BeEmerging Ai jobs for IT pros
What IT jobs will be hot in the age of Ai? Take a sneak peek at roles likely to be in demand
If you’re watching the impact of artificial intelligence on the IT organization, your interest probably starts with your own job. Can robots do what you do? But more importantly, you want to skate where the puck is headed. What emerging IT roles will Ai create? We talked to Ai and IT career experts to get a look at some emerging roles that will be valuable in the age of Ai.
[ Check out our related article, 12 emerging IT job titles with a bright future. ]
Alex Jaimes, head of R&D at DigitalOcean, notes that today, Ai and machine learning expertise is typically the domain of people with PhDs. “Rising demand may open the door for differing types of experts,” Jaimes says. “We’ll continue to see the scientist – PhDs in fields such as computer science and electrical engineering – with deep technical expertise and experience in [Ai and] machine learning, but we’ll also see more practitioners, [who] quickly learn how to use the technology to capitalize on the growing number of jobs, but do not necessarily have a deep understanding of how it works.”
The rise of the “practitioner” is one of many factors that will create new jobs, even as old ones disappear.
“Although Ai will lead to the automation of certain jobs, it will also create many new job opportunities, especially in IT,” says Akash Ganapathi, co-founder and CEO of Trill A.I. Ganapathi expects a growing enterprise focus on Ai and machine learning to generate new roles in areas including:
AI oversight & compliance: Ensuring that Ai programs are running as they should and not being compromised by any bugs, data errors, or incorrect data sources.
Ai management: Working on the technical implementations and operations of Ai.
Data aggregation and munging: Collecting (especially from obscure sources) and cleaning data sets for Ai use.
And that’s just a starting point. Here are some other Ai-related job titles and roles experts expect to crop up in the future.
1. Intelligence Designer
“I envision Intelligence Designers as Ai professionals in charge of strategic choices about how, when, and where develop artificial intelligence components in very large, complex IT systems,” says Alessandro Perilli, GM, Management Strategy, Red Hat.
He envisions this position as a descendant of today’s data scientist role, but with a key difference.
“In my mind, today’s data scientist has a more specialized focus, looking to turn normal applications into smart applications. And in some cases, it will be all a company needs. But eventually, as Ai becomes more pervasive across the application portfolio and more elements of the IT environment could be correlated in a meaningful way, there will be the need for somebody who has the big picture and sees all localized intelligences getting together as a single corporate brain, if you will.
“The analogy that comes to mind, of course, is the evolution of the human brain. It’s very exciting. We are in the early, early phases of artificial intelligence and we are still thinking about isolated smart applications, like neurons in charge of a single specific aspect of the brain. But the potential for these neurons to be integrated into a complex neocortex is enormous. And we’ll need an Intelligence Designer for that.”
2. Data Curator
“Although Ai will handle many of the routine IT decisions made by humans today, it is much more dependent on data that has been organized, cleansed, and tagged with semantic meaning,” says Doug Bordonaro, chief data evangelist, ThoughtSpot. “Today, analysts and data scientists share this function, but these positions are primarily responsible for producing insights and answers. As Ai increasingly takes over the insight part of the equation, we’ll see a new role of data curator rise in importance, focused specifically on preparing data for use by Ai algorithms across the organization.”
3. Data Evangelist
“Even after adopting Ai applications, businesses will need to teach their organizations about what data is available, how it can be applied, and how it should be applied.”
“AI has the promise to lower the bar for both access to data and ease of interaction, but it’s not going to be some silver bullet where all of a sudden everyone is using data to inform every decision,” Bordonaro says. “Even after adopting AI applications, businesses will need to teach their organizations about what data is available, how it can be applied, and how it should be applied.”
"That’s why internal data evangelism will become critical to the adoption and growth of Ai solutions. To bridge this gap, companies will invest in data evangelist roles, specifically focused on working across the organization to educate users about available solutions, the value of data-driven decision making, and how to change traditional workflows to take advantage of the new capability.”
4. Machine Learning Data Scientist
“While not a new title in itself, in order to leverage the full potential of machine learning in a big data environments, enterprises must hire a dedicated ML Data Scientist to implement and properly train the system, then provide data analysis to add value to the information collected,” says Todd Loeppke, lead CTO architect at Sungard Availability Services.
5. Robotics Process Analyst
“[This] is a business analyst type role where you perform process assessments and identify areas for automation using robotics platforms,” says Felix Fermin, manager, recruitment at Mondo.
