When a highly scripted robotic chatbot can't predict user intent or engage in meaningful, dynamic dialogue, user interaction suffers. In this relentless environment, and to meet rising user expectations, organizations are now leveraging AI and machine learning (ML) into a revolutionary new paradigm of semantic understanding that seamlessly integrates with ticketing, knowledge, and IAM systems. AI can address the need of remote workers for self-service and enable them to autonomously resolve requests and sustain employee productivity in the pandemic.
But now, most organizations have had to adopt a remote workforce at blazing speed to survive, let alone thrive and grow.Īs a result, the remote office has now emerged as "the new normal." Artificial intelligence, with its capacity to scale support for remote work has swiftly moved to the forefront as an in-demand technology, spurring chatbot evolution toward third-generation capabilities. Remote work was once reserved for family exigencies, new construction, weather emergencies and so forth. Organizations working to apply AI to their customer support and service desk risked falling short on key user expectations.Ĭovid-19 has altered the business landscape, perhaps permanently, affecting countless aspects of the work experience itself, including the role of chatbots.
It quickly became obvious that only sophisticated AI could provide that quality of user experience. This includes contextual understanding at all times. Thanks to the digital revolution - and to Apple, Google and Amazon driving expectations - today's users expect no less than a consumerized, personalized experience, with services available at the push of a button on any device.
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