The development of AI is not limited only to job postings, but can also be seen in the new trends in how organizations are recruiting. Companies are beginning to focus their searches on candidates who are capable of working with or alongside an AI-based system.
The International Monetary Fund (IMF) reports that integration of AI has resulted in changes to the structure of work in regions with a higher level of AI adoption, particularly in terms of knowledge- based roles.
AI’s Impact On Job Demand
AI is changing job demand with the increase of cross-skilled hybrid skillsets (i.e. technical skill set combined with a domain skill set) necessary to perform jobs. As these skills or worker demands shift, professions requiring data analysis, systems and application automation, and system optimization will continue to grow steadily.
As job functions are redefined due to the transformation of traditional jobs into new forms of work that are integrated with AI, professionals are being forced to adapt to newly developed tools and work methods. In many industries, traditional job functions are evolving instead of disappearing.
Human-AI Productivity
Job functions are transforming in the manner in which employees are expected to work with AI and utilize AI systems in performing their jobs, thereby enhancing productivity and improving decision-making. Reports show that AI tools increase productivity and efficiency for workers; thus, showing evidence of the benefits of Humans working with AI systems.
Identify the Positive & Negative Impacts of Job Displacement and Job Creation
AI creates more job opportunities but has also created changes to job displacement and skills changing. Some industries, like the banking industry have more exposure to automation due to their repetitive or routine task-based nature.
The industry will also see the addition to new, more specially skilled positions coming into existence as AI creates, advances and offers new products or services. Research conducted by institutions like Goldman Sachs also indicates the use of AI to alter and change how employment is perceived, however they expect employees to remain as part of the employment cycle with possibly changing employment roles.
Workforce Transition
(This is generally seen as transitional change rather than complete termination and emphasising the need for adaptability and learning.)
The Fast Growing Technology Job Market for AI Engineers and Machine Learning Professionals
AI engineers and machine learning professionals are currently two of the most in-demand positions in the technology job market. Individuals in these roles create, develop, and improve AI systems that allow programs to work across multiple areas of the economy.
Responsibilities performed by individuals in these positions vary according to the company, as job descriptions can require the engineer to create algorithms, train models, and ensure the successful use of their designed AI systems in actual life.
Market Growth
AI Engineers have experienced a tremendous increase in demand, with estimates showing that the market for AI engineering is over 140% larger than just a few years ago. This rapid growth in demand has been influenced primarily through the growing dependence upon AI technology to automate general business functions and related fields and functions like predictive analytics.
Industry Investment
Corporations such as Google and Microsoft continue to invest heavily into our economy via hiring many different professionals who possess AI engineering skills.
Core Responsibilities
AI Engineers and ML specialists have a lot of different types of projects to work on to assist with the development and delivery of intelligent systems.
Key Responsibilities
- processing, storing, or building predictive models for large volumes of data
- continually enhancing system accuracy by performing regular testing
Data Roles in AI Ecosystem
Statistics from the labor market indicate that nearly 50% of job postings for data analysts require some knowledge or experience working with artificial intelligence (AI). This statistic indicates how closely AI and data technologies will fit together as they continue to evolve alongside other technologies in the future.
Companies like Amazon and IBM are taking advantage of their investment in data professionals to provide AI-enabled functionality over the course of business operations, ensuring that the data they provide to AI systems is as accurate and well-structured as possible to achieve the best results.
Key Data Roles
- Data Analyst – these analysts work to interpret the insights they gain from analyzing various data sets for use in making business decisions and are therefore an essential part of the data management process.
- AI Data Specialist – this role involves preparing the data that will be used to build machine learning models by applying appropriate transformations to raw data.
Significance of Data Skills in AI-related Employment
Data used to train AI models is critical to the performance and accuracy of machine learning models. For this reason, data that is not reliable cannot produce reliable outputs employing the sophisticated algorithms of AI.
Therefore, possessing data analysis skills is essential to establishing a career in the field of AI. According to IBM, organizations should prioritize governing and managing the data as a constituent part of the entire process of developing an intelligent machine.
Non-Technical AI Roles
Non-Technical AI Roles – Despite being largely regarded as a technical function within organizations, AI is creating many new non-technical roles as well, with an increasing number of companies needing professionals who can translate AI capabilities into business strategies (i.e., AI Product Manager, Business Analyst, AI Consultant).
Microsoft, among others, has begun to create these roles in order to help them bridge the gap between the development of AI technologies and their use in real-world applications.
Role Expansion
In these roles, the emphasis will be on understanding how properly utilising AI tools can enhance operations, improve customer experiences, and lead to better informed decisions. Unlike engineering/technical roles, the focus will be more on communication, planning and implementation.
Research from sources such as the World Economic Forum indicates that hybrid roles that encompass a blend of business knowledge and technology knowledge will continue to grow.
AI Governance, Ethics, and Compliance Careers
Organizations such as the European Commission are creating governance frameworks to ensure the ethical use of AI and to provide regulatory oversight for the ethical application of AI.
Responsibilities of AI governance roles
- Monitoring of distribution and fairness in AI models
- Ensuring compliance with existing data protection laws
- Development of guidelines for ethical usage of AC
AI Careers are Industry Specific (Healthcare, Finance, etc.)
In addition to the impact AI will have on all markets, it is also creating new roles that are very specific to particular industries. Other examples include major organizations, such as the Mayo Clinic, integrating AI into their systems of medical research and patient care.
Examples of Industry-Specific AI Roles
- Healthcare AI Specialists – Medical Data Analysts
- Financial AI Analyst – Risk Models
- Retail AI Strategists – Present Customer Insights
- Manufacturing AI Engineers – Automation
Remote and Freelance AI Jobs
The use of AI has changed the nature of jobs by increasing the number of available remote/freelance/gig-type jobs since many of the work activities that relate to AI such as data labelling, AI consulting, and testing can be completed from anywhere.
The amount of demand for AI jobs through platforms like Upwork and Fiverr also provides proof of how work styles have changed.
Examples of Freelance AI Jobs
- data annotation and labelling for machine learning models
- chatbot AI development and testing
- predictive analytics consulting for businesses
- AI integration into websites/applications
Skills Required for AI Careers
If you’re looking to build an AI career, you’ll need both technical and non-technical skills equally. While programmatic skills and data analysis skills are essential components to being successful at your job, adaptability, problem solving, working with others across disciplines will also tend to be more of a focus going forward.
Types of technical skills professionals will require in order to develop and build their careers in AI include:
- Computer Programming: e.g. Python and R
- Data Analysis and Visualization
- Machine Learning Concepts
- Problem Solving and Logical Thinking
Learning Platforms
For example, Coursera has many courses that combine practical elements and technical elements for future employment.
Continuous Development of Skills
Skill development continues to be extremely important given the continuous and rapid evolution of AI technology; new tools, new frameworks, and new methodologies are being developed overnight to assist professionals in developing and refining their skills in order to remain up to date with the changing job landscape.
Final Summary
As a conclusion, while the job/skill set associated with AI will be unique for each organization, significant growth opportunities will continue to exist for skilled professionals in all industries and from every background as they design the solutions of AI systems.
