Artificial intelligence isn’t just making machines smarter, it’s also enhancing human intelligence, performance, and productivity – especially in the workplace.
Research by Markets and Markets anticipates that AI will become a $5.05 billion market by 2020. This is linked to increases in applications across a range of industries, including finance, tech, healthcare, retail, and service.
The impact of machine learning can be seen across a range of industries and job descriptions. From sales teams, marketers, and customer service agents to doctors, dog-walkers, and electricians, machine learning will make all of us better, faster, stronger members of the workforce.
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<h3>The Rise of Superhumans: How AI Is Making Us Smarter, Faster, and Better at Work</h3><a href="https://thinkrelay.com/blog/how-ai-is-making-us-smarter-faster-and-better-at-work/"><img src="https://thinkrelay.com/wp-content/uploads/Rise-of-Superhumans_Infographic_Final.png" alt="How AI makes us better at work" width="1625px" /></a><br><p><a href="https://thinkrelay.com">Relay shows how AI helps us at work</a></p>
With all the hype around self-driving vehicles, it’s hard not to dream about upgrading your commute with an artificially intelligent car. Not only will an AI-powered commute allow us to arrive at work refreshed instead of frazzled, but self-driving vehicles will also speed up your commute by reducing accidents by up to 90%.
But did you realize that much of today’s workforce is already using AI to simplify and shorten their commute?
Ride-sharing apps like Uber and Lyft use machine learning algorithms to match passengers with drivers and minimize detours when dropping off multiple commuters. Advancements in AI will soon make ride-sharing even easier and more efficient – with the potential to reduce traffic on the roads by up to 75%.
A pilot study also found that smart traffic lights can shorten time spent waiting at an intersection by 40% and reduce overall travel time by 26%.
So, whether you drive yourself to work, catch a Lyft, or hop into a self-driving vehicle, AI will shorten and simplify your trip.
AI can help us cut down the cost of maintaining a physical office. For example, an AI startup called DeepMind – which was bought out by Google in 2014 – used AI to slash energy usage by 40% across all of its data centers.
By using insights “learned” from the data centers to develop a prediction model for each building’s energy usage, DeepMind was able to maximize efficiency. This type of machine learning could also be used to reduce energy costs for office buildings, manufacturing facilities, and other large-scale operations.
Artificial intelligence is also proving useful in the medical field, including impacting how doctors diagnose certain conditions.
The FDA recently approved the first-ever AI-powered “diagnosis by software” that doesn’t require a doctor to interpret the results. The device uses a machine learning algorithm to detect diabetic retinopathy by analyzing images of a patient’s eye. Once the images are taken by a retinal camera and uploaded to the server, the AI automatically provides a positive or negative diagnosis.
Although this is the first example of a smart diagnostic tool that works independently of a human doctor, there are several other applications of AI within modern medicine that empower doctors to do their job better than ever. This includes AI algorithms that doctors can to detect stroke and diagnose Sepsis early on.
Research suggests that AI will eventually handle 80% of repetitive administrative tasks, allowing their human counterparts to focus on more complex tasks. Not only would this free up our brain power to solve more interesting problems with creative solutions, but the presence of machine learning will boost overall productivity.
One modern example is Clara, scheduling software that uses a mix of AI and human input to help schedule meetings and manage your calendar. Users can simply cc: Clara on an email with a meeting request and the software will take it from there.
Another way AI improves human efficiency is by making it easy to quickly reply to emails. Google’s smart reply feature for Inbox is one example that uses machine learning to automatically generate and suggest customized responses to emails. The user can choose from three messages for a quick, effortless response to any email.
The more you use AI-powered communication tools, the better they get at anticipating what you’d like to say. It can learn your communication preferences to determine which responses are most appropriate and natural-sounding, based on your previous selections and writing style.
This type of technology plays a role in day-to-day office communication and can also simplify aspects of customer service jobs. As AI gets even smarter, we can expect to see increasingly intelligent responses and automated reply options.
Machine learning allows customer support agents to focus on urgent cases while always providing fast, high-quality replies to every ticket. For example, AI can be used to auto-fill case data and provide suggested responses to a range of customer questions and concerns.
So, instead of reading through a customer’s chat history to gain a complete understanding of the situation, human agents can rely on AI to provide them with the most relevant data. This saves time, improves accuracy and efficiency, and means every customer gets the answers they need faster.
Not to mention the role AI plays in self-service support solutions. For instance, chatbots can deliver reliable responses to routine questions and AI can step in to decide when a conversation should be passed along to a human agent.
Artificial intelligence helps business owners, marketers, and sales teams develop a better understanding of their customers.
Online shopping platforms like Shop.com use machine learning to define customer segments and analyze each type of buyer journey. This allows businesses to deliver personalized promotions and offers based on browsing habits, purchase history, and social media engagement with the brand.
AI can match the best offers available to specific consumers, so marketers can automatically send out relevant deals to the right customers – which is great for the shoppers as well as the business.
In the next few years, not only will more sales reps and marketers use AI to better target customers and prospects, but machine learning will help predict consumer trends and behaviors before they happen.
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