There is a rise in the use of conversational interfaces and much talk about how these personalized AI-powered speaking computers will unseat the graphical user interface in the near future. Artificial Intelligence (AI) is at the heart of this revolution with applications becoming intelligent at understanding natural language and learning user preferences. Conversational interfaces today are what mobile apps were in 2008. When Apple launched the App Store to start the app frenzy these early entrant apps were clunky and difficult to use with many companies just shrinking their websites to fit on a mobile screen. However, in a few years, design best-practices and plenty of open source libraries emerged for everyone to facilitate modern looking and user-friendly smartphone apps. As a result, we got many billion dollar mobile-first companies such as Instagram, Uber, and Airbnb.
The Current State of the Enterprise
Conversational apps might follow a similar trajectory as we are already seeing Alexa, Google Home, and Cortana leading the way for conversational devices in the consumer space. However, the enterprise users are once again lagging behind on the wave. Large enterprise software companies are still grappling to provide decent mobile experience to their users, therefore, cannot be relied on for innovating the conversational interfaces.
Also, there is enough evidence to support that there is a high failure rate in end-user adoption with enterprise software applications. As per a Gartner Inc. report “70 to 80 percent of business intelligence initiatives end up failing.” And this is because several enterprise systems function in siloes and lack the ability to centralize organizational information that can be shared across all functions, levels and management hierarchies. One of our clients and the VP of Sales for a large US-based pharma company sighs, “I am always looking for information.”
Besides, enterprise collaboration platforms are noisy, lack information searchability and a compelling, seamless one-click experience. And so, there is a heavy dependency on IT for administrative tasks like pushing in data and pulling out reports. Also, enterprise information systems are built exclusive for desktop and lack a mobile leitmotif. Well, solving this software adoption problem is more difficult than making the software itself.
The Advent of Enterprise AI
Developing a computer that can think like a human brain and converse with us in a natural language has been the Holy Grail of technology. However, the past few years have seen immense progress in the area of AI due to the availability of data, the shift to cloud computing and powerful algorithms developed by AI researchers. Various permutations and combinations of big data analytics, machine learning, artificial intelligence, business intelligence, and natural language processing have given the machines an ability to interact with humans through speech and text.
Having said that, we believe that AI for the enterprise is still in a very nascent stage. We are still stuck between two diametrically opposed versions of AI — on one side there is our simple world of Alexa and Siri playing songs and ordering items for us and on the other side there is a more complex enterprise world where cognitive computing is still working hard to mimic how the human brain works. Although AI is the new black, the conversational experience on the consumer side isn’t as easily portable to enterprise due to data complexity, tribal language and complex workflows in organizations. It presents a massive opportunity for innovative companies to create a new category in enterprise stack to bridge the massive adoption gap.
Way forward: The World will soon be Conversation First
Despite the widespread adoption of web and mobile interfaces, most enterprise software failed to cross the chasm of user training. Application developers still expect their users to learn how to use their applications and continuously refine it for the wider user base. This results in a perpetual user training cycle and eventually software becoming too generic for a regular user. For example, a widely used consumer application like Facebook has so many features that a regular user doesn’t bother to learn about, even important things like privacy, and resorts to just basic operations. It is a much bigger problem in enterprise applications, where feature bloat is common and navigation not so intuitive. It is going to change soon with conversational interfaces that speak our language.
Today even a kid can start using Amazon Echo by just talking to it. These are early days of human interfaces but these applications will start to learn and adapt to user preferences soon. The more you use it the more it learns about you. Gartner predicts that by 2020, customers will manage 85% of their relationship with an enterprise without interacting with a human. And why not? As this Genpact study rightly points out, it is easier for humans to speak than to type. Hence, we believe the world will soon be conversational first in a few years. Entrepreneurs and users will first seek a learning and highly personalized conversational interface followed by mobile and desktop applications. We would not be surprised to see a new crop of billion-dollar companies emerging from this technology wave.
For the past few years, many boardroom discussions may have echoed with ideas and plans for a digital transformation, thanks to the advent of the internet and later the penetration of smartphones. Today, these discussions are moving toward building a conversation first enterprise. Is your’s ready to make this shift?