Chatbots have taken a quantum leap forward in user support, contributing substantially to the emergence of the modern service desk. Even in their earliest form, they heralded the promise of versatile new advances to come, such as sentiment tracking, NLP and machine learning.
Copyright by www.forbes.com
As chatbots evolve, we are seeing a continuum of progress that will soon make it nearly impossible to tell the difference between human and artificial intelligence in service desk and customer service functions. I believe it’s enlightening to understand the chatbot journey, as it has evolved from the first generation to next-gen conversational AI that is unsupervised and context-aware.
First-Generation Chatbots Leave Room For Improvement
As chatbots began to evolve, their popularity and ubiquity revealed some deficits. For one, lacking true AI capabilities at this stage, they offered scripted and robotic user experiences. These rule-based chatbots worked acceptably for simple FAQ content, but even at this stage, a new horizon of functionality was opening up: Chatbots could potentially do a lot more. Early versions were also burdened with a long time to value — at least nine to 12 months to build and deploy.
As an emerging technology, chatbots initially called for a specialized skill set requiring data science and engineering expertise. The cost of a dozen or more experts and chatbot-dedicated software engineers, as well as the time required, made first-generation chatbots less cost-effective than they could be.
Traditional chatbots also required manual training, which could take six to nine months and again require engineers and experts. Because they could not learn autonomously, chatbot training was not a one-time event but rather an ongoing, continuous process.
The Demand For Personalization
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. This includes contextual understanding at all times. It quickly became obvious that only sophisticated AI could provide that quality of user experience. Organizations working to apply AI to their customer support and service desk risked falling short on key user expectations.
Covid Presents A Demanding New Landscape
Covid-19 has altered the business landscape, perhaps permanently, affecting countless aspects of the work experience itself, including the role of chatbots. Remote work was once reserved for family exigencies, new construction, weather emergencies and so forth. But now, most organizations have had to adopt a remote workforce at blazing speed to survive, let alone thrive and grow. […]
Read more: www.forbes.com
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
Chatbots have taken a quantum leap forward in user support, contributing substantially to the emergence of the modern service desk. Even in their earliest form, they heralded the promise of versatile new advances to come, such as sentiment tracking, NLP and machine learning.
Copyright by www.forbes.com
As chatbots evolve, we are seeing a continuum of progress that will soon make it nearly impossible to tell the difference between human and artificial intelligence in service desk and customer service functions. I believe it’s enlightening to understand the chatbot journey, as it has evolved from the first generation to next-gen conversational AI that is unsupervised and context-aware.
First-Generation Chatbots Leave Room For Improvement
As chatbots began to evolve, their popularity and ubiquity revealed some deficits. For one, lacking true AI capabilities at this stage, they offered scripted and robotic user experiences. These rule-based chatbots worked acceptably for simple FAQ content, but even at this stage, a new horizon of functionality was opening up: Chatbots could potentially do a lot more. Early versions were also burdened with a long time to value — at least nine to 12 months to build and deploy.
As an emerging technology, chatbots initially called for a specialized skill set requiring data science and engineering expertise. The cost of a dozen or more experts and chatbot-dedicated software engineers, as well as the time required, made first-generation chatbots less cost-effective than they could be.
Traditional chatbots also required manual training, which could take six to nine months and again require engineers and experts. Because they could not learn autonomously, chatbot training was not a one-time event but rather an ongoing, continuous process.
The Demand For Personalization
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. This includes contextual understanding at all times. It quickly became obvious that only sophisticated AI could provide that quality of user experience. Organizations working to apply AI to their customer support and service desk risked falling short on key user expectations.
Covid Presents A Demanding New Landscape
Covid-19 has altered the business landscape, perhaps permanently, affecting countless aspects of the work experience itself, including the role of chatbots. Remote work was once reserved for family exigencies, new construction, weather emergencies and so forth. But now, most organizations have had to adopt a remote workforce at blazing speed to survive, let alone thrive and grow. […]
Read more: www.forbes.com
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
Share this: