You could worry about the jobs AI will obliterate or focus on the exciting new jobs it will create. The latter will take you places.

AI is transforming global job markets. From reshaping career paths to developing new markets, it is an exciting time for people who wish to learn new skills and persevere. A report from the World Economic Forum (WEF) states that AI will create 58 million new jobs by 2022. Those who wish to capitalize on this enormous opportunity need to focus on reskilling and upskilling and take a proactive approach to learning so they can land some of the most sought-after jobs in the modern AI era.

Here are the most promising jobs in the future of AI. We’ll talk about what they entail, whom they would best suit and how you can get yourself upskilled to conquer this new landscape of AI jobs.

1. AI Architect

An AI architect is one of the hottest jobs of the future. With businesses across all industries making a push for advanced artificial intelligence systems, skilled AI architects are required to pilot mission-critical solutions and develop viable, stout, and cost-effective AI plans.

Pivotal business verticals like information management, user experience, analytics, security, and infrastructure all need a robust AI architecture to produce tangible business solutions. Qualified AI architects will, therefore, be highly sought after and can easily anticipate annual salaries of over $100,000.

Becoming an AI architect with a good company requires a significant amount of education and experience. If you have an advanced degree in computer science, statistics, or applied math and have worked in a machine learning and deep learning environment, you could consider upskilling yourself for an AI architect’s role. Enroll in an online AI program that trains as well as certifies you for this job.

2. Machine Learning Engineer

Being highly sought after by businesses adopting AI and ML, machine learning engineers enjoy an annual median salary of $114,856, with the good ones drawing as much as $200,000 each year.

Every smart business needed a software engineer to develop the code and a data scientist to collect, analyze, and draw insights from a rolling sea of data. It is important that these two work in tandem to produce the best AI applications, but in reality, these two roles hardly understand each other. A machine learning engineer is required to be the bridge between these two critical, but estranged people.

The ML engineer must be fluent enough in both code and data science to ensure optimal results for the business. Thus, an ML engineer must have a background in data science, predictive models, and applied research, as well as be experienced with agile development processes and major programming languages like Java and Python.

There are various free and paid online courses that prepare you for the role of a machine learning engineer. You can actually begin with Google’s free 15-hour crash course in machine learning and advance from there. All major reputed universities offer courses in machine learning.

3. Data Scientist

Data is the new currency and data scientists are its new treasurers. These are the people who collect, analyze, and make sense of extremely large and complex datasets, drawing actionable insights on how a business should strategize.

Data scientists are hugely in demand and absolutely every business today needs one. No wonder data scientists make an average annual salary of $120,931, and the top brass makes much more than that. If you wish to upgrade from the role of a coder or software developer, becoming a data scientist is the next big step.

To become one, you need to be familiar with platforms like Hive, Hadoop, MapReduce, and Spark, as well as be adept in statistical computing languages like Perl, Python, and SQL. The good companies usually want people with a master’s or even a doctoral degree in computer science or mathematics. If you are in the ballpark territory, work at advancing your knowledge as well as experience to gain expertise in all related platforms and languages, amass experience in machine learning, and seek opportunities to exhibit strong analytical and communication skills.

4. Business Intelligence (BI) Developer

Developing robust artificial intelligence applications hinges strongly on analyzing complex data and painting a picture that shows where the business is headed. Business intelligence is what shows if the campaigns are producing positive results or where they need work. Becoming a good BI analyst requires very sharp technical and analytical skills, as well as a stronghold on modeling, designing, and maintaining complex cloud-based data platforms.

The great thing is that you can foray into the world of business intelligence with a bachelor’s degree in computer science. You must, however, hone your skills and gain significant experience in areas such as data mining, server integration, data warehouse design, SQL queries, and BI technologies among others.

Be sure to gain enough understanding of parallel computing, benchmarking, AI, and machine learning. Once again, you can take up free or paid online courses or join a local college to develop your skills. With enough passion and perseverance, you can expect to make an annual median salary of $99,809.

5. AI Ethicist

Another very crucial job that is finding relevance in the modern digital landscape is that of an AI ethicist. With the scale at which artificial intelligence is penetrating daily lives and the sheer volume of sensitive information that is being collected and exchanged, there is an urgent need to draw some ethical boundaries. Who holds the AI systems accountable? What’s the lawful penalty for an AI bot crime?

As regulations tighten and governing bodies step up, companies going full throttle on AI adoption will need to employ AI ethicists to ensure legal and moral boundaries to keep AI in check. Ethical frameworks will need to be developed, and AI ethicists will be highly paid people. Research scientists and AI professionals with advanced degrees and a proven track record can hope to become the guardians of the ethics in the AI world.

Wrapping Up

As you may have noticed, artificial intelligence, machine learning, and big data will create more jobs than they will obliterate. What you’ll need in order to capitalize on this riveting development is a strong passion to develop your skills, advance your experience, and explore new avenues for growth. Begin upskilling today to not just avoid losing your jobs to AI but to, in fact, straddle the opportunity and grow infinitely.