Chatbots, artificial intelligence (AI), and natural language user interfaces (NLUIs) are making it increasingly feasible for humans to have realistic conversations with software applications. For example, chatbot developer Kore, Inc., is working with the SAP Co-Innovation Lab to create solutions that suggest possible actions to users when a sales opportunity has changed, an order is delayed, or an expense needs approval.
While these solutions are not self-aware, experts are working to create networks that emulate the way information traverses the brain. Such groundbreaking research may eventually result in AI that is able to learn, improve, and converse naturally with users.
Kris Hammond, founder of the University of Chicago’s AI laboratory, envisions a type of applied AI that will enable this type of seamless dialogue between humans and machines. He says: “Conversation as an interface is the best way for machines to interact with us using the human tool we already know exceptionally well – language!”
A new computing era is already here
The technologies for enabling AI conversation are evolving faster than ever, and the future will be defined by how quickly business leaders incorporate these solutions into their operations.
Success is being shaped by many factors, including more digitally demanding employees, customers, partners, resource scarcity, and data abundance. And technology is helping companies run better and improve people’s lives by revolutionizing how they experience computing.
Machines are getting better at understanding language
Personal assistants such as Amazon Alexa and Google Home have already established a beachhead in the consumer market and are beginning to find applications in the business world. Soon, AI conversation will become the default for making experiences more seamless, simple, and efficient – whether controlling a robot or ordering a ride.
As AI becomes better at understanding what conversation is, it will play an increasing role in enabling life experiences.
But the nuance of language is still a challenge
Of course, challenges remain. Language is full of idiomatic phrases, dialects, and regionalisms. Machines must be able to understand these nuances for ongoing innovation to occur. The ultimate goal for many AI experts is to create a user experience that does not require a screen-based user interface.
The complexity of language means that style, tone, and sentiment have a direct impact on the value and effectiveness of devices such as chatbots and their underlying AI systems. Developers have to anticipate numerous variables, program rules, and defined inputs to anticipate what users will say to machines and what machines may say (or do) in response.
Consequently, AI conversation will not thrive until it can understand not just the words a person is using but also their underlying meaning. For example, someone speaking a dialect of southern U.S. English might ask a friend to “carry” her to the store. Any native speaker would know that this person is asking for a ride in the friend’s vehicle. Someone not familiar with this expression would certainly request a clarification. An effective AI system needs to possess enough awareness to be able to understand the intent of a question or a command or, at least, when to ask for clarification that will result in the desired action or outcome.
Predicting outcomes is one of the most promising applications for AI
Companies are starting to integrate these technologies with sensors in Internet of Things (IoT) applications. For example, SAP is combining a cloud platform with Kore chatbots to create rules-based alerts for vending machines, coolers, power tools, and other connected devices. Instead of waiting for a failure or making unnecessary trips for preventative maintenance or restocking, programming, rules, and mathematics will help users make statistically valid decisions while saving resources and improving outcomes.
The trend for these technologies is integrated systems capable of independent learning and thought and autonomous actions. Some AI developers are eager to realize this technological singularity. Whether or not that goal is achieved, chat bots, AI, and NRLIs seem poised to fundamentally change how humans interact with and relate to the technology that underpins much of the modern world.
Interested in learning more? Check out the SAPRadio show “AI and the Conversational Era: Connecting People to Technology” and @SAPPartnerBuild on Twitter.