2016 Year in Review and a Look Ahead: AI in the Workplace Edition
November 30, 2016
In the last installment of our annual Year in Review and a Look Ahead we discussed how the 1989 film Back to the Future II was eerily prescient when it imagined a fictional 2015. Despite all of things the movie got right (electronic pay, personal drones and even hoverboards to name a few), it missed one of its biggest predictions…by a single year. In the film, the Chicago Cubs win the World Series in 2015; in real life, they won it in 2016. Better luck next time, McFly!
Whereas the film swung and missed on that one, high school senior Michael Lee knocked it out of the park by predicting 2016 as the fateful year…in 1993! All things considered, we did pretty well too (admittedly, it’s easier to foresee a year into the future than two-plus decades). For instance, we prophesized Marketing Departments’ struggles in the face of user-generated content and envisioned that purpose-built mobile apps would take over the world.
Can we do it again? We’re confident enough to dust off our crystal balls and give it a shot by taking on artificial intelligence. Brash? Perhaps a little. While last year we tried to be Doc Brown; this year we hope to be like Mike.
The State of AI in 2016
While 2015’s sci-fi film Ex Machina and HBO’s nail-biting series Westworld have more than a few people worried about a future in which self-aware androids plot to destroy humanity, AI circa 2016 has been a bit more benign. That’s not to say it’s not exciting, it’s just far more likely to recommend the above titles to your Netflix queue than to take over the world. From recommender engines to natural language processing, AI is conspiring…to make our lives easier? Bots were the big story in the workplace this past year, helping organizations handle everything from managing support tickets to streamlining workflows. While machine learning is making inroads into the massive amounts of data that’s being collected, it’s still mostly up to humans to make the tough calls based on the analysis of that information. Expect that to begin to change in 2017.
Top 5 AI Trends for 2017
We’re going to start off our predictions this year with an easy one. Big data is going to get bigger in 2017. Much bigger. By 2020, the digital universe is set to grow to 44 zettabytes. But you already knew that. The real reason we wanted to share this one is to put that number in perspective. 44 zettabytes is enough storage to stream your favorite SNL sketches continuously on a loop for the next 7 billion years—in HD! If you prefer never-ending diabolical schemes to David S. Pumpkins, you can spend eternity watching episodes of House of Cards instead. In the coming year, machine learning will get much better at combing through all of that data. In some cases, it will acquire the ability to not only recommended content as you need it, but to anticipate your needs and offer up information even before you think you need it.
Today, there are more devices connected to the Internet than there are people on the planet. Before you scoff at why on earth we need all of those “dumb” things, consider one example: the navigation app Waze. Today, Waze mostly relies on crowdsourcing to help tens of millions of drivers “outsmart traffic” worldwide. As the Internet of Things (IoT) evolves and expands, sensors embedded in cars (including the engine and fuel tank) will add even more power to the app by alerting you to maintenance issues or guiding you to the nearest gas station before you run out. On the work front, companies across all industries will use sensors plugged into their organization’s collaboration hub to exchange real-time data on everything from delivery delays to controlling the office environment based on people’s preferences and personal algorithms—all without human intervention. It doesn’t sound so dumb now, does it? 2017 will be the year the IoT goes mainstream; and it will be so intuitive you will hardly even notice.
In 2017, predictive analytics will begin to play a bigger role in decision-making within an enterprise. Today, more and more employees are involved in non-routine work, which can make choosing individuals for specific teams or certain jobs a headache for leaders. Network analysis of metadata can take the pressure off by accurately identifying the right people for the right projects and teams, regardless of department, role or title. A recent McKinsey study found that predictive analytics can shorten the sales process by up to 30 percent and increase conversion rates by up to 10 percent! By picking out the amplifiers and drivers across a network, predictive analytics has the added benefit of freeing executives to focus on other important matters such as innovating and creating business value.
While team-based messaging apps may have been all the rage in 2016, look to 2017 to be a year of consolidation in the collaboration space. That’s because all of the apps companies are relying on today add to one the biggest problems enterprises face: fragmentation. A collaboration hub that integrates all of those disparate solutions solves many of the higher order problems executives face that ESNs, chat-based apps and document-centric solutions simply can’t. Whereas all of those “noisy” tools create their own metadata, ensuring their value is limited to specific individuals and teams, a hub collects information across the enterprise, making it visible, searchable and memorable—today and into the future. Beyond 2017, as it adds to corporate memory, the work graph will become even more powerful and intuitive, eventually taking on more and more of the decision-making duties in organizations.
Interactivity: Voice-first and VR
2017 is the year Voice-first and Virtual Reality (VR) infiltrate the enterprise. Quality and speed upgrades in speech recognition technology have made playing music, ordering pizza and checking the weather easier at home; now they’re set to help you organize your inbox, create content and streamline meetings at work as well. On the VR front, technology and device improvements will begin to drive some truly incredible innovations in the coming year. Imagine using VR to review large-scale company process improvements. For example, AI recommends efficiency gains by consolidating 100 stores, three company offices and two manufacturing plants. Executives then take to VR to not only see, but to interact with the impacts the changes will have on consumers, the supply chain and employees, thus allowing them to make more informed decisions. And you thought VR was only good for gaming.
How will we do with our 2017 predictions? Only time will tell.
Tune in tomorrow for our “2016 Year in Review and a Look Ahead: The State of Enterprise Collaboration” Edition!
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