For over two years, teams at the SAP Innovation Center Silicon Valley have been exploring natural language-based interfaces and cognitive abilities in the context of enterprise software. The projects range from enabling an executive dashboard on a large-scale video wall using voice recognition, authenticating users to business systems by analyzing the individual characteristics of their voices and faces, to the most recent focus area, Enterprise Bots – the incarnation of chatbots in a business context.
The Innovation Center Silicon Valley is exploring the space with various internal and external teams, one of them is the startup Kore. They provide an enterprise-grade platform to deploy Enterprise Bots on a large scale for a variety of business use cases.
Messaging as a Platform for Enterprise Applications
We live in times where only on Facebook’s messaging platforms (Messenger and WhatsApp), people exchange over 1 billion messages every single day and this massive trend is not just restricted to millennials. Already today WeChat is used in China by millions of users to order taxis and products, to schedule medical appointments, to pay bills and to transfer money, all using a messaging interface without having to install additional apps.
So it is rather obvious that the move towards a new user interaction paradigm bears considerable potentials also for enterprise software. Bots will not replace mobile apps just like mobile apps have not replaced desktop software. But again they will further diversify the range of alternatives to consume digital solutions and to get the job done
Chatbots in the Enterprise
Enabling humans to communicate with systems and vice versa with low friction and natural interactions using message-based interfaces has a number of advantages.
For end users, Enterprise Bots lead to an increase in productivity:
- Better Ease of Use: One interaction step to any business function, a dramatically simplified user experience even in complex business scenarios.
- Less Training Required: Business knowledge sufficient to use any software, no training necessary, users just need to know common business terminology.
- Shorter Time to Insights: Personalized, contextual, dynamic, and robust understanding of user input.
- Minimal GUI: (Semi-) autonomous generation of bots based on existing APIs, mostly text-based interactions augmented with existing WebViews or shortcuts to existing applications.
- Autonomous Improvements: Continuous improvement of capabilities and quality through unsupervised learning based on user input, user behavior, and business data.
- Centralized Learning: A holistic NLP and AI engine which provides the interpretation of natural language and intent is trained centrally, serving all bots and users and learning more and more about additional domains and business scenarios. What one user teaches the system also benefits all others.
Amplifying Employee Productivity Through Enterprise Bots
- A sales representative updating her latest customer opportunities using a CRM bot via Facebook Messenger.
- An office worker submitting his leave request using a HR bot via the Slack app.
- A project manager being alerted about task delays and potential mitigation actions by a project tracker bot via Telegram.
- A technician sending a picture of a broken pump by iMessage to let the service bot identify the model. The bot engine is augmented with image processing capabilities and responds with the detailed product details and suggests to order a replacement.
- A team assistant sending a mail to the facilities bot to reduce the temperature in the IoT-enabled building.
- An executive requesting a team update from his direct reports using the status bot which gathers the information from all members via WhatsApp.
- A presales engineer booking a trip to New York using a travel bot via SMS, which automatically dispatches individual requests to a flight bot, a hotel bot, an Uber bot and a calendar bot that automatically updates the user’s calendar.