No matter what industry you’re in, it seems there’s some level of artificial intelligence (AI) being used, and that trend is probably increasing daily. Whether it’s supply chain operations, inventory management, or providing personalization in everyday services, AI is there helping elevate productivity. It’s easy to see why people may think it could take over some or all aspects of jobs in the future.
When it comes to customer service, there’s most certainly a significant amount of AI working behind the scenes. In fact, the more mature your organization’s contact center is, the more AI may be involved on some level. Analyst firm McKinsey says most mature companies are digitally native and are in the habit of “delivering proactive, service-led engagement, which lets them handle more than 95% of their service interactions via AI and digital channels.”
But what exactly is AI taking care of for that large swath of customer service interactions?
While it helps in many areas, here’s three areas AI benefits contact center agents:
- Knowledge Management
- Customer Experience
- Workforce Optimization
Retrieving the right information at the right time is crucial for any agent to successfully carry out their daily work. But if it’s sitting on different on-premises repositories or cloud storage accounts, the question of easy access comes into play.
How vital is seamlessly accessing the right information in agent to customer interactions?
As it turns out, customers expect high-quality customer service any time they interact with an agent. To help agents deliver those customer experiences, knowledge management systems help expedite locating the best knowledge for each interaction touchpoint. Basically, it’s a virtual system that allows information access from a central repository. It’s often embedded with AI-based algorithms to help identify the best knowledge for each caller session.
For organizations looking for a way to organize and streamline their information, knowledge management systems go beyond boosting agent productivity. It also benefits the organization as analyst firm Gartner says “40% of knowledge management systems that do not include AI/ML-powered capture, authoring, curation, and contextualization capabilities will fail to meet operational and strategic goals1.”
Knowledge management is also seeing newfound productivity gains from AI on the authoring and maintenance side of knowledge management process as well. Generative AI can help fast track the creation of knowledge as well as the summarization, standardization and restructuring of existing knowledge that may have originally been written by dozens of different authors with their own style for far fewer digital channels than organizations may require today.
At the core of all contact center agents’ productivity goals is to provide a great customer experience. To do that, organizations need to have agents managing various points of communication. From website chatbots to traditional phone calls, we know “75% of customers prefer to reach out over different contact methods throughout their contact center experience2.”
For agents to have the capacity to efficiently and effectively manage multiple contact channels, it’s necessary to have some level of AI-enabled technology. By incorporating it into their work tools, agents are able to better serve customers via personalized interactions, gauging satisfaction via emotions, enhancing self-service, and improving call speed.
Having hyper efficient and effective agents is arguably the number one goal of most contact centers. To do that, having the entire workforce optimized is the ideal scenario. Making that happen without the use of AI would likely be extremely strenuous and costly for the organization itself.
Don’t worry about AI taking over agent work fully any time in the near future. It’s our belief that there will always be a human in the loop (HITL) to monitor and streamline AI output. This technology itself is there to enhance productivity, not replace workers.
On average, using AI saves agents nearly two hours of work each day3. Instead of putting a customer on hold to search for an answer on different siloed systems or drafting notes during a call, agents can spend that time providing quality service. As a proof of concept, Stanford and MIT did a study showing a 14% increase in agent productivity by utilizing Generative AI4.
With the use of AI, contact centers can better monitor call volume predictions, automate routine tasks, and enable intelligent routing to prioritize customer queries. These are just a few ways AI can strengthen an organization’s workforce optimization efforts.
Future of AI in Contact Centers
Having AI-enabled help in contact centers isn’t necessarily new. In fact, it’s been around since the 1980s. With the newness of Generative AI, we believe most contact centers are still figuring out its place in their organization.
For more on everyday AI use and the future of it in contact centers, check out our AI Guide for Contact Centers.
1Rathnayake, Pri. Kraus, Drew. 2022. Market Guide for Customer Service Knowledge Management Systems. Gartner, Inc.
2Chandra Das, Avinash et al. 2023. The next frontier of customer engagement: AI-enabled customer service. www.mckinsey.com. www.mckinsey.com/ capabilities/operations//our-insights/the-next-frontier-of-customerengagement-ai-enabled-customer-service.
3Needle, Flori.2023. The State of AI in Customer Service [New Data]. www.blog.hubspot.com/service/state-of-ai-in-service. www.hubspot.com.
4Liu, Jennifer. 2023. Stanford and MIT study: A.I. boosted worker productivity by 14%—those who use it ‘will replace those who don’t’. www.cnbc.com/2023/04/25/stanford-and-mit-study-ai-boosted-worker-productivity-by-14percent. www.cnbc.com.