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Customer experience channels are increasing and with them, the number of interactions with customers. Because of this, businesses are turning to automation and bots for assistance. In fact, 9% of Fortune 500 companies have already implemented bots and that number is expected to increase rapidly.
But unlike humans, bots and AI software are still unable to carry out multiple and emotionally complex operations at the same time. It leaves businesses with a complex mix of platforms and capabilities that are difficult to map to business goals.
Chart a Path Along the AI Maturity Curve
The story of bots and AI and the challenges of implementation vary widely depending on where you are in terms of maturity, and your growth plans. While most companies are eager to get more from their AI investments, random bots handling individual tasks is the norm with some connectivity to improve service. But this journey to fully integrate bots and move to a differentiated experience takes time.
The good news is that it’s easy to start small, such as using bots to enhance knowledge search, answer FAQs and provide basic support. Proactive engagement at the top end of the curve is still rare, and today it typically requires a human to initiate interaction.
Common Use Cases for Bots and Their Limitations
Bots are evolving to more relationship-based actions, and from higher customer effort to more highly automated services. Yet most businesses are simply trying to use bots and AI to automate self-service. That’s their primary use case.
Narrow-focused bots are becoming better than humans at defined tasks: answering specific questions, capturing intent, and if enabled, handing off that information to agents when needed, or even to another bot. Generalist bots get confused at times and their business value is still to be demonstrated. Still, as bots become more conversational, we see use cases move beyond simple real-time queries.
For example, a bot can automate processes when its confidence is high in the proper answer. But when the bot’s confidence is low, it nudges the agent and asks for the agent’s help. We’ll talk more about what’s required for a use case with this level of coordination.
Many bots can take care of sequences of transactions, and optimize journeys by helping customers navigate channels. And at best, bots seamlessly connect with humans and take business to a new level of AI. According to Opus Research, the trend toward hybrid human-machine cooperation is as much about empowering the human customer support team as it is about offering customers automated self-service options.
Connected Channels Is the Heart of Successful AI
Human agents are indeed a prime beneficiary of bots and AI. According to a DestinationCRM article on unified desktops, Ventana Research reports that 44% of contact center agents need to access three or more applications to resolve a single customer issue. Bots eliminate many of these time-consuming steps by giving agents instant suggestions on how to respond to individual customers, or insights into the customer based on sentiment analysis and previous customer interactions. Guiding agents through interactions helps them find better answers and deliver them faster.
Integration with human agents dramatically impacts customer experience. And until more businesses catch up, this type of human-bot connection is a major business differentiator.
A Single Customer Experience Platform for Advanced AI
In an informal poll conducted during a Genesys webinar on AI, integration was by far the top concern of most respondents in implementing bots and AI. And for good reason. Natural language processing (NLP) is a mature technology, but many vendors lack the capability to integrate NLP with self-service dialogue. Implementing NLP and AI bots with advanced machine learning typically requires high implementation and support costs; multiple languages adds to the complexity.
Even when you integrate AI and agent dialogue, consider the customer service issues. Focusing too much on the conversational element takes away from the goal of self-serving customers. And how can you ensure that you don’t over-emphasize self-service and automation and forget about the human touch?
For optimal efficiency and effectiveness, bots and humans should run on one system that connects all your platforms. That enables you to monitor and measure all agents—human and bot—using similar metrics. A single customer experience platform lets you optimize for any business outcome you choose and support future changes to strategy.
The critical role of humans in customer-focused AI is the driver for Kate by Genesys, an enterprise intelligent assistant. Kate brings together AI, bots, adaptive learning and other automation technologies for more personalized customer experiences. The combined power of Kate working with agents and other employees is what we call Blended AI by Genesys. It’s automation and machine learning working with human agents and employees. It’s also specifically focused on enhancing customer journeys across channels versus simply automating random tasks.
The Future Is at Hand
Proactive AI in which an intelligent assistant, such as Kate, automatically reaches out to customers is beginning to change the landscape. But start simply. Connect the bots that serve your business requirements—and engage your customers in natural conversations using voice, text or microapps.
As you integrate more bots and AI strategy with human agents, you’ll move further along the maturity curve. You’ll see faster resolution of problems and lower costs and complexity. Most importantly, you’ll improve the customer experience.
For more details on moving forward with your AI strategy, view our on-demand webinar Meet Kate and Discover Blended AI by Genesys: Where bots & automation collide with the power of the human touch
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