Impresarios of hip hop have long spawned businesses that capitalize on their personal brand. Jay-Z publishes music under his Roc Nation brand, Sean “Brother Love” Combs peddles vodka under the Cîroc label, Lil Wayne joins the fun with Bogey Cigars, his Cigar company.

So it isn’t too surprising that will.i.am created a tech company called i.am+ which began as a purveyor of wearable tech. What is surprising is the fact that he is now leading the company into the enterprise B2B space with Omega for Enterprise, a virtual assistant for the office:

So will Omega carry the same moxy in the office as Alexa, Siri, and OK Google do in the home? It’s too early to tell really. Hip hop and enterprise IT seem to be strange bedfellows but who knows–maybe Omega will get it started in the office, finally.

The use of bots, or “chatbots”, is an immensely impactful, rapidly-growing trend in enterprise operations and customer interaction that change the way we work. 

What is a bot?

Bots are a lightweight form of machine learning that basically converts unstructured human language into structured data that serves as instructions for the software that consumes it. For example, the following statements all initiate the same software action of adding an appointment to the user’s calendar:

  • “Put a meeting on my calendar for tomorrow at 10 am”
  • “Add appointment called ‘Meet with Bob’ tomorrow on my calendar”
  • “Invite Bob to a meeting tomorrow at 10 am”

In each case, the bot parses out the user’s intent as well as the parameters that complete the request. In the above examples, the bot understands that the intent is to create a meeting. The parameters are the date (“tomorrow”), the time (“10 am“), and a meeting participant to invite (“Bob“). If there are any required parameters missing from the command, the bot will follow up with the user by requesting that information: “What is the subject for this meeting?”.

 This interaction is fundamentally the same as filling out a form that, upon validation, alerts you that you missed a required field. In fact, the code that consumes the structured data from the bot is processing your meeting request in exactly the same way. 

It’s a big deal

It may not seem to be very earth-shattering at first glance, but bots are quite monumental in the evolution of human-computer interaction (HCI). Think about it–bots represent a total inversion of control wherein we, the users, command the computer in a way that’s natural for us rather than needing to conform to a series of steps that the software dictates. This can save untold amounts of time and frustration by not having to learn the detailed workflows of a given application or website and instead get right to what you need by simply “talking” to the program.

Enterprise bots

Bots have become pretty common in our personal lives. We use them for anything from scheduling doctor’s appointments, shopping for the latest fashion styles, playing online games, sending money to friends, and so forth. But bots hold a tremendous value proposition for the enterprise as well which is why heavy-hitters like Microsoft and Google’s GSuite are becoming major players in the space.

People often associate bots with customer service when thinking about them within the enterprise context. While it’s true that bots can be tremendously helpful in directing your customers to the resources they need without incurring the cost of human assistants, there is tremendous value to be had in regular enterprise operations as well. For example, an IT department can utilize bots to provision new user accounts, automate DevOps tasks, and request security scan reports. Executives can use bots to request sales reports and financial forecasts. Field staff can use bots to conduct inspections, request supplies and materials, update stock levels, and report progress.

Implementing a custom bot specifically for your enterprise will make your team more efficient, increase data accuracy, and refocus your human resources on higher-value work. Bots get “smarter” over time and as they do, more obstacles are removed between us users and the outcomes we seek. As you use any application today, think about the steps you take to get the outcome you need and ask yourself whether a bot could have improved the process by allowing you to get straight to what you needed with a single command stated in your own way.

Bots and your customers

Regardless of whether you are in healthcare, retail, travel, hospitality, or any other industry you can’t afford to ignore the bot concept. You have to “meet the customer where they are” by ensuring that your applications work in a way similar to what they have become accustomed to in their personal lives. Whether the medium is a messenger app, SMS, or your own application interface, you need to provide your customer with a way to simply “tell” the application what they need.

Facebook CEO Mark Zuckerberg agrees with this notion. Facebook is investing heavily into bot integration for their Messenger product. Says Zuckerberg, “You should just be able to message a business the same way that you message a friend, you should get a quick response and it shouldn’t take your full attention like phone calling and you shouldn’t install a new app”.

