Below are the 7 steps we’ve pinpointed that can help you build a successful career as an artificial intelligence specialist.
We’ll dive into each of these steps more, but first, let’s cover what exactly an artificial intelligence specialist does.
An Artificial Intelligence Specialist might work in any number of tech roles and is sort of an umbrella term for numerous jobs that skillfully leverage AI to complete tasks. Exactly what those tasks depend on the needs of the organization. Advanced AI specialists might even work in a consultant capacity in which they advise many organizations on projects with a wide range of AI applications and goals.
Sub-fields of AI include machine learning, automation, computer vision, image recognition, speech recognition, deep learning, “smart” appliances, neural networks, and robotics.
AI specialists may have a combination of skills that help them excel in particular applications of AI. A data scientist with a specialization in AI might leverage their skills to develop predictive models based on large data sets, while robotics engineers can leverage AI skills to program their robots to perform complex tasks and act autonomously or semi-autonomously.
At the top of the Artificial Intelligence career path are AI research scientists who research advancements in artificial intelligence or study its current implications on society, technology, and economies. These scientists publish their findings for the tech and scientific communities.
It’s highly recommended that you pursue some post-secondary education in computer science, data science, and/or artificial intelligence in order to become an artificial intelligence expert. While it’s possible to learn some of the relevant skills on your own with online resources or books, the field is changing so rapidly with constant innovation that you’ll benefit massively by learning from an expert. Additionally, having post-secondary education on your resume signals to employers that you are trained in relevant skills before you even take a technical interview or complete a case study assignment.
As in many highly skilled fields, many employers will favor applicants that have a bachelor’s degree. However, this degree doesn’t necessarily need to be in a related field. If you have an unrelated degree and have also completed a data science or coding bootcamp you’ll still be an excellent candidate for many AI-related jobs. If you have no degree but do have all the relevant skills, you may still be an excellent candidate but you’ll just need to work a bit harder to demonstrate this to employers.
In order to become an artificial intelligence researcher or other pioneering position, it can be important to complete a Master’s or PhD program.
Below we’ll compare a few different education options you can choose from.
|Independent Learning, Free Online Courses||– Low Cost|
– Completely flexible learning schedule
|– May miss newer developments in the field|
– Lack of career services
– Lack of expert guidance
– Minimal resume boost
– No networking included
|Bootcamp||– Completed faster than degree programs|
– Semi-flexible schedule
– Often, career services
– Often, networking opportunities with employers
– Expert guidance
– Frequently updated curriculums
– Often, flexible payment methods
– Shorter application process
|– Sometimes, costly|
– Fewer opportunities to participate in research than degree programs
|Bachelor’s Degree in Relevant Subject||– Usually, career services|
– Usually, vast alumni networks
– Expert guidance
– Sometimes, scholarships & loans offered
– Often, opportunities to work on cutting edge research
|– Often, costly|
– Takes about 4 years to complete
– Curriculum may be updated less frequently
– Often, rigorous application process
– Usually, minimal flexibility
|Master’s Degree or PhD||– Usually, career services|
– Expert-level alumni networks
– Expert guidance
– Sometimes, scholarships & loans offered
– Work on research in the field
– Big resume boost
– Learn innovative, cutting edge concepts
|– Often, costly|
– Takes multiple years
– Requires a bachelor’s degree as prerequisite
– Often, rigorous application process
First things first – develop a strong understanding of what artificial intelligence is, its current capabilities, and the underlying technologies that make AI systems work. Pop culture tends to personify AI and make it look extra ‘cool’ – think shiny, human-sized robots. There’s no question that AI is cool – it can be used to accomplish amazing things! However, it doesn’t always look cool. Sometimes, AI is an algorithm that shoots out calculations. Sometimes it is a spam filter. Sometimes it’s a digital assistant like Siri and Alexa.
Do your homework and read up on artificial intelligence, machine learning, deep learning, automation, internet of things (IoT), natural language processing, AI algorithms, weak vs strong AI, facial recognition, moral implications of AI, and artificial neural networks.
Below are a few good resources to learn from:
One of the earlier steps in your AI career planning journey should be browsing the AI jobs available in your area. Even before you’re fully skilled up and ready to jump into the field professionally, it is a good idea to learn about the requirements and responsibilities of AI jobs, as well as the variety of job openings you’ll be applying for.
Read the job descriptions and take note of any elements that you don’t understand. Later, as you learn more AI skills, be sure to fill in the knowledge gaps that you identify in this initial investigation. Also, don’t be afraid to reach out to the companies posting these jobs on LinkedIn or by email. You can let them know that you are early in your AI education and ask about what they are looking for in an excellent candidate.
Before you learn all of the advanced AI and machine learning skills you’ll need to make sure you have a solid foundation in programming and data science. You can accomplish this in a few different ways depending on how much of a computer science background you already have and what stage of your career you are in. If you’re currently a student, it’s a good idea to major in computer science for a future career in AI. If you’ve already graduated from college or don’t have plans to attend, you can self-educate with online coding & data science resources and books or you can enroll in a coding or data science bootcamp (more on that below).
Though it’s semi-possible to self-educate and start a successful career in an innovative tech field like AI, most people will benefit massively in the job market by having some post-secondary education. Even if you think you can teach yourself all of the necessary skills, a structured education will expose you to experts who can share valuable insights. Additionally, having formal education on your resume is a positive indicator for recruiters and hiring managers.
Your formal education might be a university degree (in computer science or a related field), an expedited bootcamp learning experience, or some combination of the two. A master’s degree is another option, though it may be useful to try out some entry-level work in AI first to get a feel for the professional environment and learn new skills on the job.
