Alexa for Business: Difficult Journey?

alexa-for-business-difficult-journey

On November 30, Amazon announced the availability of Alexa for Business , touting the idea that Echo devices can manage conference room meetings and handle personal productivity, such as perform hands-free calling and messaging, auto-dial conference calls, help schedule meetings, manage to-do lists, and find information on business applications like Salesforce or Concur.

While conversational user interfaces and virtual assistants will undoubtedly someday permeate the workplace, Alexa and Amazon face some challenges today.

Personal versus Corporate Context

At home, it is not critical that Alexa knows who you are. At work, it would seem to be critical that Alexa does know who you are for purposes of nearly any task Amazon described as potential for Alexa to perform. (Note: Amazon does have roles for shared Echo devices for the management of conference room meetings/video conferencing). You would have to assume users interested in calendaring, to-do lists, and auto dialing conference calls would have to identify who they are every time they use it.

Integration with Office 365

According to the announcement, Alexa for Business does work with Microsoft Exchange Calendar. While that is great, it is doubtful that Microsoft will look kindly upon deep integration of Alexa with its Office 365 suite of business applications. Since Microsoft has such a dominant position in business applications, this will present problems for Amazon.

Voice Assistants in Cubicle Land

Everyone who works in shared office space enjoys that one person who uses a speakerphone all the time. Those people are very popular. Can you imagine the frustration of people who work in cubicle land trying to use a voice assistant? There might be lawsuits. Certainly, there will be many pranks. Does this limit Alexa for Business to those with a private office?

Business Application Virtual Digital Assistants in the Workplace

Due to the popularity of Slack, a wide range of business application providers and communications platforms have begun to focus on enterprise productivity and collaboration tools in the form of text-based chatbots, or virtual digital assistants (VDAs). Most of these chatbots live on conversational platforms, such as Slack, HipChat, Microsoft Teams, SAP Jam Collaboration, Cisco Spark, and others. Enterprise chatbots can perform a wide range of functions, such as meeting scheduling, managing and transcribing stand-up meetings, proofreading, and project management.

In addition to productivity and collaboration, VDAs are being used to improve workflow and project management. Typically, generating large amounts of complex data that needs to be analyzed and monitored, project management is a use case that is ripe for NLP adoption for some redundant tasks. Particular value can come from the ability of NLP combined with ML to automate monitoring of a broad range of devices and platforms for a real-time view of status and reducing the size of larger project teams. According to a Harvard Business Review survey, administrative duties of a project, such as determining work schedules and checking on shipments take up 54% of a project manager’s time. Teams that work within Slack have access to many chatbots and applications for workflow and project management, including Fireflies.ai, Trello, Asana, Wunderlist, and Pivotal Tracker, just to name a few.

Collectively, VDAs for productivity, collaboration, workflow, and project management make up the use case for business application VDAs.

In our recently published report, Virtual Digital Assistants for Enterprise Applications, Tractica forecasts that business application VDAs will generate $3.3 billion in enterprise VDA software revenue between 2017 and 2025. Tractica expects that major business application players, such as Microsoft and Salesforce, will begin to dominate the business application VDA market by 2020. These larger players will deploy their own business application VDAs as part of their software platforms, using them not as direct revenue generators, but as enhancements to their core business application services.

Business Application Virtual Digital Assistant Players

Julie Desk

Julie Desk is competing in the personal scheduler space. The virtual assistant “lives” within your email, with the ability to schedule a meeting on your behalf or respond to a meeting request simply by cc’ing it. The VDA is not completely based on artificial intelligence (AI), but requires some human supervision.

Julie Desk also competes with players like Calendly and Doodle/Meekan, although each has different approaches (Calendly helps you manage your schedule, but is not technically a VDA. (It does not use natural language processing [NLP] and is a rules-based piece of software. Meekan is an AI-fueled VDA, but it lives within enterprise chat platforms like Slack, HipChat, and Microsoft Teams.)

“Julie requires much less work than Calendly, she has more intelligence,” said Chief Executive Officer (CEO) Julien Hobeika, “Julie can estimate your travel time for a physical meeting and will figure that in when scheduling your meeting.”

