WEF Says 58 Million Net New Jobs Will Be Created by AI by 2022: What Does It Take to Build a Career in the Emerging AI Landscape?
It’s a widely held belief that advances in AI that result in the deployment of more AI systems in commercial and enterprise applications will result in widespread lost jobs for workers. A recent Brookings Institute study determined that 36 million American workers are highly exposed to employment disruption due to automation.
But a more in depth analysis reveals that AI has the potential to be a potent engine for job creation: the World Economic Forum predicts that AI and automation could create as many new technology- and AI-enabled jobs as it destroys in production, transportation, food service and other highly exposed industries.
Understanding how career opportunities are evolving is the key to successfully pivoting in a changing employment market. Here’s a closer look at how the next generation of workers can prepare themselves to be relevant and coveted in a workforce shaped by the emerging AI landscape.
Looking at AI Careers
First you need to understand potential targets you’re aiming for: what are the actual jobs needed by the AI sector itself? Three of the most relevant AI jobs for the near term include:
AI engineers conceptualize, build, deploy and maintain AI models and infrastructure. They are key personnel within an AI-focused hierarchy, responsible for coordinating operations with data scientists, converting machine learning models into APIs, and using AI to empower enterprise performance and advance goals.
- Degree: Computer Science, Robotics, Engineering, Physics
- Skills: Data science, mathematics, computer science, programming
Machine learning engineers work directly with data, systems and processes, to develop the algorithms that enable AI systems to learn within both supervised and unsupervised frameworks. They are critical to maintaining the performance framework within an AI department, including hands-on training and retraining of AI systems.
- Degree: Computer Science, Mathematics
- Skills: Data science, statistics, mathematics, probability, computer science, programming
Data scientists perform intensive collection, organization and analysis of data to meet individual project goals. They are expected to research and develop learning models for data analysis, collaborate with engineers and implement new methodologies as needed. Their work provides the data-centric backbone of AI research and development.
- Degree: Computer Science, Statistics, Mathematics
- Skills: Programming, statistics, mathematics, analysis, pattern recognition and modeling
Transitioning from Technical Focus to Business Focus
As the technology side of AI matures, with workers adding experience and technical skills diversification to their portfolios, an employment shift is gradually taking place. Enterprises are looking for “business leaders capable of interpreting AI results, making decisions, and taking appropriate actions,” according to management consultancy Deloitte.
Their survey demonstrates how enterprise needs evolve as automation increases and AI integration accelerates. Industry maturation inevitably leads to an increased focus on management and executive talent capable of providing business leadership that can best exploit new technologies, processes and solutions. Topping the career need list are “AI Translators,” including:
- Business leaders who can re-frame AI business problems/needs into solution requirements
- Change management/transformation experts who can implement and integrate AI-led procedural change strategies
- User-experience designers able to reduce complexity and improve usability of AI systems
- Subject-matter experts able to re-contextualize domain expertise into AI performance
Becoming an AI expert is an area ripe for career growth well into the near future. Understand trending technologies, connect yourself with relevant knowledge, and align your goals with enterprise needs, and you’ll be well positioned to jump start your career in the thriving field of artificial intelligence for business.