Hiring Trends in Artificial Intelligence
New reports shed light on the skills and education you need for AI work.
- By Brian J. Dooley
- October 31, 2017
As interest in artificial intelligence (AI) grows, companies are struggling to hire AI talent. The required skills are changing as the discipline matures (discussed previously in The AI Toolbox: New Skills for a New Generation). Requirements are beginning to broaden from basic programming areas toward those skills required to fit AI into the business environment, integrate it with other tools, and prepare it for a more active role in complex business processes and in solving specific business problems.
Meanwhile, the need for AI skills is growing increasingly acute. Filling these roles requires a better understanding of this developing skills market on the part of both employers and job applicants.
Top AI Technologies
Demand for specific skills tends to respond to the top and most critical emerging technologies. In the AI space, the top trends reported by Forrester Research for the first quarter of 2017, as noted in Gil Press' Forbes blog (Top 10 Hot Artificial Intelligence (AI) Technologies), are:
- Natural language generation
- Speech recognition
- Virtual agents
- Machine learning platforms
- AI-optimized hardware
- Decision management
- Deep learning platforms
- Robotic process automation
- Text analytics and natural language processing
Hiring is likely to be concentrated in areas related to these technologies. Each of these requires different talents and different abilities; some of these skills are valuable in a narrow range of industries, and some are applicable to a larger domain. Each solves a different type of business problem, and different domain knowledge will be required.
The skills required for AI practitioners are highly variable in level of required understanding and performance. A report from career and hiring data firm Paysa provides additional insight into hiring patterns. The report found that 35 percent of AI positions require a Ph.D. and 26 percent require a master's degree.
The reason for the Ph.D. requirement is that AI skills, particularly in deep learning and machine learning, are of relatively recent prominence and are developing swiftly. Expertise gained from studying at the Ph.D. level and participating in academic projects provides advanced talent that can hit the ground running. These higher academic requirements are expected to increase as machine learning and AI become more prevalent and as skills and experience become more common.
Skill sets in demand must be inferred from employment advertisements. A definitive survey is impeded by the early stage of hiring and by the broad scope of AI definitions. Course developer Udacity studied thousands of job postings in researching AI course demand. Machine learning engineer was the most popular job title across descriptions posted on sites such as Stack, Overflow, Indeed, and Hacker News. Within this job category, the top specific skill areas were natural language processing, computer vision, and prediction/insights/recommendations.
Hiring today includes long-term employees in the traditional sense as well as those brought in on a contract or freelance basis. The freelance platform Upwork released a second quarter 2017 index ranking the fastest-growing skills for freelancers across all professional areas. Artificial intelligence and related fields were prominent, with natural language processing the second fastest-growing skill, neural networks fifth, and machine learning sixteenth. The top and eighth skills were the related virtual reality and image processing, respectively. Hiring managers use freelancers to access skills they don't have in-house, and these skills have been growing at a rate of more than 150 percent per year.
Currently, the skills most in demand are mainly in more established areas, as expected. These include natural language processing, image processing, general machine learning, and prediction. Engineers focused on machine learning are particularly in demand. What is certain is that the world of AI employment will broaden and develop new roles as AI becomes ubiquitous. The skills shortage will continue to grow as more large companies attempt to acquire and train this talent.
Continuing Growth for AI Skills Demand
According to the Paysa report, U.S. employers will spend more than $650 million on annual salaries for 10,000 jobs in AI in 2017. Growth has been spectacular. A Narrative Science survey found that 38 percent of enterprises were already using AI in 2016 and this figure was likely to rise to 62 percent by 2018; Forrester Research predicts a greater than 300 percent increase in investment in AI during 2017 (Forrester Q2 2016 Global State Of Artificial Intelligence Online Survey).
Increasingly specific job requirements are matched to a growing range of courses and curricula aimed at developing AI specialties. In many cases these courses provide knowledge without the project experience demanded by companies. At this early stage, practitioners need to find ways to demonstrate their expertise in order to obtain cutting-edge jobs. Competition will energize the training markets to develop curricula focused on a broader range of problems and answering the need for next generation skills that focus on AI integration and solutions to specific business problems.
Brian J. Dooley is an author, analyst, and journalist with more than 30 years' experience in analyzing and writing about trends in IT. He has written six books, numerous user manuals, hundreds of reports, and more than 1,000 magazine features. You can contact the author at email@example.com.