Over 20 million job opportunities will be seen in the field of artificial intelligence (AI) by 2023, says a report by Analytics Insight.
In another report by IDC, nearly three-quarters of commercial enterprise applications will rely on AI in 2021.
Undoubtedly, AI is and will still be a buzz-worthy technology in the foreseeable future. As a result of the COVID-19 crisis, the trends in consumerism have drastically changed resulting in a notable change in the field of AI.
As AI engineers, establishing a career in the AI realm could be proven beneficial in 2021. More so since AI now becomes one of the key drivers of emerging technologies like the Internet of Things (IoT), robotics, and big data.
In 2021, the world is likely to experience multiple AI job opportunities in sectors like banking and fintech, healthcare, and public safety, says Gus Walker, director of product at Veritone, an A.I. tech company based in Costa Mesa, California.
While three of these sectors have made huge investments in AI and machine learning, 2021 marks to be a year where we will see how these investments will pay off.
The pandemic has caused the rise of data analytics expertise. Professionals having extensive skills in data collection and preparation are likely to get hired the most this year. While organizations struggle to get back to normal, it is evident that they will need candidates who can easily identify the relevant data and interpret it to make informed decisions. More so, talents who can maintain training data sets for a customized model generation.
In simple terms, organizations are in dire need to hire candidates with expertise in fine-tuning and training algorithms. While candidates having experience in DevOps and A.I. operationalization will be in demand.
Due to digitalization, structured and unstructured data have increased making it significant for more data to be leveraged. As a result, there will be a rapid growth of AI professionals. As Walker points out, “businesses will need someone who can maintain production deployment.”
Let us look at some of the technology job postings and the percentage at which machine learning skills were found crucial:
- Occupation – Data Scientist
Job Postings Requesting Skill(s)(%) – 68.0%
- Occupation – Data Engineer
Job Postings Requesting Skill(s)(%) -18.0%
- Occupation – Data / Data Mining Analyst
Job Postings Requesting Skill(s)(%) – 7.0%
- Occupation – Database Architect
Job Postings Requesting Skill(s)(%) – 6.0%
- Occupation – Researcher / Research Associate
Job Postings Requesting Skill(s)(%) – 5.5%
- Occupation – Network Engineer / Architect
Job Postings Requesting Skill(s)(%) – 4.4%
- Occupation – Product Manager
Job Postings Requesting Skill(s)(%) -3.9%
- Occupation – Software Developer / Engineer
Job Postings Requesting Skill(s)(%) – 3.1%
- Occupation – Computer Systems Engineer / Architect
Job Postings Requesting Skill(s)(%) – 2.6%
- Occupation – Business / Management Analyst
Job Postings Requesting Skill(s)(%) – 0.8%
The statistics are provided by Burning Glass.
Extensive skillsets – the prerequisite
According to Terry Simpson, technical evangelist at Nintex, a process management, and workflow automation company based in Bellevue, WA, the skillset of AI engineers revolving around AI and machine learning can vary between two extremes.
While on one end you might have a technical developer, who is busy developing an algorithm to execute a particular task in a repeated format while on the other extreme, you have a business analyst who can understand and identify the business needs of the company and automate it as per the requirement.
Between both extremes, you find a small group of individuals having the right balance of knowledge between a business analyst and a developer, says Terry.
Since organizations have started leveraging the power of AI and machine learning, these will be the skills that are likely to be the highest in demand.
A candidate having the right technical knowledge but lacks business acumen is likely to fail. This also applies to the candidate with knowledge in business but who lacks technical capabilities. Whereas, a candidate knowing both the business side and technical capabilities can be a sweet spot for someone looking to make their way toward the AI and machine learning space.
While AI is gaining greater dominance in the technology world, it is best recommended to start gaining skills while you still have the time. An AI engineer certification is a great way to start building skills in the field. Not only will certifications boost your credibility in the field but will further help you gain better opportunities in the AI career.
As the organization matures with time, they start seeking candidates who can offer full-time service while extending their expertise in both AI and machine learning. AI professionals who can build or deploy AI solutions whether it is a prebuilt or point solution.
Are you ready for the AI disruption?