AI & the Job Market in Recession 2024 - Impact on Next Gen Professionals

AI is a branch of computer science merging with other domains that enables machines to perform a wide variety of advanced functionalities like understanding human voice or speech, seeing and classifying items, reading or communicating verbally, predicting human behavior, make decisions on their own, etc. It enables machines to feed on old data and make decisions by analyzing them. 

AI engineers use mathematics, statistics, programming, and other disciplines, to prepare AI projects. These AI projects often leverage cloud technology and Graphics Processing Units (GPUs) for seamless execution. According to the Allied Market Research report, the global AI market will reach $1,581.70 billion by 2030 growing at a CAGR of 38%. AI is a domain in technology and IT that is seeing increased demand even in the recession.

Source: Google Trend

Machine Learning (ML) and Deep Learning (DL) are sub-domains of AI that help machines learn on their own and develop cognitive and decision-making abilities based on data. By integrating ML algorithms with data science, companies can build predictive models and analyze future requirements. In today's hyper-digital market, multiple industries use Machine Learning engineers and Deep Learning engineers and their skills to develop intelligent machines or systems in healthcare, finance, marketing, software development, robotics, Robotic Process Automation (RPA), automated industries, etc.

ML teaches machines how to learn on their own, whereas DL is a subset of machine learning that uses Artificial Neural Networks (ANN) to develop cognitive understanding and analyze patterns or human behaviors to serve humans better. According to Spherical Insight's report, the global ML market will touch $302.62 billion by 2030, reflecting a CAGR of 38.1%. Again, according to the Allied Market research report, the global DL market will reach $179.96 billion by 2030, growing at a CAGR of 39.2 %.

Over the past couple of years, it has been observed that different industries are using AI in numerous ways to carry out complex technological operations easily. Whether we talk about search engines or surgery bots, they are made possible because of AI and ML algorithms. Since these algorithms reduce the chances of false positives significantly, they work as the most effective tool in understanding and carrying out complex technological operations quite effortlessly.

That is why experts consider a job in this field recession-proof. Every industry and sector, be it Information Technology (IT) or healthcare, marketing or finance, is hiring AI and ML engineers to develop intelligent machines. Over the past 4 years, AI and ML jobs have grown by almost 75%. Even Venture Capitalists are also investing massive amounts of money on AI-based startups.

A very recent example is ChatGPT and Dall.E developed by Open AI. While ChatGPT is an AI-powered language model that uses DL techniques to generate human-like text based on input and previous training models, DALL-E is an AI-powered creative model that can generate unique and diverse images from textual descriptions. The model can yield a wide range of machine-generated photos 
from photorealistic to highly imaginative with fine-grained control over their features and styles. 

Before exploring the various AI and ML skills required to get a stable recession-proof job in 2024, let us explore some key areas where AI and ML algorithms are booming.

• Computer Vision
  It is a branch of AI where AI algorithms and ML models recognize images, videos, and other real-life objects. AI algorithms can help identify images and videos, object detection, image synthesis, etc. Companies like Meta, Viso.ai, Snapchat, Nauto, Tractable, Verkada, Airobotics, etc., hire AI engineers with skills in computer vision.
   
• Natural Language Processing (NLP)
  It is a branch of AI where the AI algorithms and ML models enable AI systems to function as the brain and mouth do in the body, to understand human speech and reply back. Text classification, sentiment analysis, language translation, speech recognition, etc., are some technical areas it uses to achieve such potential. All the virtual assistants we use are examples of NLP. Companies like Google, Apple, Microsoft, Tesla, etc, hire NLP-skilled AI engineers.
   
• Robotics
  With the help of mechanics in tandem with AI algorithms, when a machine can walk or move on its own, we consider it robotics. Intelligent drones, autonomous vehicles, service robots, industrial robots, etc., are well-known examples of robotics. Companies like Alphabet's DeepMind, Tesla, SpaceX, Apple, Microsoft, IBM, Hanson Robotics, OpenAI, etc., need such robotics engineers.
   
• Gaming and Entertainment
  AI-powered game strategy, game characters, and various use cases of gamification utilize AI algorithms. AI algorithms can also synthesize music composition and other digital art effortlessly. Anything mathematical and calculative will be possible to develop one day through AI. Numerous gaming companies and game engine providers are hiring AI engineers to develop AI logic and implementation for their games.
   
• Healthcare
  Drug discovery, medical diagnosis, treatment recommendation, etc., is another branch where AI engineers are in great demand. Numerous healthcare companies like IBM Watson Health, Microsoft Healthcare, Google Health, NVIDIA Clara, Vital A.I., Synapsica Healthcare, Enlitic, Cardinal Health, Viz.ai, Butterfly Network, Benevolent.AI, H2O.aiare, etc., are hiring AI engineers.
   
• Finance
  Identifying frauds, scams, hacking, algorithmic trading, credit scoring, etc., is possible through machine learning models and complex AI systems that run on complex cloud GPUs. Today all banks and insurance firms are hiring AI engineers to develop intelligent fraud detectors and ML-based security systems.
   
