How to Spot the AI Jobs You Should Avoid in 2018

As we focus more on Data Science this month, let’s consider AI jobs.

There has been much media debate on whether or not the rise of Artificial Intelligence (AI) will take away jobs or create new ones. Pessimists & optimists have battled it out, all the way from the uniformed to the late great Prof Stephen Hawking.

So, to shed some light, on the topic of AI jobs, and considerations for those thinking of applying, I’m delighted to welcome a new guest blogger.

Bente Busch works as chief advisor, on AI and Data Intelligence, in EVRY . A leading Nordic technology company. So, she is well placed to inform us on the opportunities & pitfalls AI jobs bring. Over to Bente to inform this debate…

AI jobs are coming to a business near you


In the coming years, we will see massive recruitment within AI. Whether you are a graduate, or have some years of experience and consider a career change, these are exciting times. However, some jobs will not have proper conditions to succeed. Here are 5 warning signs.

Artificial Intelligence , or popularly called AI, is one of the significant technology hypes these days. The news is filled with physical and digital robots which are becoming tremendously advanced. You’ve probably seen, machines beating humans in complex board games or massive robots doing the somersault.

Robots and AI will replace as much as 50% of the jobs we have today within 10-20 years . This may sound gloomy, but many jobs will come into being. These involve technical programming of artificial intelligence, as well as supporting roles like sales, marketing, product development, designers, and managers. Regardless of your background, you may land a job related to AI.

However, there are some positions you should avoid. Here are some rules to spot AI jobs to avoid:

Your new boss cannot explain what AI is (the 1-minute-test)


If your future employer is unable to give a brief explanation of what you are going to work with, it usually means that they do not understand it. That will become a problem for you. They will have unrealistic expectations of the technology, and no understanding of its limitations. Your boss will never completely get what you spend your time on, every day, or why it takes time to create results.

Many companies will mature over time. In the first 6-12 months, though, your position will consist of more adult education than hands-on work with AI. Consider whether that is what you want, and check if your goals are according to this priority. If the answer is no, to either of these questions, consider leaving.

Now, you may want to give yourself the 1-minute-test.

Lacking alignment between technology and business


Companies sometimes start technology-driven initiatives because the tech itself is so cool. AI is in that category, along with IoT , VR , and Blockchain , at the time of writing. ( Check out Gartner’s Hype Curve of Emerging Technologies for a complete list .) Testing new technology is excellent, and you will have some fun experiments in your new job.

However, IT is a cost, until it is implemented and can create value. A pure technology-oriented AI-department will start out as the coolest kids on the block. But as newer tech appears on the hype curve, your unit is moved to the basement, to be forgotten.

Ask what value the company expects to gain from the AI-initiative. For example, through new or improved products and services, or more efficient internal systems and processes. Where can you generate value ?

AI jobs that have no mandate


Have you ever seen job advertisements, looking for an “ evangelist ”, or “ catalyst for innovation ”? These roles look attractive on paper, and are great fun for a while. You get to drive idea generation processes. The participants start believing that your company will provide new value to customers and users, and praise your awesomeness at every occasion.

Unfortunately, evangelists rarely have budgets, to take ideas into action. The good ideas end up far down on the priority list of those with real influence, where they stay, to die eventually. Investment budgets go to fixing problems and extinguishing fires. They may invest in developing concepts, but with a more predictable revenue than AI. Over time, this kills the motivation of any evangelist.

Regardless of the job title, you should make sure that your part of the organization has an actual budget . That is what enables ideas to become fully implemented AI-solutions.

Someone had tried AI jobs before – and failed


Most of the AI jobs out there, will be entirely new positions. Still, you may find yourself applying for a job, someone has had before, and not delivered the desired results. Now they want someone new, with better qualifications. During such an interview, you may feel very special, like the chosen one; the one who will save the day. Now, put your flattered ego aside for a minute and figure out why your predecessor failed.

Ask about what the organization has learned. Listen for reflections; around factors like technology, regulatory restrictions, culture and even management. If the blame is only on the person, and the belief that a new hire will solve everything, the chances are big that you too will be set aside in a few months.

Related: Fantastic Data Beasts and Where to Find Them, and What to Pay Them

Traditional and bureaucratic company culture


Culture is probably the most crucial premise, to succeed with innovative technology like AI. No matter how competent you are, and the support, tools, and budgets you get, I can guarantee that some things are going to fail. That is why you should find a company where there is culture, for testing and experimenting, and failure is considered learning.

AI has tight connections to technical development, which often follows agile development methodology . Still, even in tech-driven companies, other departments may be very bureaucratic and formal. This can be particularly so at C-level and boards. At the end of the day, it is the people on top, who decide the direction.

You have to work somewhere, for a short while, before you fully understand the company culture. The best way to find out, during an interview, is to ask questions regarding goals and priorities. The more rigid, top-heavy and slow, the stronger the signal that you should let this job go.

Many people dream of working in an exciting field that everyone talks about. It is in the news every day, and you feel you will have an enormous impact on your society . However, when working with young technology like AI, I can guarantee you many moments of frustration.

With these tips, I hope that organization and culture become the least of your problems. Then you can focus, your energy, on creating the products and services which will give value to us all in the future.

Wise counsel, on AI jobs and more


Many thanks to Bente, for sharing those wise warnings.

I am old enough to have seen many new technologies move through the famous Gartner hype cycle. From Data Warehouses , to Data Visualisation , Expert Systems & Object-Orientated Programming. But, all of them followed many of the patterns that Bente highlights.

Culture & leadership will determine your success in such roles, more than refinements to the technology. That’s why, on this blog, we give as much focus to Softer Skills , Leadership & Coaching .

Let’s collaborate to develop the leaders and culture that businesses need, if they are to realise the benefits of Data Science & AI jobs .