The Skills You’ll Need For the World of AI

Artificial intelligence (AI) is here – but that doesn’t mean self-aware robots. What it means is that computers can process communication, analyze data and even learn like never before. Here’s a run-through of what that could mean for people on all sides of the enterprise tech equation.

With each passing year, people are interacting more with artificial intelligence (AI) – and probably don’t even realize it. For those who haven’t kept up on this specific evolution of enterprise technology, that might sound unlikely or even scary.  After all, the term AI conjures images of the autonomous, self-aware robots that have long been a science fiction staple. And some well-established futurists occasionally grabbing headlines with warnings about the dangers of that kind of AI getting too smart probably adds to the confusion. But the AI that’s here now isn’t that kind of AI.  

The kind of AI we’ve seen appear on the enterprise computing landscape is a type that can learn and think insofar as it can process massive amounts of data and automate laborious tasks. And as it grows more popular and more effective, those building and selling tech solutions are going to want to have a solid understanding of what it’s going to take to effectively implement and manage AI. 

So if while you were reading the CompTIA IT Industry Outlook for 2018 you noticed mention of the need for new skill sets to handle AI, don’t worry – it doesn’t mean you’ll need to hire a dedicated robot wrangler.

But let’s explore what it does mean, so you can keep an eye toward the future when it comes to selling, implementing, leveraging or managing this important up-and-coming technology.

Developer Skills … And More

One of the biggest recent AI innovations is that public-facing chatbots have quietly begun to emerge, changing the way the public interacts with a wide array of businesses. 

Whether you’re looking for information about your bill from a utility company, asking a retailer about a refund or seeking answers about how to use a feature on a new enterprise app, you’ve probably started to expect the option of communicating with customer service through opening through a chat window. And some of these lower-tier customer service interactions, which once required a phone call, are being handled behind the scenes by chatbots. Natural language processing allows bots to interpret and respond to simple conversational queues rather than direct commands. And with machine learning, the bots are getting better at understanding and reacting to simple requests.

Tier-one customer service isn’t the only area where chatbots are popping up. Some restaurants have implemented chatbots to handle ordering via text or Facebook Messenger. As the technology matures, retailers are piloting features like text message-based personal shoppers.  And you can’t really talk about AI without mentioning one of the biggest trends in commerce – voice-assistants like Amazon Alexa and Google Home, which rely on AI, machine learning and natural language processing to carry out a range of tasks.

So, if you’re providing services to a company that wants to roll out or experiment with such an initiative, having tech staff that understands the nuts-and-bolts of how these work – how to create them and how to maintain them – is an obvious first step. 

But, as with any technological innovation, there very well may arise jobs around AIs that aren’t technical in the developer level. Double-checking, correcting and fulfilling AI-generated requests could be a growth area. This could mean different things depending on the area – in terms of customer service, it could mean a bigger, more highly-skilled Tier 2 team managing what an AI-automated Tier 1 support chatbot can’t handle.

Data Analysis Skills

Big data is becoming a fundamental driving force behind the moves businesses make, and AI with deep learning capabilities is foundational to making them. The right AI can recognize patterns too obscure for an individual to pick up – in a repository of data too massive for a human to pour through in a reasonable time frame. 

But AI doesn’t do all the work – not by a long shot. Skilled data analysts, who understand how to read and make decisions based on AI-gathered data, are crucial to getting value out of an AI-based system. The more businesses leverage AIs to get insights, the more they’ll need people to interpret those insights and guide the business in taking the right action based on them.

Communication Skills

With any technology it’s easy for businesses to get caught up in buzzwords. Rather than determining a need and implementing the solution to meet it, businesses run the risk of implementing something that doesn’t really serve a purpose, just because it purports to take advantage of the latest technology on the market. This is certainly true with an emerging tech trend like AI. So in order for business to find the right ways to apply AI, machine learning, natural language processing and other related technologies, everybody needs to be speaking the same language. 

That’s why one of the most important skills arising around AI as it reaches maturity is the ability for those who are working on it to explain clearly what it is, what it does and why it is important to other business units – the ones that can make use of and, in some cases, finance it.

Does this mean that there will someday need to be a chief AI officer in the C-suite of every business, coordinating all the AI-involved initiatives? Some experts have begun to theorize about the need for such a job role. Many others see AI as technology that will remain one tool in a tech department’s toolbox, without a need for its own specific C-suite member to set the standards. But either way, communication skills around AI and its significance will be critical for those implementing, using and selling the technology.

Click here to read more about how AI technology is affecting the IT ecosystem in the CompTIA IT Industry Outlook 2018.

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