— From health-care delivery to government affairs, automation and artificial intelligence are altering the way business is getting done.

To understand their usefulness, one must first understand the distinction between the two, according to Brian Casazza, chief information officer for the B2B coaching company Vistage International.

“Many people use the terms ‘AI’ and ‘automation’ interchangeably when in fact they are very different,” Casazza said. “Automation is software that follows pre-programmed rules, and AI is designed to simulate human thinking.”

At AMN Healthcare, automation has proven most beneficial so far.

Automation Fills In

“Our automation efforts are freeing up team members to focus on higher-value activities,” said Julie Hubbard, vice president of infrastructure for the nursing and other health-care staffing company.

AMN started with IT automation, then grew to use robotic process automation software.

“In many cases, automation is the first step toward (using artificial intelligence),” Hubbard said. “AMN started with automation, and I expect that we will see those activities on our technology roadmaps for the next couple of years. Much like others in the staffing industry, we are looking toward artificial intelligence as an opportunity to reduce the time-to-talent through the use of data mining and statistical modeling that will match candidates to open positions more quickly.”

At DMV.org, automation is also used well while the practical application of artificial intelligence still in its infancy.

“Automation is embedded in our genes at this point as all businesses aim for efficiency, precision and scale,” said David Gray, vice president of product and engineering for the state site.

Though the use of artificial intelligence is not yet well developed at DMV.org, implementations of it are coming fast, according to Gray.

A Revolution

“Artificial intelligence will be the technical revolution of our time,” he said. “The applications are rising due to processing power and data consumption. Autonomous vehicles will transform how we think about transportation.”

Though her own company started with automation, AMN’s Hubbard insists there is no one-size-fits-all approach to adopting automation and artificial intelligence into a business’s technology.

“There is no right or wrong answer here, I think this depends on the industry,” she said. “For example, science-based companies managing massive amounts of data are probably looking at artificial intelligence before automation, whereas finance companies have likely focused on automation as a first step.”

Vistage started by leveraging artificial intelligence to help find and engage with new customers.

“We’ve implemented artificial intelligence and within our customer relationship management platform to automate conversations with member candidates at the very top of the funnel,” Casazza said. “This has improved our effectiveness and efficiency with how we contact, nurture and qualify our leads. As a result, we are improving our lead conversation rates and sales productivity. We have also implemented artificial intelligence within our customer feedback loops to help us better understand and act on customer sentiment.”

Predictive Analytics

Casazza said the next wave of artificial intelligence implementation for Vistage will be centered around predictive analytics.

“We will gear it toward enhancing our member experience by delivering deeper personalization and more relevant content recommendations,” Casazza said. “There is also a significant opportunity for us to leverage artificial intelligence to identify members who may be at risk of canceling their membership. To the extent that we can accurately predict attrition we can then automate tasks and workflows designed to address whatever the problem areas may be.

“Taken together, these initiatives will build on artificial intelligence and automation capabilities to improve member value and increase our retention rates,” Casazza said.

Like anything, there are going to limitations of artificial intelligence and automation.

“Limitations will largely be centered round talent gaps,” Hubbard said. “There will be an increasing demand for data scientist, process experts, robotic process automation architects and engineers. Cybersecurity professionals also have to adapt to meet emerging risk associated with these technologies.”