• Marketing
  Personalized marketing, customer segmentation, marketing analytics, etc., are well-known applications where AI algorithms can help detect patterns and identify trends so that business executives can make proactive decisions. Companies that hire AI engineers for developing intelligent marketing tools are Amazon, Microsoft, Salesforce, Intel, Accenture, Wipro, Infosys, Cognizant, etc.
   
• Customer Service
  Conversational AIs, chatbots, virtual assistants, voice assistants, etc., are some popular AI-based tools and services that call centers and customer service sectors leverage because of AI. Companies that hire AI engineers to develop customer service tools are Amazon, Accenture, HCL, Infosys, Knowlarity, CallHippo, Cognizant, etc.

In times of recession, certain industries may experience challenges, including those related to artificial intelligence (AI). However, AI has been growing rapidly in recent years and is expected to continue expanding in the long term. While no job can be completely recession-proof, several AI-related roles are likely to remain in demand even during economic downturns. Here are some AI jobs that tend to be resilient:

• AI Research Scientist
  AI Research Scientists focus on advancing the field of AI through research and development. They work on cutting-edge technologies and are often employed by universities, research institutions, and technology companies.
  
  The demand for AI research scientists is expected to remain strong in the coming years due to the increasing integration of AI in various industries. According to the Grand View Research report, the global artificial intelligence market size is estimated to expand at a Compound Annual Growth Rate (CAGR) of 37.3% by 2030.
  
  In terms of salary, AI research scientists are highly valued for their expertise and often receive competitive compensation. The average annual salary for AI research scientists in the US is around $160,000. To pursue a career as an AI research scientist, acquiring a strong educational background in computer science, AI, or related fields is beneficial. A Ph.D. in a relevant discipline is often preferred for research positions, although some industry roles may consider candidates with a master's degree or extensive practical experience.
  
  Continued learning and staying updated with the latest advancements in AI research are crucial for success in this field. Participating in conferences, publishing research papers, and collaborating with other researchers can help establish a strong professional network and enhance your reputation within the AI community.
  
  Careervira is a valuable platform for exploring online courses related to AI research, such as "Post Graduate Certificate in Advanced Machine Learning & AI," "Deep Learning Specialization," "Natural Language Processing," and "Reinforcement Learning," among others. These courses, offered by renowned institutions and industry experts, can provide you with the necessary foundations and advanced concepts to excel as an AI research scientist. 
  
  By continuously honing your skills, contributing to the scientific community, and staying abreast of the latest AI developments, you can position yourself for a successful and fulfilling career as an AI research scientist. 
   
• Data Scientist
  Data scientists analyze large datasets to extract valuable insights and develop predictive models. Their expertise is essential for companies across various industries, including finance, healthcare, and marketing. Top companies hire data scientists to add value to their business, and as per predictions, there will be a 36% growth in demand for data scientists by 2031.
  
  One report by Market and Market, predicts that the growth of the global data science market will touch $322.9 billion in 2026. Researchers expect this market to register a CAGR of 27.7% in the next few years. Due to this high demand, aspirants can find secure, recession-proof, lucrative career options in data science.
  
  Companies hire professional data scientists and tend to pay well. Further, certifications like Microsoft Certified Azure Data Scientist Associate Certification, Amazon AWS Big Data Certification, IBM Data Science Professional Certification, and degrees like Master's degree in Data Science, Bachelor's Degree in Computer Science, Master’s in Computer Science and a doctorate in Data Science help one to start working as a data scientist.
  
  On average, the annual salary of a data scientist with high skills is $144,327. Well-known companies like Deloitte, PwC Accounting and Professional Services, Amazon and AWS, Microsoft Technology, and many other reputed companies hire data scientists who are willing, to learn hard-core skills and have the potential to upgrade their skills and knowledge. 
   
• Machine Learning Engineer
  Machine learning engineers design and implement AI systems that can learn and improve over time. They are responsible for developing algorithms, building models, and deploying machine learning solutions in real-world applications. ML is a fast-growing and vast IT field and a recession-proof career option in 2024.
  
  Additionally, the pay is also good; ML engineers make an average salary of $136150 per year. To work in this domain, aspirants should learn ML skills and acquire top industry-grade certifications and degrees. Azure AI Engineer Associate by Microsoft, AWS Certified Machine Learning - Specialty, Machine Learning from Stanford University, etc., are the best certifications provided by top well-known institutes. Knowledge and understanding of verticals like mathematics, computer programming, and data science, are primary requirements.
  
  The global market size of ML was $15.44 billion in 2021, and research predicts a further surge to $209.91 billion by 2029. Aspirants seeking a secure job during the recession of 2024 can opt for ML as a profession with the help of exciting online courses from popular platforms like Careervira. This platform provides self-paced courses on ML like IBM Machine Learning Professional Certificate, Optimizing Machine Learning Performance, Apply Creative Machine Learning, etc. Users can also find top categories of various courses, and have accessibility to them anytime. You can explore more than 50,000 courses on Careervira to help beat the recession in 2024.
   
