AI is great, but why do I still run out of toilet paper at home?

If we start to focus tasks that are easily automated and improve productivity, we may finally cut through the hype and have something to show when we say, “this is the year of AI.” And that’s something we can all get behind.

frog toilet
Alexas_Fotos via Pixabay (Public Domain)

There’s been a lot of buzz about what artificial intelligence is capable of doing lately. From writing poetry, to predicting the winner of the Kentucky Derby, and even beating a world champion chess player – it seems that machines are poised to start doing some incredible things in the near future.

Or maybe not. With all the hype and click-baity articles promising the future of this technology: the self-driving cars, the home robots, even reports on Skynet and the A.I. singularity… What progress do we have to show for it in 2017?

And more importantly, why aren’t we focusing on the routine, mundane or easily automatable tasks that often take up so much of our time? Before we build autonomous vehicles, maybe it’d be helpful to have something that reminds us when we’re almost out of toilet paper – so we don’t wind up stranded on the can with nary a roll in sight. Where is the AI to take care of that?

There are so many real-world applications we could build that would have a huge impact on our lives. And yet in the working world, it seems like no one is focusing on practical business applications for A.I. technology. Here are a few areas where innovation could significantly improve business and team collaboration.

Automated meeting notes

As the founder of a video conferencing startup, it’s interesting to consider the potential uses for artificial intelligence as it concerns meetings and conference calls. There is a real focus in the collaboration industry on how to continue making meetings more natural and productive. Innovations such as spatial audio recognition (making users louder/softer depending on where they stand in relation to the microphone) and cameras that automatically reposition to focus on the person talking are starting to become more common.

But while strides have been made, there is still a ton of untapped potential to unlock through artificial intelligence. For example, mid-meeting idea exchanges can get stymied as participants focus their energies on taking notes instead of thinking creatively. Imagine a conference experience in which software not only records and transcribes the call, but also distills the most important conversation points into an easily digestible round-up that can be accessed and shared later.

This kind of small, but useful feature could fundamentally change the dynamics of meetings by allowing workers to be continuously present in the conversation. And while some of this technology is undergoing development and testing, we still haven’t figured out practical ways to fully integrate machine learning with our daily tools in a universal way.  

Virtual assistants for enterprise

Over the last few years we’ve seen the proliferation of virtual assistants like Amazon’s Alexa, Microsoft’s Cortana and Google Assistant. Paired with smart speakers, these tools are now used by millions of people every day to place food orders, dictate text messages, and stream music using simple voice commands. But how has any of that translated to business?

As these assistants become increasingly ingrained in everyday life, enterprise applications haven’t kept pace. We haven’t yet developed virtual assistants to serve an entire company by performing tasks like scheduling meetings or calls between employees, ordering a car for a client meeting, or responding to emails and Slack messages on your behalf. Right now, these are on the radar, but at this point nothing more than hypotheticals.

And although this technology is still in its early days, the idea of a ‘virtual enterprise assistant’ doesn’t seem so far off – if only tech companies would choose to more fully pursue the development of those use cases. Such a solution could save valuable time and resources, and be a major boon for productivity.

Customer service chatbots

Businesses know that creating an excellent customer experience is of the utmost importance to their long-term success. It may seem like backwards logic to apply artificial intelligence to a distinctly human interaction like customer service, but when you consider the potential that chatbots are capable of, you can start to see a clearer picture of where we’re headed.

While chatbots are starting to crop up everywhere, the current iterations of this technology are more of a novelty than they are useful, and in some cases even do more harm than good. You probably recall Microsoft’s failed Twitter chatbot last year, which began spewing racist and sexist messages it learned from users and forced the company to pull the plug less than 24 hours later. But once we can solve for those machine learning issues, chatbots can become the next great asset for customer service teams.

Chatbots have the potential to reduce the frustration associated with hold times and call transfers when paired properly with current customer service systems. Bots can also glean key information from the customer and begin to develop smart insights that service agents could leverage to troubleshoot issues more accurately. They may eventually be able to handle entire conversations and resolves issues without the need to wait for an available human agent.

We are already starting to see this technology come to life, smartly integrating into messaging tools such as Facebook, Whatsapp and Slack. With further integrations and use cases chatbots stand to streamline the entire customer service process, and provide small businesses the ability to deliver that ideal personalized customer experience, even while they’re still growing.

While the theme in Hollywood continues to be doom and gloom when it comes machines, the future of business and productivity looks brighter than ever if tech providers can find practical uses for the AI they’re developing. The opportunities for this technology to touch and improve our lives are nearly limitless, but real progress has yet to be made on applications that make us feel like the AI era is truly upon us.

If we start to focus on those tasks that are easily automated and improve productivity, we may finally cut through the hype and have something to show when we say, “this is the year of AI.” And that’s something we can all get behind.

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