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Created For and Commissioned By: DELOITTE GLOBAL
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Beyond the Hype: What’s Next in Machine Learning and Augmented Reality

Deloitte Global advises to engage, not wait. These technologies “are going to be foundational to the way business is done.”

Beyond the Hype: What’s Next in Machine Learning and Augmented Reality

There’s no question that we’re living in an era of unprecedented technological upheaval. Amidst all this change are a number of intriguing questions about the future, especially when it comes to two of the most promising and most hyped technologies: machine learning and augmented reality.

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Will machine learning and other cognitive technologies be the magic bullet that transforms businesses into more intelligent, efficient, and proactive organizations? Is augmented reality ready to go beyond social media filters and improve how we live and work?

With the recent release of its annual Technology, Media and Telecommunications Predictions report, Deloitte Global aims to separate truth from fiction and delineate the reality of several of the most notable current trends. Through an in-depth look at how technologies such as machine learning (ML) and augmented reality (AR) are developing and being implemented, the Deloitte Global team is able to make concrete predictions on where these cutting-edge technologies might soon lead.

Here’s a look at their key insights.

Machine Learning

A subset of artificial intelligence, machine learning is a cognitive technology that uses data to learn and improve its own processes without the need to be programmed explicitly by a human. Put simply, it’s a machine that can teach itself when given the right data. Machine learning has the potential to automate a vast array of expensive, time consuming processes that currently hamper organizations, from data analytics to inventory tracking.

This powerful technology has a number of specific applications, but Paul Sallomi, vice chairman and global technology, media, and telecommunications industry leader for Deloitte, believes that overall machine learning’s biggest impact will be in allowing organizations to build strong, efficient digital cores.

“Everybody talks about being a digital enterprise, but what does it really mean?” Sallomi says. “In many cases, tools like machine learning are analogous to the Wizard of Oz behind the curtain that are driving digital transformations. It’s impacting everything from core finance, to supply chains, to predictive maintenance on machinery, inventory replenishment and even customer support in call centers as organizations become truly digital enterprises. All of this can lead to greater efficiency and better decision-making.”

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But for all its potential, and all the hype surrounding it, machine learning technology is still a long way from universal adoption. According to the Deloitte report, “Most enterprises using ML have only a handful of deployments and pilots under way,” even considering the “aggressive forecasts for investment in [machine learning.]”

That conservative approach is changing, however. Advances in the technologies that underpin machine learning—such as improved data training methods, specialized chips, and smaller, more affordable hardware—will make deployment faster and easier for companies of all sizes, and more accessible to smaller and medium-sized businesses. In 2018, the number of ML deployments and pilots across enterprises of all sizes is projected to double compared to the previous calendar year, and Deloitte expects it to double again by 2020. By 2021, spending on ML is projected to reach $57.6 billion, nearly five times what it was last year.

For those looking to take the leap and explore ML technology for the first time, Deloitte suggests starting with data-science automation. It also suggests keeping an eye out for new techniques such as data synthesis and transfer learning that use less data and therefore have lower barriers to entry for organizations just getting their bearings with the technology.

Augmented Reality

Chances are, you’ve already been using AR, perhaps without even knowing it. Ever taken a selfie with a Snapchat filter that gives you, say, cartoon dog ears or a flower crown? That’s AR. It enables digital images to be superimposed on real ones. As futuristic as that sounds, the technology is poised to evolve and become even more pervasive in the coming months. Deloitte Global predicts that “over a billion smartphone users will create augmented reality (AR) content at least once in 2018, with three hundred million being monthly creators and tens of millions making and sharing content weekly.”

Advances in hardware and algorithms will allow the technology to shift beyond stylized representations towards realistic images as early as this year. That will have big repercussions for app and device makers, as well as entertainment, gaming, and marketing companies.

More retailers and marketers will use AR to offer personalized shopping experiences, such as showing someone exactly how a piece of clothing will look on their body, or how a makeup shade will complement their skin tone. Home improvement brands will have the ability to show how a piece of furniture or rug will look in their actual home, down to how much space it would take up and how the color looks with their existing decor.

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AR will have big implications for other industries as well as it makes its way into industrial, medical,and domestic settings. Technicians can use their smartphones to superimpose instructions on top of a piece of equipment they’re fixing. The augmented reality layer could show an arrow indicating where a part should be installed, show the tool required, and how it should be deployed. Think of the tens of millions of how-to-fix-it videos on the web; AR replaces them with this visual layer of instructions.

Another promising application is in medical training. Whereas a text book shows only a diagram of a heart, and a film only a simulation of a beating heart, AR can provide a 360-degree model of a beating heart that the user sees and explores from every angle,, simply by moving the smartphone ‘inside’ the heart, giving students a more complete and dynamic way to learn.

With all the hype surrounding AR, Deloitte Global advises organizations to take a balanced approach. “Enterprises should experiment enthusiastically but pragmatically with possible applications,” the Predictions report says. The cost of experimentation has fallen significantly due to the availability of new AR standards that reduce the technical expertise required to create AR apps.

“Aside from marketing opportunities,” the report continues, “there are also possibilities for AR to assist with sales, technical guidance, and aftermarket support. Enterprises should be careful, however, not to start to with AR as an answer and then look for solutions it could address.”

The point, Deloitte stresses, is getting started. With AR and machine learning, companies can’t afford to sit back with a wait-and-see approach. “These tools are going to be foundational to the way business is done,” says Sallomi, the Deloitte vice chairman. “And both are at a level of sophistication and maturity now that every enterprise can and should be engaging with these tools, in some way, shape, or form.

“Waiting to see how they mature, or simply not engaging is not advisable. This is a permanent shift, and it’s picking up steam.”

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This story was created for and commissioned by Deloitte.

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