Maryland and Washington, D.C.- based corporations need to embrace and implement hot tech trends like artificial intelligence (AI) and machine learning to remain competitive in their fiercely competitive industries.

Being successful, hinges partially on attracting sought-after employees with strong AI skills, as well as training current employees from diverse departments on fields like coding and algorithms.

In fact, Jim Liew, a professor at Johns Hopkins University’s Carey Business School, told SmartCEO that companies which do not have AI capabilities “will fall by the wayside…. And whoever leads in AI, in a particular industry, will dominate the industry.”

AI is used to automate many company operations and is used to analyze company data so a business can become more efficient, more profitable and understand its customers better.

Liew explained that a company’s board members need to understand AI, too. Promoting AI should start at the board level, and Liew said that if a board member does not even know what AI is, that board member “shouldn’t even be on the board.”

The CEO needs to prioritize AI, too, and hire someone for the C-Suite who is well versed in AI, Liew suggests. That person needs to have access to company data and resources. At that high level, companies need to identify the “biggest question” that will help the company succeed. Then see if relevant data can answer the question through a process of gathering data, analyzing the data and displaying it visually. There are many different algorithms that may be useful in answering the company’s data-driven questions, Liew said.

When looking for higher-level employees to work on AI and machine learning, there are two needed skill groups. One is business consulting, so the person can look at the “big picture” and can explain “how we can stay competitive as a business,” Liew said. The other skills are data-related. The person will need to know how to detect any bias in data that is being analyzed. That means understanding how data has been cleaned, curated and managed, Liew said.

“Someone with both skill sets – that is in short supply right now,” Liew said.

Companies also need to hire lower and mid-level employees throughout the workforce who either have a knowledge of AI or a willingness to learn about it, Liew said. Current employees may want to train themselves in the field, starting with learning how to code and then learning about algorithms. Companies can also train their employees in AI, such as through hackathons or holding training sessions, Liew recommends.

One common thread for anyone doing AI or machine learning is that there is a lot of “trial and error,” Liew said. He explains there may be a lot of failures along the way before employees find something that works.

But the talent is needed in the workplace.

“There’s great demand for people who have the skills,” Liew said. “That demand is definitely going to increase.”

Rachel Russell, executive director of corporate strategy and marketing at Allegis Group’s Maryland office, said currently there is demand for employees who work with AI-related technology in software engineering and IT consulting. Other high-demand skills include: data and analytics, modeling, computational intelligence, machine learning, mathematics, psychology, linguistics and neuroscience.

“There are many types of roles that work with AI, there is no single job type or employee type that is called ‘AI’,” she told SmartCEO.

Nationally, powerhouse companies like Google, Amazon, Facebook and IBM have been hiring a lot of people with AI skills. Where does that leave smaller companies? “To compete for that talent, less well-known companies have to offer a truly compelling opportunity,” Russell advised. “People with AI-related skills want to do work that’s exciting and meaningful to a company’s strategy and its ability to disrupt the industry and pioneer a new level of value and service. Of course, the hiring manager will need to expect to pay commensurate for these highly-valuable skills, too.”

AI also touches on many practical applications. Natural Language Processing (NLP) can automate a lot of research done by legal departments. Machine learning can be used in finance and accounting. “In these cases, you’ll start seeing firms looking not so much … [for] programmers, but more for people in their fields who are comfortable using the technologies that do the work,” Russell said.

AI also will soon be listed in job descriptions for non-technology positions. For example, a paralegal will need to know how to use an AI-driven research tool, Russell said.

“With the potential to cut up to 40% of labor costs, everything that can be automated, will be,” Russell added.

Also, Liew has confidence that Maryland has potential in the field, with the presence of many corporations, research universities, healthcare organizations and government offices located here. “There’s no reason Maryland can’t lead in this,” Liew said. “People are really smart here.”