes sure that teams work on their designated tasks and helps in measuring output in the right context.

Which is more important?

	Implementing AI	Measuring adherence
Improving the performance of different agents	No	Yes
Automating help centre operations	Yes	No
Driving SLA performance	No	Yes
Reducing backlogs	Yes	Yes
Reducing handle time	Yes	Yes

Both AI and adherence are extremely useful but serve different purposes. AI is a powerful long-term tool for automation and efficiency, while adherence is crucial for managing human teams effectively. Adherence offers a short-term boost in productivity by setting clear goals and expectations, whereas AI provides sustained efficiency improvements.

Balancing the implementation of AI with adherence measurement provides a comprehensive strategy for improving customer service performance, ensuring both immediate and sustained improvements in productivity.