Once you’ve developed key marketable skills, you’ll likely start off in an internship or an entry-level tech position. Don’t fret if your first position isn’t directly focused on AI technologies. Roles such as data analyst, IT helpdesk technician, machine learning intern, and ai engineering intern are much more available and easier to nab. Instead of spending years on the job market looking for your dream job, start in a role that’s attainable. You’ll likely learn new tech skills and professional soft skills on the job and can later leverage your experience to secure a job that’s more in line with your specific interests.
As you grow and develop in your career, you’ll be exposed to different applications of AI and you’ll see the field developing. Since AI has so many different applications, it’s a good idea to find an area to specialize in. This may happen naturally from the work you focus on early in your career or, if you have a specialty in mind that’s not related to your work, see if you can incorporate it into what you are working on or try to learn about it independently. Specialties you may pursue in AI include deep learning, IoT, voice recognition, chat bots, speech recognition, algorithm development, or any other area we mentioned in Step 1 above.
Since AI is an emerging technology, the field is full of innovation and AI specialists are constantly building on each others’ work to create more applications and abilities. To be successful as an artificial intelligence specialist you need to stay on top of new developments and learn new tools as they become available. This applies to those early in their careers as well as those who’ve been working in AI for decades. Everyone needs to keep learning in order to keep pace with the technology.
In order to stay relevant, you should follow tech publications like those cited in this list by Industry Wired, attend (or virtually join) conferences like those in this Top AI Conferences list, and take continuing education courses to fill in skill gaps as you progress. Many bootcamp providers provide advanced classes designed for experienced professionals that focus on developing specific skills. Sometimes, employers will pay for or subsidize professional development because it benefits them too when they’re employees are at the forefront of the field!
A concern discussed by economists, labor-market researchers, and job-hunters alike is whether artificial intelligence and automation will replace jobs previously held by humans. There is not yet a full consensus on the macro-level impact that AI will have on the labor market as a whole. However, one sure thing is that, as AI and automation become more important to the economy, the demand for AI specialists will only grow.
Underscoring the need for highly skilled AI specialists is a 2017 study by Wilson, Daugherty, and Morini‑Bianzino that found that less than half of companies are confident in the safety of their AI systems. Another 2017 study by Smith and Anderson found that only a third of companies are confident in the fairness of their AI systems. These low confidence levels indicate a need for specialized employees to fine-tune current AI systems or even develop new, better ones.
A Gallup report published by the Bureau of Labor Statistics pinpointed specific gaps in AI where specialists will be called to contribute to furthering the technology. These areas include training AI systems to perform highly intelligent tasks and to understand the complexities of human communication such as sarcasm and humor. The report also indicated a growing need for AI specialists to act as intermediaries between tech developers and businesses to explain the potential uses and impacts of AI systems in a given industry. Since the goal of AI is to require less hands-on work from employees, it is often just the initial setup and decision-making that requires the most human intervention. This is where AI specialists can be especially helpful.
The Bureau of Labor Statistics estimates that jobs for computer and information research scientists will increase by 15% between 2019 and 2029 – that’s at least triple the growth rate expected for other jobs! The metro areas with the highest concentrations of these jobs are Lexington Park, Maryland and Warner Robins, Georgia.
For AI specifically, the outlook is even better! In its 2020 Future of Jobs report, the world economic forum prospectively ranked AI & Machine Learning Specialist as the #2 most in-demand job over the next five years. (The #1 spot went to Data Scientist which – by the way – is another profession that leverages AI technology!)
As companies across sectors and the U.S. find more and more ways to leverage AI and automation to improve efficiency, the need for artificial intelligence specialists to support and develop these technologies will continue to grow. Artificial intelligence specialists can also take comfort in the knowledge that their role will not one day be replaced by automation.
As we mentioned above, artificial intelligence has a huge range of applications and its applicability is only growing as AI technology becomes more advanced. As such, AI specialists may find opportunities in many different fields. Below are just a few examples:
Industries that offer online customer service may leverage AI for chatbots that can help direct customers to the right resources before they speak with a real person.
Many developers rely on AI to catch bugs and inspect their systems. Many particular software products and apps use AI for their functions too. An AI specialist in software development could work on developing new features and improving existing ones.
Marketing agencies are constantly looking for an advantage over their competitors. Often this advantage can be found in the use of AI to optimize campaigns. An AI specialist could work with marketing agencies to develop algorithms and automate digital marketing.
As artificial intelligence becomes a more prominent part of our world, there is a growing need for AI experts in law who can help resolve legal cases involving unprecedented technology. Additionally, law first can leverage AI for internal operations such as document management and outcome predictions.
There are a couple of different applications for AI in manufacturing. It can be useful on the business side to help make predictions about output and demand. It can even be used to indicate when machinery is due for maintenance. AI can also be applied with robotics to sort materials, assemble parts, and run quality inspection.
The most advanced AI specialists can join research teams in pushing the limits of artificial intelligence and discovering new capabilities of the technology.
Artificial intelligence specialists’ salaries vary according to several different factors. Your location across the country, the industry you work in, your experience level and the specific responsibilities of your role are a few determinants. As a broad estimate, the average yearly salary for artificial intelligence specialists in the United States is $112,145 (from Glassdoor).
Though this is just an average measure, it’s notably higher (nearly twice as high!) than the U.S. average yearly salary across all jobs. Most jobs that you find in this field will tend to pay well.
Now you know what it takes to become an artificial intelligence specialist! This is a cutting edge career with huge (and growing) demand across industries. We’ve discussed a few education paths you may take to become an artificial intelligence expert. To browse bootcamp programs that are well-designed for someone with this career in mind, check out the list we’ve assembled below!