6. Digital Knowledge Manager
Alexa, Siri, and Google Home are already changing how consumers discover and choose businesses.
Duane Forrester, VP of Industry Insights at Yext, points out that virtual assistants and other “intelligent” services today – think Alexa, Siri, Google Home, and so forth – are already changing how consumers discover and choose businesses. Those businesses will need to invest deeply in how they manage the information available about them in the “intelligent ecosystem.”
“The age of structured data needs professionals to provide context for maps, info cards and specific answers, and digital knowledge. Companies are increasingly appointing a Digital Knowledge Manager to be the cross-functional leader responsible for the strategy behind a company's key digital knowledge, the cornerstone of a company's success in the coming years,” Forrester says. “From ensuring online data is accurate, to coupling internal projects and extending the value of content, product and contextual investments, these DKMs will be at the forefront of guiding a company's digital focus in the future.”
7. Ai Interaction Designer
There will be a growing need for IT and design pros who can make Ai interfaces usable for mass audiences, says Mondo's Fremin. This role will “create the personality of artificial intelligence agents with the goal to make them as human-like as possible.”
8. Cognitive Copywriter
Sean MacPhedran, director of future platforms at Smith Labs, expects this to become an increasingly trendy role as more companies begin building natural language processing functions into their customer interactions. It’s a great example of a role that transcends traditional organizational silos: It’s a mix of technology, marketing, customer service, and other disciplines. Here’s how MacPhedran defines the job:
A technically minded creative writer who can:
Understand the various machine learning systems and API connectors that hang together in a particular natural language interface.
Grasp and can creatively manage the limitations of a natural language processing system in customer experience – a new dimension in UX design
Express the nuances of the brand itself in the personality and language used by the NLP AI interface.
Replaced by robots: 8 jobs that could be hit hard by the A.I. revolution
There’s no doubt that artificial intelligence (A.I.) and other cutting edge technologies are going to change the face of employment as we know it. According to one famous study, 47 percent of currently existing jobs in America are at high risk of potential automation in the coming decades.
What are some of the professions that will suffer the effects of the A.I. revolution? And is there anything people can hope to do about it? Read on to find out.
Lawyers
Why they’re screwed: Judging from the number of movies and TV shows about the profession, being a lawyer is a pretty great job: an interesting, high-earning career with bags of social status attached. However, hiring a lawyer is also expensive and a substantial portion of what lawyers do on a daily basis turns out to be a lot more routinized than some in the profession would have you believe.
While genuinely bespoke legal work still requires humans, A.I. can help perform tasks ranging from legal discovery (the pre-trial process in which lawyers decide which documents are relevant to a case) to creating contracts. They can even argue parking fines and handle divorce proceedings.
So there’s no hope? Junior lawyer jobs may be harder to come by than ever, but studying a combination of law and computer science could be extremely fulfilling. Whether it’s advising on how best to turn laws into algorithms or investigating the legal framework around new technologies like self-driving cars, there are plenty of interesting opportunities available.
Journalists
Why they’re screwed: An algorithm could never write a listicle as compelling as this one, right? Guess again! Whether it’s using bots to generate sports reports and other news articles or attempts to use A.I. for more in-depth investigative journalism, there’s plenty to suggest that journalism isn’t safe from the clutches of artificial intelligence.
Heck, combine advances in computational creativity and text generation with the sorry financial state of many media companies and the results don’t add up to anything approaching optimistic for wordsmiths.
So there’s no hope? A.I. doesn’t have to be your enemy. As it turns out, bots could be the hired researcher human journalists always dreamed of, with the ability to pull up statistics and unearth interesting patterns in data which can lead to entirely new ways of telling and presenting stories.
In the future, there’s also the possibility that A.I. automated agents could be used to help personalize human-written stories for readers, based on their knowledge, location, age, or reading level. Doing so could expose human writers’ work to even larger audiences.
Drivers
Why they’re screwed: In a chapter from their 2004 book, The New Division of Labor, MIT and Harvard economists Frank Levy and Richard Murnane argued that a computer would never be able to drive a car, due to the enormous complexity of information involved with this task.
Today, we know that is categorically false, due to the thousands of miles successfully driven by self-driving cars. Fleets of autonomous vehicles owned by companies like Uber will have an enormous impact on professional human taxi drivers, while autonomous trucks will mean the same thing for long-distance drivers.
Things don’t look too hot for driving instructors either. After all, will kids born in 2018 even need to pass a driving test?
