5 AI Misconceptions, Debunked

AI Misconceptions, Debunked

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Whether or not you realize it, artificial intelligence has become a ubiquitous part of our everyday lives. We use it to schedule appointments, send emails and protect our bank accounts from hackers. It fights fake news on social media, introduces us to products we’re likely to enjoy and even parks our cars.

And yet, many people still think of AI as an enigma, a far-off concept rather than a practical tool pretty much all of us can benefit from. If you’re in a line of business where you serve customers, however, this is the wrong viewpoint. 

If you are considering using AI for IVR, sentiment analysis, or intelligent call distribution; To help you fully leverage AI’s capabilities in your organization, we’re clearing up five of the biggest misconceptions about it that we frequently run into.

Myth #1: AI is only relevant to high-tech industries

Remember when some people thought the internet was a passing fad only relevant to techies? Today, there’s not a business under the sun that doesn’t benefit from being searchable on Google. 

It’s a similar scenario with artificial intelligence. While the tech sector is an obvious testing ground to push the boundaries of AI, there’s not an industry that’s removed from its impact, whether it’s happening now or is on the near horizon. 

AI has implications for all fields, from construction, where it helps builders save money by better planning projects, to the beer industry, where it’s being used to predict which tastes consumers will like most. In customer service, AI is transforming customer interactions and helping agents do their jobs better. 

Those who lag in adopting AI because they think it’s “only for the tech field” will be behind the curve. 

Myth #2: AI will replace humans

For some, the mere mention of AI conjures up science fiction visions of a robot takeover a la Ex Machina. To be sure, there are some industries where machines are making roles once held by humans obsolete. 

But technology researcher Kate Darling has the right idea in comparing robots to animals; we’ve been working alongside creatures like horses and dogs for centuries without fearing them or feeling the need to compete with them. In fact, they take some of the most tedious labor off our plates. AI works in much the same way.

AI’s greatest power lies in complementing, rather than replacing, our uniquely human skills. Its ability to take over manual, repetitive jobs that most humans don’t find desirable in the first place can increase efficiency, boost accuracy and reduce costs.

Myth #3: Implementation is complex and expensive

While tech giants like Google, Facebook and Amazon are spending big bucks to develop bespoke AI applications like smart personal assistants, the vast majority of businesses can benefit from much simpler AI investments. One example is a cloud-based contact center platform with AI capabilities. 

Because it’s based in the cloud, such a system doesn’t require heavy lifting from your internal IT team to troubleshoot and maintain. Once the initial setup is complete, updates are painless and can be done without a major overhaul to your infrastructure.

Myth #4: Intelligent machines can think for themselves

An end-stage AI product might give the impression that it thinks for itself, analyzing inputs, making decisions and creating dynamic outputs. However, it’s humans that construct the framework for AI-based decision making, prepare the data for input, set parameters for how the data is used, and create new data that’s continuously used to improve the system. 

AI may have the human brain beat in its ability to gather and compute data, but it lacks the context of the human experience that drives natural intelligence. From our colloquialisms (“catch you on the flip side!”) to our evolutionary learnings (don’t wander into a lion’s den), there are many aspects of human thought that AI hasn’t yet mastered.

This isn’t to say intelligent machines that can truly think won’t ever be created. For the vast majority of today’s practical applications, though, that’s not the type of AI technology we’re dealing with. 

Myth #5: AI is perfectly objective

As we touched on in myth #4, AI technology is based on rules and data sets created by humans. All humans hold biases, both intrinsic and learned, and as such, some biases are passed on to the AI systems those humans create. 

In addition to the biases built into AI’s algorithms, bias can come from the data itself, as was the case in a New York system designed to flag possible child abuse. AI systems that pull data from social media are also more susceptible to bias. It’s important to recognize the existence of bias in AI systems so that we don’t rely on them to make objective decisions. 

When it comes to AI, knowledge is power. Pairing AI’s capabilities for analyzing data and making predictions with uniquely human skills and insights can lead to time-saving, cost-cutting solutions. The more we can combat misinformation about AI, the more we can help business leaders leverage it in ways that are both practical and profitable. 

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About LiveVox

LiveVox (Nasdaq: LVOX) is a proven cloud CCaaS platform that helps business leaders redefine customer engagement and transform their contact center’s performance. Decision-makers use LiveVox to improve customer experience, boost agent productivity, empower their managers, and enhance their system orchestration capabilities. Everything needed to deliver game-changing results can be seamlessly integrated and configured to maximize your success: Omnichannel Communications, AI, a Contact Center CRM, and Workforce Engagement Management tools.

For more than 20 years, clients of all sizes and industries have trusted LiveVox’s scalable and reliable cloud platform to power billions of omnichannel interactions every year. LiveVox is headquartered in San Francisco, with international offices in Medellin, Colombia and Bangalore, India.

To stay up to date with everything LiveVox, follow us @LiveVox, visit www.livevox.com or call one of our specialists at (844) 207-6663.

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