When traveling to a new place, knowing precisely where it is and having a plan to get there is crucial to ensure a successful journey.
After all, if you start heading in the wrong direction, the journey to your desired destination will take longer than necessary.
In the world of AI and generative AI (GenAI), this metaphor is especially applicable.
AI has generated a lot of press and internal urgency. Senior leaders are telling teams to “get on with it.”
As such, many have rushed out the door and made missteps, with several public failures throughout 2024. That resulted in bad PR, upset customers, and even lawsuits.
Instead, contact centers should press forward with context, understanding, and clear business objectives. That starts with understanding the breadth of AI and GenAI applications and how they can help your business.
Contact Center AI: More Than Bots Alone
Adopting AI goes beyond simply implementing a bot or automating a few processes; it’s about building a comprehensive strategy that meets your business objectives, whether it be to enhance the customer experience, improve the efficiency of frontline teams, managers, and analysts, save costs, or myriad other goals.
Achieving this requires understanding AI's current limitations and capabilities and how it can realistically help you achieve the desired results.
Creating such an all-encompassing strategy may sound intimidating. However, businesses can follow the “crawl, walk, run” approach.
A “Crawl, Walk, Run” Example
Many contact centers will start their GenAI journey by leveraging auto-summarization solutions.
Noting this use case, Steve Nattress, VP of Product Management at Enghouse Interactive, said:
“AI Summarization condenses long conversations into just a few sentences, saving time both at the start and end of calls. This allows agents to quickly review previous interactions at the beginning of a call and streamlines post-call wrap-up by identifying next actions and eliminating the oversights and inaccuracies of manual summaries.”
In addition, auto-summarization can automate ticket tagging to categorize customer interactions. With that comes more accurate data, which leaders can harness to better understand ways to improve their processes, products, and services.
Leaders may analyze those tags to spot product issues and broken processes, prioritize contact center journeys, and consider broader AI use cases to fix, automate, and enhance those experiences.
Consider the Quick Wins That Will Build Confidence
Like any major change, widescale AI adoption won't happen overnight. For instance, many contact centers still struggle to implement a true omnichannel experience. Indeed, as recently as 2023, over two-thirds of contact centers were still not omnichannel. AI will also take time.
Yet, many customer service leaders are under pressure to implement AI. So, consider the quick wins that will instill confidence from above and complement the broader "crawl, walk, run" strategy.
A simple voicebot that detects intent and routes contacts in place of a conventional IVR is an excellent example of where to start.
At a later date, the contact center can augment its voicebot capabilities with a GenAI-based virtual agent. With the appropriate guardrails, the virtual agent can help automate targeted Q&A queries, match the question to a predefined knowledge base article, and present relevant responses in a proper tone. Virtual agents' responses can also be evaluated for accuracy, just like human agents – only they are available 24 hours a day.
Also, because the virtual agent can detect intent, it can ensure that queries without related, qualified knowledge content pass directly to a live agent.
Understand the Fundamentals of Contact Center AI
While developing a “crawl, walk, run” strategy, there are plenty of best practices to follow. Here are three excellent examples.