The AI Talent Squeeze Is Hurting Industry

Here’s what businesses can do

Published: Wednesday, June 15, 2022 - 12:02

With ongoing global shortages of all kinds of goods, from cars to lumber to cooking oil, both consumers and companies are struggling. The Russian invasion of Ukraine, along with renewed Covid outbreaks in China, are two things that are likely to make things worse before they get better.

One way to solve the ongoing crisis, according to experts, is to use artificial intelligence (AI) to improve manufacturing, distribution, and shipping systems. But many industrial companies are having trouble finding enough qualified engineers and other professionals to implement this badly needed AI. Not only are AI engineers not numerous enough, but the top talent that is available tends to go to work for the big tech companies, which have the deep pockets to offer AI talent salary and benefit packages that most industry and business can’t begin to match.

How should manufacturers, distributors, and others who need AI help but are struggling to hire AI talent deal with this talent squeeze? One alternative is to try and grow AI expertise within the company, funding education for promising employees. While this could be a good longer-term solution, it’s not going to solve problems that demand immediate attention, such as current production, supply chain, or distribution issues.

Another option is to use AI-as a-service solutions. Among the AI projects big tech has undertaken with its large pool of talent are sites with “plug and play” AI modules that users can download to solve specific problems. Given the popularity of these modules, it’s likely that many companies are able to solve specific problems using them. But often these alone aren’t sufficient, and a more tailored, customized approach is needed.

Companies that need more immediate and specific solutions could get the help they need by working with an AI services company to develop customized solutions. But companies seeking to implement AI this way must tread carefully and vet their new partners to ensure that they have the know-how and experience needed to make AI the solution to the company’s particular issues.

AI isn’t just another technology—it consists of specific advanced technologies, including machine learning, natural language processing, neural networks, deep learning, cognitive intelligence, and more. Developing expertise in these areas requires a great deal of knowledge and experience, and many of the AI service companies just don’t have that. To avoid disappointment, companies should prepare themselves accordingly.

Set expectations. Some 85 percent of AI projects never reach completion. One major reason for these failures is that many companies just expect too much from their projects. Often, what is portrayed as AI is really just a type of advanced statistical analysis technology that has been around for decades. Clearly that is useful in many cases, but at the same time, many companies need something more sophisticated to solve their problems. Companies should educate themselves on what AI can do, how it can help them, and determine if their potential partner has the skills, knowledge, and capabilities to take on their project.

Have a plan. To avoid AI project failure, companies, along with their partners, must develop a specific plan that will list all the actions they need to take to achieve the desired result. This greatly increases the chances of project success because it enables companies to look objectively at the stages involved in developing an AI solution—as well as determining whether their potential partners have the experience, knowledge, and skills to carry the project out. Proper planning increases the chances of success and reduces the likelihood of disappointment.

Understand the scope and required resources. To accomplish the desired goals, an AI project requires data, time, talent, and, of course, money; failure to allocate enough of any of these will likely lead to failure of the project. A good partner will be able to take the overall plan and break it down step by step. These include how long each stage is expected to take, how much it will cost, and what skills will be required to accomplish it.

AI is indeed going to change the world, but in many ways, it’s still in its infancy. More universities are offering courses and degrees in AI, but it’s going to be awhile before the large cadres of talented AI engineers that business and industry need are going to be available. Until then, companies need to carefully research their needs, understand their resources, and seek out the partners that can help them competently carry out their vision in 2022 and beyond.

About The Authors

Faustino Gomez

Faustino Gomez is CEO and co-founder at NNAISENSE. Shortly after receiving his Ph.D. in artificial intelligence from the University of Texas-Austin in 2003, he joined the Swiss AI Lab, IDSIA, initially as a post-doctoral researcher and then senior researcher working with computer scientist Juergen Schmidhuber. He has published more than 50 papers in the fields of neural networks, evolutionary computation, machine learning, and reinforcement learning.

Sepp Hochreiter

Sepp Hochreiter heads the Institute for Machine Learning, the LIT AI Lab, and the AUDI.JKU deep learning center at the Johannes Kepler University of Linz, Austria. He is director of the Institute of Advanced Research in Artificial Intelligence (IARAI) and a pioneer of deep learning. His contributions in Long Short-Term Memory (LSTM) and the analysis of the vanishing gradient are viewed as milestones and key moments in the history of both machine learning and deep learning. He also is a full professor at the Johannes Kepler University and head of the Institute for Machine Learning.