The time is now

 Whether your enterprise is prepared or not, bots have arrived and are being further interwoven into our cultural fabric each day. It is critical that you act now to implement bots of your own before you lose customers to a competitor who offers a better experience or employees to a workplace that allows them to do their job with less frustration. At Polyrific, we have a special affinity for bots and machine learning in general and we have the experience necessary to successfully implement a family of bots throughout your enterprise’s application ecosystem. 

Please contact us today if you are ready to join the bot revolution and take your enterprise operations and sales to new heights!

You probably already know that machine learning is an incredibly powerful technology that has the ability to solve difficult problems in a surprisingly effective manner.  What you may not have realized, however, is that since machine learning algorithmically builds its “gray matter” by learning from previous patterns, trends, and data models, we are at present witnessing only the very early stages of what machine learning can do for us.

Recently the science behind machine learning hit a significant milestone in fields that hadn’t really moved the needle for some time like speech recognition and image understanding. With the recent proliferation of sufficiently capable computing hardware, we witnessing a BIG BANG in machine learning technology that represents a major step forward in how computers can learn and perform.

For several years now, the use of machine learning has been used as a form of automation for low-value tasks that are easy to do but time-consuming when carried out by human hands. As we move into the near future, expect to see an explosion of applied machine learning as the necessary computing power and software implementation proliferate around you but it won’t all be easy; machine learning algorithms tend to have errors, and it is very interesting to know how we humans-in-the-loop in “coach” of those errors out of the result sets through training and deep-instruction in neural networks.

With that said, machine learning will have a great impact on all areas of business. One of the important things for enterprises to bear in mind is that they need to look beyond the AI hype for practical ways to incorporate machine learning into their operations. Expect too much too fast and we will find ourselves in another “AI Winter”: a season we have witnessed before during which confidence in machine learning plummets and investment stops. Machine learning algorithms should be regarded as a child in need of time and instruction to become truly effective. Goldcorp – a mining company that uses immense vehicles to haul tailings and other debris away from mining sites – is taking this step-by-step approach with great results by iterating a machine learning algorithm over time that now predicts with over 90 % accuracy, when will their machines need maintenance. Since a vehicle breakdown can cost Goldcorp over $2 million per day, it’s hard to argue the economy of this kind of applied machine learning; however, had Goldcorp expected for machine learning to first be able to make all of their monster vehicles self-driving, it is very possible that the program would have failed and the more simple, but extremely useful, algorithms would have never been implemented.

Short Term Predictions

More enterprises will begin their machine learning journey over the next 18 months than any other time in history. The smarter ones will create competitive separation for their enterprise by getting started with machine learning now while still learning from others’ mistakes. Resisting the urge to expect too much too fast will pay off handsomely – as was the case with Goldcorp – while machine learning quietly takes hold beneath a cacophony of AI marketing speak.

Employment

Some of the gloomier predictions will end on a higher note: machine learning will automate some human jobs out of the equation, but those jobs will be replaced with higher-value, more stimulating work. Retail and sales jobs are primed for machine learning implementation and automation. We will see robots in hospitals delivering medicines, materials, and meals. Self-driving cars will rule the highways in the next few years. In fact, we will see autonomous trucks, tractors, taxis, forklifts, cargo handlers, etc.

Automation of such large parts of our workforce is going to require that our governments come together in a very bipartisan way to avoid economic strive, but on the positive side, the world will see a tidal wave of creativity and innovation like never before due to the freeing of creative thought afforded by machine learning-based automation.

Culture Shift

Machine Learning will become so powerful in the future that it will shape culture by driving us to make better decisions and providing us a more profound vision for the pursuit of happiness and showing you the outcomes, explanations, or evidence that you might be missing in topics both big and small. And it will not only show you those missing elements but will also support you in weighing and making sense of them.

Machine learning will also bring about revolutionary personalization in the services and products based on your tastes, historical choices, location, even your DNA. This of course changes the way products are made, consumed, and marketed.

In conclusion, machine learning is changing everything quietly at the moment with the volume increasing dramatically over the next two years. Ignoring the technology is not an option, but it is important to measure your expectations and have a long game for machine learning in order to reap the highest rewards. 

It’s impossible to predict exactly where this phenomenon will lead us but in the words of Peter Thiel, 

“Not being able to get the future exactly right doesn’t mean you don’t have to think about it”. 

We are here to help you and think about your future and how machine learning can become a part of it as soon as possible. Please contact us to get started.