Hobeika said Julie Desk has resonated with small businesses. “The concept of calendar management is more mature in the U.S.” said Hobeika, “The culture in the U.S. is more business focused and willing to let tech do this type of work.” Hobeika explained that, globally, big companies thinking about VDA scheduling want to customize it. The company is licensing its software for that purpose. According to Hobeika, the barrier for most businesses is concern about security. To address this, Hobeika said Julie will soon be International Standards Organization (ISO) certified. The company is also offering the solution via a single tenant cloud.

Talla

Startup Talla has pivoted slightly since Tractica’s 2016 VDA report. Previously, Talla founder Rob May’s vision was to tap into a company’s common knowledge to build a useful database and fuel a useful, internally-focused VDA. “In our research, we found that companies were looking for ways to automate some HR communications and knowledge sharing on systems like Slack,” said May in June 2016. “They wanted to find an automated way when employees had HR questions to tap into the handbook, and also for a way to automate onboarding new employees. So, we built Talla, with NLP and AI, to do that. So, if Talla doesn’t know the answer, she can go out and find the answer to build the knowledge base. Well, how? Talla focuses on systems that aren’t in domains, but could be in someone’s head.”

Today, Talla has de-emphasized the development of the unstructured knowledge base and instead focused on automating internal IT service desks, human resources (HR), and other internal service teams. Talla sits in enterprise messaging platforms like Slack, HipChat, and Microsoft Teams. The company raised $8.3 million in Series A funding in June 2017.

Microsoft

Microsoft is positioning itself to become the dominant player in the enterprise messaging platform space with the launch of Microsoft Teams. Teams is a conversation-interface collaboration and productivity platform designed to rival Slack, with one distinct advantage: Teams lives within Office 365 and can, therefore, tap into the vast installed base of global Office 365 users (100 million active users, according to Microsoft).

Microsoft, perhaps more so than Slack, is enterprise chatbot-friendly in that Teams will likely appeal to a much broader audience than the typical tech and app developer communities drawn to Slack. In addition, Microsoft also has an advantage with larger enterprises, a market segment that has been difficult for Slack to penetrate. Microsoft makes its Bot Framework authoring tools available for free and for developers to use across various platforms, but the genius of that strategy is that Microsoft is betting developers will look closely at placing their collaboration, productivity, work flow, and project management-related chatbots on Teams. Tractica believes Microsoft Teams will quickly gain traction as an enterprise messaging platform and for chatbot use, although it will take a few years before Microsoft catches Slack as the largest enterprise messaging platform.

Converse.AI

When it comes to enterprise chatbots, two tech giants, Google and Facebook, are leaning on a small startup partner, Converse.ai. In May at Google.io, Converse.ai launched its partnership with Google to power chatbots on Google Assistant and announced it was a launch partner for Workplace by Facebook. Converse.ai chatbots are designed from the outset to integrate with the existing tools, services, and business workflow of the companies using them, without the need for additional code or software.

In 2015, CEO Tony Lucas observed that messaging was getting bigger and bigger, “but enterprise use of messaging was incredibly nascent,” said Lucas, “Humans want to interact with companies via messaging, and automation, in my view, is the only way to make that work.” Thus, Converse.ai was launched in 2016 with the goal of focusing on enterprise chatbots.

Lucas built several bots from scratch in 2015. “I started thinking about the use cases, and the challenges, then started to think about the architecture, said Lucas. “I wanted to take the code out so that HR people or some other non-tech could build a bot. Which brought us to a graphical platform to build these workflows but with a conversation interface. Every time we saw a trend in that, we built a module that could address the issue. We now have 300 modules. For enterprise, 2017 is a year of less hype for chatbots and more about, ‘oh yeah maybe this is useful’.”

Lucas said the early focus within Workplace by Facebook with its chatbots come from HR. “They are looking for ways to increase the flow of communication about things like vacation requests, shift swapping, perhaps safety reporting,” said Lucas. In terms of use case momentum, Lucas is sold on workflow management. “I think workflow is far more interesting than other use cases and we think our product is well suited for it.” Lucas also said the company is developing an application programming interface (API) platform as well, but did not share a specific timeline for launch.

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