So there’s no hope? Based on the response to Uber in some major cities like London, human cab drivers may be able to resist the threat of self-driving cars for a short time. Sad as it is to say, however, human drivers should probably think about reskilling.
Chefs
Why they’re screwed: Considering that they need cooling fans at the best of times, working in a hot kitchen sounds like a terrible idea for a computer. But A.I. is always ready to surprise us. One example of a chef robot was created using IBM’s Watson technology. Called Chef Watson, it’s able to generate entirely new recipes from scratch using an astonishing knowledge of taste chemistry and flavor pairings.
Meanwhile, robots like Miso Robotics’ burger-preparing Flippy are capable of preparing meals and serving them up at speeds that human chefs struggle to achieve. Add table delivery drones into the mix and you don’t even need human waiters to deliver the food to customers.
So there’s no hope? As with a lot of areas, humans who are ready to take advantage of the technology stand to benefit. If you’re a chef, you could conceivably use robots to churn out identical dishes to your specifications in greater quantities than you yourself could cook.
Using technologies like 3D food printing will also make possible the creation of entirely new dishes that would have been previously unimaginable.
Financial analysts
Why they’re screwed: Like being a lawyer, working in the finance sector has traditionally been a high status, high income job. However, increasingly A.I. is taking over. Computers can spot patterns and make trades faster than even the most eagle-eyed of human analysts.
With billions of dollars (or more) at stake, it’s no wonder that machine learning tools are all the rage, while some estimates suggest that around 30 percent of banking sector jobs will be lost to A.I. within the next decade.
So there’s no hope? There will be fewer jobs, but there are certainly opportunities. So-called “quants” who are able to combine knowledge of the financial sector with computer science and math are highly sought after to help develop the algorithms which increasingly drive this field.
Elsewhere, the importance of “relationship banking” to help build up customer loyalty and provide personalized service will continue to grow.
Telemarketers and customer service assistants
Why they’re screwed: Chatbots are getting way smarter, as tools like Google Home and Amazon’s Alexa show us. That doesn’t bode well for a lot of telemarketers and phone-based customer service assistants, who are often speaking according to a script.
With miserable conversion rates for direct telephone sales and fewer people willing to wait customer service assistants to become available, smart chatbots can perform a lot of these tools admirably. That’s not good for people working in this field, who have already been hit by the outsourcing of many of these jobs to people in other countries like India.
So there’s no hope? Not necessarily. One A.I. company, Mattersight, uses voice recognition technology to figure out the personality type of customer service line callers and patch them through to humans with a similar personality type. Doing so can dramatically shorten the length of calls, while increasing the problem resolution rate.
Meanwhile, companies like Twitter employ human “judges” who can help machines make sense of the information they’re being shown — such as figuring out the context of a specific trending topic. In other words, these jobs may still exist, but you could be answering an A.I.’s questions instead of a human’s.
Medics
Why they’re screwed: Whether it’s algorithms which can make diagnoses about disease, computers being used to make recommendations about the best cancer treatment, A.I. pharmacists, wearable devices that can help treat physical disorders, or even robots carrying out surgery, there’s no doubt that cutting edge technology will have a big impact on a range of medical professions.
Due to their brilliance at capturing and analyzing data, artificial intelligence promises to be a major disruptor in this space, giving everyone an A.I. physician in their pocket.
So there’s no hope? A lot depends on the area of medicine you work in. For the most part, though, humans will still be in the loop. Diagnoses and even surgery could one day be managed by machine, but in the immediate future technology will augment human physicians and healthcare workers, not replace them.
Construction workers or other manual labor jobs
Why they’re screwed: Whether it’s bricklaying on construction sites, working in warehouses, or picking fruit and vegetables on a farm, there’s no doubt that a large number of manual labor jobs that once required humans can now be carried out by robots.
The advantage of these robots is their ability to work nonstop without getting tired. That’s something that’s not possibly in any line of work, but especially not in physically taxing manual labor roles.
So there’s no hope? All of the jobs we’ve mentioned are going to get more automated, but right now humans still have an advantage over robots when it comes to dexterity. For example, Amazon’s warehouses use robots developed by Kiva Systems to move around racks of shelves and bring them to stationary human workers who then pick the required items off the shelf.
Similarly, bricklaying robots can lay bricks, but require humans to do the grouting. This balance will shift as robots get more dexterous, but for now many humans will find themselves working alongside robots rather than being flat-out replaced by them.
