AI on the horizon
AI may be the next technology wave to shake up the IT operations model. AI will likely play numerous roles, from providing cognitive capabilities to process robotics to enabling natural language processing chatbots.
In this environment, Tan sees continuing demand for data scientists who can generate and validate hypotheses, create algorithms and understand aspects of AI such as machine learning and deep learning. But people skilled in data science “are not easy to find,” she conceded.
“Data scientists are at a premium,” Tinic agreed. “We’re not going to staff the organization with hordes of data scientists.”
Instead, Tinic said his approach will be to evolve systems engineers to become more analytical and up to speed on data science. He said Level 3’s technology teams already deploy AI in various flavors. Uses include bolstering cybersecurity, identifying patterns that indicate possible systems issues and optimizing resources — identifying which employee will be the soonest available to do a particular task.
Training IT staff is one approach for overcoming the shortage of data scientists. Another is to acquire software tools that can turn business users into citizen data scientists. Business teams are beginning to use tools that automate elements of the data science process.
John Reed
In any event, retooling and reskilling appear inevitable as AI makes its way into the IT department. John Reed, senior executive director at Robert Half Technology, an IT recruitment firm, said AI will likely create a shift in the way some people work and the skills they will use every day.
“The strength of technology professionals, though, is in their ability to be flexible and constantly learning, which will help them take any changes to the way we work in stride.”
But what they end up learning may stem from experimentation, rather than a formal program of knowledge. PwC’s Curran said he’s a big believer in demonstration labs as a mechanism to help determine what skills an organization will need to absorb a particular technology.
“The AI domain is perfect … for experimentation,” he said.
A demonstration or innovation lab is the ideal setting to kick the tires on AI tools and find out what IT staffers know — and what they don’t know, he said. Curran said AI experiments can help determine what kind of skills development and training will be necessary and what kind of third-party help might be required.
“I think that is a best practice — having that capability to do the hands-on experimentation.”