2020: The Year Digital Colleagues Master Conversation

By Juan Martinez, Senior Writer
December 3, 2019 • 4 minute read

Digital Colleagues and AI systems have improved their usage of conversation. Learn how to create smarter systems.

With 2019 rapidly drawing to a close, we’re examining trends and topics that will be at the forefront of the AI industry next year with a new blog series running throughout December: The IPsoft Top 5 in AI 2020. This is the first in the series.

The past several years have produced Artificial Intelligence (AI) systems for the enterprise that are capable of using conversation to interact directly with users, yet very few systems have mastered human dialogue completely, if at all successfully. In 2020, crucial updates to how organizations apply natural language technology to AI deployments will reshape how Digital Colleagues recognize and use language to deliver human experiences at machine speed. Additionally, the speed with which companies put AI systems to use will accelerate exponentially, thereby allowing implementers to more quickly refine and perfect projects, which will in turn produce faster return-on-investment (ROI).

In this post, we’ll examine four crucial ways in which Digital Colleagues and AI systems have improved their usage of conversation to produce better experiences, and will continue to do so. We’ll review better ways to access, deploy, and converse with Digital Colleagues, regardless of use case, and how better conversation will in turn help create smarter systems.

AI Will Be Deployed More Rapidly

Most enterprise AI deployments require hours of meetings and a broad team of deployment specialists to get a use case up and running. Starting in 2020, the process will be as simple as downloading a game onto your iPhone. You will be able to log onto a marketplace where Digital Employees are arranged according to skills. You’ll select the ones you need for your business (Wi-Fi Troubleshooter, Benefits Specialist, Credit Card Account Manager, etc.) and “interview” the AI-powered worker before making an investment. If the employee meets your company’s standards, the solution will self-configure and integrate to your company’s cloud-based servers and systems — meaning ROI comes in days and weeks, not months or years.

As this model takes hold, conversation will make or break Digital Colleagues’ value to a business. Poor dialogue will turn potential users away, which means AI providers will be laser-focused on producing near-perfect out-of-the-box conversational experiences. You wouldn’t hire a banker who doesn’t understand the industry’s specific language and contexts. Similarly, you would not hire a Digital Colleague who cannot speak fluently to customers about your business — so the better the conversational skills, the higher potential for success, as more businesses will discover starting next year.

Use Cases Will Be Built Through Dialogue

What happens if the use case or skills you need are not available on a marketplace? Is the default position another drawn-out development process? Thankfully, no. Digital Colleagues will increasingly be able to work with you to create the experience required, and do so via conversation. The solution will learn and improve as you work with the system, almost like a new employee learns during training and orientation.

Ideally, Digital Colleagues will be able to handle the back-end technical specifics on their own, with APIs into cloud-based systems that will require little or limited integration through human intervention. This will allow company leaders in 2020 to focus on business processes, the user experience, and overall user satisfaction.

Digital Colleagues Will Learn Conversation More Quickly

Thanks to improvements to Natural Language Processing (NLP), Digital Colleagues will become even better equipped to handle new phrases, utterances and colloquialisms in 2020. Instead of attempting to learn new phrases one at a time, which can create a backlog of unused knowledge, Digital Colleagues will use machine learning to cluster unrecognized utterances so that unknown phrases can be learned in bulk. This will accelerate optimization during the production process so that improvements happen in a single episode rather than through multiple ones. For example, with this approach, a Digital Colleague will learn more quickly that phrases such as, “My password isn’t working,” and “I need to reset my password” are asking for the same outcome, just in different ways, so the issue can be addressed even more quickly than before.

Digital Colleagues Will Learn Skills More Intuitively

As Digital Colleagues improve their conversational acumen in 2020, they’ll also start to identify requests and cluster intents for more rapid implementation of new skills. As a result, Digital Colleagues will not only learn words and phrases faster, they’ll also be able to sort and apply new knowledge to real-life use cases. Words that previously may not have triggered intent recognition will now become part of the system’s intent recognition toolset, which will allow digital workers to more quickly and organically understand why a user is contacting them.

Just as words and phrases will be clustered for faster learning, so will new skills to words describing their functions. As a system learns, for example, that the words “recover,” “lost” and “message” typically apply to deleted email recovery, the system will work with human experts to create a deleted email recovery skill. In other words, Digital Colleagues will begin to learn what users need and prompt the creation of new skills as required.

Conversation, while a uniquely human ability, is being transferred to the digital realm as AI technologies continue their expansion into the lives of consumers and business users. On the enterprise front, 2020 is poised to be a year when conversational Digital Colleagues do more than sound human when they interact with end users; they will begin to use conversation as an essential element in their own deployment, optimization and learning. Overall, this will help businesses accelerate their own AI journeys with new use cases and faster time to value.

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