Is the Enterprise MoNage-Ready?
During the past two months, I’ve spoken at four industry events – and attended four others – with a common theme being the impact of chatbots and AI on the workplace. My talks have been in the context of collaboration and the customer experience, and there’s no doubt that these trends are coming. Two of these talks have been at events for Jeff Pulver’s MoNage conference, and both were updated versions of a talk I initially gave at his March event, which I wrote about here.
Following each of these events, my talk keeps evolving, and it’s clear that the broader AI space is moving faster than IT can keep up, hence the title of this post. The innovations I’m seeing are exciting, but the business value is hard to gauge, and it’s fair to ask if enterprises are ready for what’s coming. To help do that, I’m going to share my thoughts about the intersection of collaboration and AI for two sides of any business – internally for driving employee engagement, and externally for driving customer engagement.
Internal collaboration - driving employee engagement
When it comes to internal collaboration, AI plays a limited role - so far. Mainstream UC offerings do a good job of integrating standalone communications applications, and for many businesses, that’s the objective. In that scenario, UC is living up to its namesake – literally - but we know it can do much more. With the likes of workstream messaging and CPaaS gaining traction, UC is now just one type of solution for collaboration. Of course, what makes this messy is the amorphous nature of “collaboration,” which is increasingly being defined by the latest technologies that enable certain types of work modes.
Out of all these variations, CPaaS is probably best positioned to leverage AI for internal collaboration. While the core task of integrating communications provide a good foundation for collaboration, it doesn’t bring much automation to the process. This is where the open API ecosystem that drives CPaaS comes into play, but these applications lack the intelligence that AI brings, along with the ability to engage with workers in a more human-like fashion.
The latter capability may seem frivolous, especially when the likes of Alexa and Siri are quite limited. However, those offerings are only going to improve – that’s the nature of machine learning – and we’ll soon be seeing voice-based virtual assistants at work. It’s a fair point to argue that voice is losing ground to messaging as the labor pool trends younger, but that’s not a reason to discount AI as a driver for internal collaboration.
Messaging-based chatbots may well become the AI mode of choice for digital natives, and as they become both trusted and integrated into workflows, we’ll see them handle a growing share of the workload around collaboration. Initially, this may just entail organizing meetings with the team and circulating basic documents to support the work. From there, however, expect to see chatbots interfacing with other chatbots, making low level workflow decisions without human involvement.
In this context, AI can enable a higher level of workflow automation than either UC or CPaaS can provide. For decision-makers, the business value will be to free up team members to spend more in-person time working through complex tasks and completing projects in less time. So, are enterprises ready for that yet? Probably not, but depending on how you define collaboration, these applications are coming, especially when considering how badly outsiders like Amazon, Facebook and Google want a bigger foothold in the enterprise market. They’re investing untold resources into AI, and if the usual suspects don’t bring this type of innovation to market, these players certainly will.
External collaboration - driving customer engagement
At present, this is the more compelling opportunity, especially given how pervasive chatbots are becoming in the contact center. To be fair, that type of interaction isn’t really about collaboration, since the communication is generally one-to-one, as in agent-to-customer. Popular as this flavor of chatbots is becoming, however, it’s not the only way to understand the AI opportunity.
Behind the scenes, while agents are frantically trying to assure customers they have a solution, UC enables the real-time, back-channel communication that gets the job done. Ideally, this will all be transparent to the customer, but it very much is a form of collaboration that is externally focused. This scenario is very different from internal collaboration, especially due to the pressing need to solve the customer’s problem in the moment, during that call.
When time is short, and the stakes are high, this is where the processing power of AI can really enhance collaboration. Not only can AI-driven chatbots seek out and find the right experts to support agents, but they can also gather relevant information from a wider range of sources in far less time than humans. In this context, AI delivers on the most important variable – speed – and so long as the right information is provided – which today, is far from 100% - agents can provide the kind of customer engagement that management craves.
This is another example of MoNage-readiness that reflects what’s happening with developers and the broader AI/chatbot ecosystem. Things are moving very quickly in those circles, and while most of the focus is predictably on helping businesses sell more stuff, there’s lots of attention being paid to applications that aren’t about driving commerce. If decision-makers – and channels for that matter – only see the former, then they won’t be ready for how AI can drive external collaboration.