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Can your business afford to lag behind while competitors harness GenAI to transform their customer service operations? The question is not whether to adopt AI, but how soon you can afford to do so?
With the market size for generative AI in customer service projected to surpass USD 2.9 B by 2032, the urgency is quite undeniable. Gartner Impact of GenAI Survey showed 69% of tech CEOs "are interested in using GenAI for customer success/service". Clearly, businesses that fail to start embedding AI now will be struggling to fit a patchwork of AI into their existing solutions later. Unsure where to put their investment, they will be either a ‘late majority’ or a ‘laggard in the market.
On the other hand - By combining generative AI with rich enterprise service data, early adopter customer service organizations are set to deliver stand-out digital experiences that increase first call resolution rates (FCR) for agents so that they find dot precise answers to customer queries at the first go!
Imagine a service agent, Emily who can generate answers with a single click. AI highlights questions buried in long email threads and scavenges content from past communications. LLMs provide natural language answers grounded in company information, empowering Emily with intelligent QA to answer customer queries on the go! She can prepare case summaries, collaborate internally, and update customers with AI-generated emails. When a service ticket is created, AI categorizes it automatically, enabling her to route it to the relevant teams. For similar incoming tickets, Emily is recommended top similar ticket solutions to check for possible answers. With access to 360 customer profile, she can stay updated on recent cases and marketing promotions.
Relevant to Industry? The Utilities sector, for example, can benefit from AI-powered customer service solutions for managing inquiries, billing, move-in/move-out processes, energy usage optimization etc. An AI empowered service agent, in a Utilities Contact Center, like Emily, can efficiently handle move-in /move out requests. When routed to a call from a customer moving to a new home, she can view customer's 360 profile (contracts, premise details, point of delivery), can quickly gather additional information (on pending outstanding, unbilled units during move-out) and then schedule the service activation. If a billing dispute arises, AI can quickly analyze customer sentiment, retrieve billing history and recommend a solution with possible corrections (adjustment reversal, corrected meter readings, better plans, list of devices with consumption spike etc.).
Industries, such as Retail, Telco, Banking & Financial Services, Healthcare etc. are also well-positioned to be early adopters of GenAI in customer service due to their high volume of customer interactions and potential for significant efficiency gains.
Cost Savings: A 2023 McKinsey study estimated that applying generative AI to customer care functions could increase productivity from 30-45% of current function costs. To quantify such outcomes, first movers focus on two KPIs: first call resolution rate (FCR) and average handling time, which together enhance agent productivity. With AI, if FCR rate can jump by 10-20 percentage points, reaching 75-90%, then no more than 10-25% of customers should need to call back regarding the same issue. The business can thus anticipate substantial savings on repeat inbound calls and reduced operating costs. A recent NBER research found out that agents who leveraged AI could handle 13.8% more customer inquiries per hour and time spent handling an issue reduced by 9%. It also reduced agent attrition and requests to speak to a manager by 25%. Now, all this time saved by agents can be allocated to high-value tasks, proactive outreach, process improvements, and enhancing customer relationships.
NPS and revenue impact: Using LLMs, customer data can be analyzed, rapidly processed, and actioned on. Needless to say, the technology can detect patterns and correlations, and focus on improving the experiences of promoters while addressing the concerns of potential detractors.
Early Adopter or Early Majority? If your organization hasn't yet become an early adopter, it's time to pinpoint where Generative AI can make the most substantial impact. Start by incrementally integrating AI tools to augment service operations (be it hyper personalization, harnessing intelligence from customer conversations, generating automated email replies for agents, co-pilots etc.). Invest in enabling service agents to leverage AI effectively and continuously monitor & optimize performance with gradual adoption. As the technology matures, in years to come, your organization should aim to be...
Equipped to set up AI governance or maturity framework.
Figure out how to scale AI across departments.
Able to (incrementally) measure quantifiable business outcomes with AI usage.
Tomorrow’s future showcases fully AI-enabled service organizations that will deliver unmatched personalization, higher productivity, and intelligent customer support experiences – Can your business afford to be left behind?
If you are ready to get started with generative AI to drive business value, check here to know more!
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