• Robotics Engineer
  Robotics combines AI and physical systems to create autonomous machines. Robotics engineers design, build, and program robots for various applications, such as manufacturing, healthcare, and logistics. It is predicted that the demand for robotic engineers will exceed 6.7% by 2026. As per the Allied Market research, the robotic engineering market will grow to $149,866.4 million by 2030, at a CAGR of 27.7%. Thus, it is predicted that the demand for robotics engineers will exceed the current estimations, and create 19,920 new jobs by 2029.
  
  On average, the annual salary of a robotic engineer is $83151. Also, as a skilled robotic engineer, you can earn an average additional pay of $21,747 from bonuses, profits, or commissions. Industry-grade certifications and degrees can help you get a decent job in robotics engineering. These include courses like: FANUC Certified Robot Technician, CS-STEM Network (CS2N), Bachelor in Robotics, Robotics Engineering, FANUC Certified Robot Operator, and the Certified Vision Professional-Basic, etc.
  
  Careervira is a top platform to search online courses like Modern Robotics, Course 2: Robot Kinematics, Robotics Foundation II - Robot Control, Become a Robotics Software Engineer, and many more, from world-class academies.
   
• Natural Language Processing (NLP) Engineer
  NLP engineers specialize in developing AI systems that can understand and process human language. They work on applications like speech recognition, language translation, and chatbots. NLP is the future of AI as it has numerous applications across industries, including customer service, virtual assistants, content analysis, and information retrieval.
  
  The demand for NLP engineers is on the rise, as organizations seek to leverage the power of language processing technologies to extract valuable insights from textual data and improve user experiences. According to Fortune Business Insights reports, the NLP market is expected to grow to $112.28 billion by 2030, with a Compound Annual Growth Rate (CAGR) of 24.6%.
  
  As an NLP engineer, you can expect competitive salaries. On average, the annual salary of an NLP engineer ranges from $90,000 to $150,000. Acquiring the right skills and knowledge is crucial to pursue a career as an NLP engineer. Relevant educational backgrounds include computer science, computational linguistics, or a related field. Additionally, industry-grade certifications and specialized courses can enhance your qualifications.
  
  Some popular NLP courses and certifications include Natural Language Processing Specialization, Applied Text Mining in Python, Deep Learning Specialization, Natural Language Processing nanodegree program and many more. Careervira is an excellent platform to explore online courses that focus on NLP engineering. By developing expertise in NLP engineering, you position yourself for a promising and recession-proof career in an industry with significant growth potential.

With recession-proof AI jobs, several specific skills within the AI field can be valuable during economic downturns. By acquiring these recession-proof AI skills, you can position yourself for success in a rapidly evolving job market and contribute to the development and application of AI technologies across various industries.

Here are some recession-proof AI skills:

• AIOps
  AIOps (Artificial Intelligence for IT Operations) combines AI and machine learning techniques with IT operations to enhance system monitoring, troubleshooting, and incident management. AIOps skills are valuable for maintaining efficient and reliable AI systems.
   
• Analytics and Visualization Skills
  The ability to analyze data and present insights visually is highly sought after. Proficiency in analytics tools, statistical analysis, and data visualization platforms like Tableau or Power BI allows you to communicate complex information effectively.
   
• Libraries and Frameworks
  Proficiency in popular AI libraries and frameworks like TensorFlow, PyTorch, and scikit-learn allows you to develop AI models and applications, making you an asset in AI development teams.
   
• Mathematics and Algorithms
  AI professionals need strong mathematical foundations and a deep understanding of algorithms. The math skills enable you to develop efficient models, optimize algorithms, and solve complex problems.
   
• Emotional Artificial Intelligence
  With the growing focus on user experience and personalization, skills in emotional AI, which involve understanding and analyzing human emotions, can be valuable for developing AI systems that interact with users in a more human-like manner.
   
• AI Marketing
  AI is transforming the marketing landscape by enabling personalized marketing campaigns, customer segmentation, and predictive analytics. AI marketing skills include leveraging machine learning algorithms for customer insights and marketing automation, which can help businesses optimize their marketing strategies.
   
• Command over UNIX Tools
  Proficiency in UNIX tools and command-line interfaces (CLIs) allows for efficient data processing, scripting, and automation, making you more productive and adaptable in various AI-related roles.
   
• Business Intelligence Development
  As businesses strive to make data-driven decisions, expertise in business intelligence (BI) development becomes crucial. BI professionals who can build data pipelines, design dashboards, and provide actionable insights are highly sought after.
   
• Network Management
  With the increasing reliance on cloud-based services and distributed systems, knowledge of network management becomes vital. Understanding networking protocols, security, and performance optimization ensures efficient communication between AI systems.
   
• Distributed Computer Efficiency
  Skills in distributed computing, including frameworks like Apache Hadoop and Apache Spark, enable you to process and analyze large-scale datasets across clusters of machines, ensuring scalability and performance in AI applications.

We hope this article has helped you understand the impact of ai on jobs and how equipping yourself with AI skills can help you succeed even in the midst of a recession. Based on our analysis and predictions, aspirants can confidently choose from the above recession-proof career options. Careervira is a brilliant platform to gain knowledge and guidance about professional courses. Its varied offering of online courses on various recession-proof career verticals is sure to help you navigate this season of recession.