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AI is changing the way contact centers serve their customers.
With its ability to fully resolve calls, eliminate wait times, and increase hiring efficiency, it’s no surprise that 80% of organizations anticipate an increase in AI investments next year, according to McKinsey.
Still, AI can be a daunting undertaking for any contact center leader.
Part of the reason is that AI is one solution in a long line of many. For years, contact centers have tried to tamp down costs with chatbots, IVRs and agent assist tools that overpromised and underdelivered.
Another reason is that AI itself can be intimidating. Can it actually address the decades-long woes of contact centers? Will it require months or years of resources to launch? Even after launching, will we be set up to keep pace with AI’s rapid growth?
Even after checking these boxes, the trepidation toward AI for many contact centers often boils down to one big question:
“Are we ready?”
From the readiness of your tech stack to that of your customers, agents, and even company culture, understanding how AI might fit into your organizational landscape can feel like an impossible question to answer.
Determining your AI readiness
Every contact center leader will eventually invest in AI. Great ones already have. Following the rise of ChatGPT in 2023, AI became mainstream, prompting many contact centers to accelerate their investments. As such, a lot can be gleaned from what early adopters had in common before implementing AI, and their immediate results.
Top readiness factors:
Immediate challenges. Nothing lends itself to readiness quite like necessity. Every contact center adopting AI does so with the intention of solving for immediate challenges. These can include unpredictable call volumes, understaffed or misused agents, high costs, high wait times, low CSAT, and more.
Predictable ROI: Perform a thorough cost-benefit analysis. While AI can streamline processes and improve efficiency, the initial investment and ongoing maintenance costs should be clearly justified by the expected gains in customer satisfaction, operational efficiency, and cost savings.
Stakeholder buy-in: Clearly communicate the value of AI to the stakeholders involved using the impact projections tied directly to their goals. ROI and hiring savings, for example, are always top of mind for finance and operations, whereas CSAT may matter most to CX leaders, and integrations for IT stakeholders.
Integration-ready tech stack. Evaluate the compatibility of your current systems with AI technologies – or find a solution that is platform-agnostic. Seamless integration is crucial to ensure that AI complements existing processes rather than disrupts them. Assess whether your APIs, CRM, CCaaS, and telephony stack can effectively incorporate AI features.
Security and Compliance. AI implementation must align with industry regulations and data security standards. Assess the compliance measures needed from an AI solution in order to accommodate your customer information and regulatory environment.
Target use cases. Early adopters always share some idea of the use cases that would most benefit from automation. These can range from simple flows like caller authentication all the way to end-to-end requests like scheduling an appointment. The common theme is always that the use case is high in volume, repetitive, and not where agents should be spending time.
Urgency. It’s important to understand that AI is not an all-or-nothing proposition. In fact, almost every early adopter starts small and scales to new use cases over time. Most contact centers that have adopted AI began by automating a fractional volume of a single call type, and began organizing and scaling around those learnings.
Behind the question “Are we ready,” is the simple truth that few contact centers who have adopted AI actually felt ready. What was true, however, is they had one of two things: Acute challenges that had to be solved; or, a strong desire to gain a competitive edge.
Armed with these motivators, readiness often takes a backseat to necessity. By focusing on outcomes rather than perceived obstacles, the path forward becomes clearer.
Not sure where to start? Get a custom call assessment using the same AI brain that has automated tens of millions of calls at companies like ADP, DoorDash, The General, AAA, and others.
