Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. In the era of mass AI adoption, aimed at enabling disruptive technology innovations, this week we will explore the concern over skill shortages in the AI market.

 

Preparing for AI adoption amidst a serious skills shortage

Illustration by Balaji K.R.

Artificial intelligence(AI) remains a major technology driver for 2022 and beyond. It has been ranked in the top technology trends consistently for several years. It is no surprise that organizations are planning to adopt AI in their business and there is a fear of missing out for organizations that want to jump into the AI bandwagon. 

But are these organizations equipped with the right talent to build and sustain AI in their businesses?

According to a recent IDC report, spending on AI will reach $342 billion in 2021. Meanwhile, O’Reilly’s 2021 report on AI adoption showed that major barriers are the lack of skilled people and difficulty in hiring.

Organizations now must address the question “What is the best way to adopt AI in their business?” Build or buy?

“Build” is investing in setting up AI teams that include people, hardware, and software. “Buy” is looking for readily available AI solutions or resorting to AI services. Each of these options comes with its own pros and cons in terms of time, money, energy, and ownership of the AI solution developed.

The fierce battle begins with finding top talents for AI, and the top companies are ready to pay the big bucks for it. In 2016, Google-owned DeepMind paid an average of $345,000 per annum each for 400 employees.

Here are five interesting reads on the AI skill shortage and how organizations can address it.

  1. The AI Talent Shortage Isn’t Over Yet

 Globally, organizations are vying to hire the top talents in AI from an inadequate number of candidates. Despite economic disruptions and layoffs caused by the pandemic, the demand for AI talent remains strong as management seeks to reduce costs through automation and enhanced efficiencies, areas where AI plays a key role. The article discusses how to identify the skills gap according to the needs of the AI project.

  1. The reality of America’s AI talent shortages

Cybersecurity being a key application area for AI, the skill shortage in AI is considered a national security concern. Due to the limited availability of talent domestically, there is a need to rely on foreign talent. To build and sustain talent creation, there needs to be some form of incentivizing for organizations to partner with universities and schools to facilitate AI upskilling.

  1. 8 considerations for buying versus building AI  

Even though there are advantages with using off-the-shelf AI software, building software could prove to be more advantageous due to domain expertise in niche markets, or creating core AI tools that provide key differentiators from peers and competitors. The article discusses the various factors to be considered when evaluating whether to buy or build AI.

  1.  How low-code platforms enable machine learning  

 Low-code and no-code, in simple terms, means to automate coding. In a world where there is a serious AI skill shortage, citizen analysts and software developers can use the existing models to build the required AI models as easily as if they are drag-and-drop functions.

  1. Navigating the Post-Pandemic Intelligent Automation Talent Shortage  

AI talent requires a unique combination of skills: technical expertise along with a good business and change-agent acumen. Many organizations need to reimagine the way employment packages are offered to attract individuals with these in-demand talents. The article discusses the traditional and alternative ways to source and recruit individuals with this combination of skills.

The push towards building effective AI teams is also facilitated by the supporting ecosystem. The AI Index report 2021 by Stanford University shows that universities have increased their investment in AI education over the last four academic years. Engaging with the universities and schools with training programs, helps organizations solve the talent shortage in the long run. The advancements in computational capabilities further promotes the adoption of AI. With organizations competing in recruiting in-demand talent, they need to find innovative ways to entice individuals to choose to work for their organization not just for big paychecks, but also for joining to build and experience a great work culture.