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Moving Ahead of STEM: Adopting Skill Beyond AI

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The world will never be able to function without technology, not anymore.

Science, technology, engineering, and math (STEM) skills are cool and it is important. Without a doubt, STEM skills have now formed among the fastest-growing job categories. Saying no is not an option anymore. The issue is at hand and everyone needs to take it seriously. Employers are facing a crucial global skills crisis that has a probability of holding back the economic promises of intelligent technologies.


Beyond today’s talent shortages, where do we stand?

A study by the World Economic Forum estimated that the data-related jobs will accelerate within the next four years, along with technologies like machine learning and AI.

What’s more interesting?

  • Estimation of 75 million jobs to be destroyed.
  • Creation of 133 million newer jobs.
  • Shifts in the global job market results in 58 million net new jobs.

Other job-related categories will include data analyst, data scientist, AI specialist, machine learning specialist, software developer, application developer, application analyst, and big data specialist – though it’s likely these professionals will own a different name in the foreseeable future.

Will STEM skills bridge the talent gap?

I doubt it.

Emphasizing STEM skills is not enough, although there needs to be a greater emphasis that needs to be taken care of. Most people try and interact with each other in the context of coming with a solution for their workplace challenge.

“Creating a workforce ready for the challenges of an AI and digital future requires teaching people to think differently, says Malcom, head of education and human resources programs of the American Association for the Advancement of Science.”

Education needs to be reimagined and reformed.

Bridging the AI skill gap is merely not about having the capabilities of attracting top talents. But to have an agile, cross-organizational approach to AI that can upskill stakeholders to be in-line with business strategies.

When an AI reaches the organizational maturity, new governance structure and development of AI talent should be embedded at all levels in an organization.

It is believed that the success of AI in a workforce compiles of a three-pronged approached: -

  • Upskilling
  • Diversity
  • Rethinking

This is what Genpact believes, the best way to shape the future workforce is to first focus on fundamental literacies and get more AI-focused training on the job and not on advanced degrees. Employers can then put these concerns to rest while optimizing their existing AI workforce and AI initiatives.

This can simply be done by investing in employee training for most AI effective skills.

Beyond employee training: AI certifications

the idea is to talk more about learning rather than education. To some, the solution is much simpler. Train more software engineers, raise the numbers of data analysts, data designers, and AI professionals like AI specialists.

But it is not as simple as it looks for other employers.

Based on a report, “How AI Boosts Industry Profits and Innovations,” it is estimated that AI is estimated to grow its economic growth at an average of 1.7% across 16 industries by 2035. The report proceeds further by stating that AI technology will increase labor productivity by 40% and even higher.

If you’re seeking to penetrate the current AI industry, then perhaps taking an AI certification is a call you need to take. Organizations are adopting AI and sooner than you would know, certified AI professionals will be in demand.

Having said that, the demand for trained AI professionals and certified AI professionals is increasing at large.

Earning the right certification will take you one step closer toward your career goal and make you marketable.

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