What exactly is technical debt? When discussing your organization’s technical debt - and possible changes to it - with various audiences, you need to articulate the key issues in plain terms. Here’s expert advice on how to do that.
AI skills: 5 ways to build talent internally
Artificial intelligence skills are hot. It’s time to stop bemoaning the lack of AI talent and start training up existing staff
4. Make AI skills development a continuous process
Certain kinds of training might be well-served by one-off or short-term programs; developing AI skills is not one of them. The complexity and pace of change in the field will be immense.
“The most successful organizations will develop programs for ongoing training and education,” Jarvinen from OpenText says.
One way to foster this: Make learning collaborative, in the sense that information is shared widely and your “students” get to become the teachers once they’ve gained proficiency with new skills and tools. Johnson notes that when you send team members outside of the firm for training and education, for example, you should sponsor initiatives that enable them to share what they’ve learned with others.
At LexisNexis, ongoing learning includes regular collaborative work across teams.
“For example, we conduct regular internal hackathons that provide a rich environment for sharing AI skills among teams and for trying new things out,” Reihl says.
As some team members gain AI expertise, you can create incentives for them to help bring less experienced people up to speed, which can produce a wide range of benefits.
“Nurturing internal AI experts as mentors and evangelists can have a major impact,” Jarvinen says. “Matching senior practitioners with a junior analyst or others making a transition into a more AI-focused role can help build skills and insulate an organization against attrition issues. [You’re] ensuring knowledge is shared and an institutional memory of best practices is created, rather than held in secret by only a few key employees who risk moving on one day given the heightened demand in the market for AI talent.”
5. Identify the right people for training
Especially at the start, it’s important to pick the right people for developing internal AI skills. Reihl points to your software developers as a good place to start, since programming (especially in certain languages, like Python) is commonly a foundational AI skill. But you don't have to be a developer. Here are some other “types” that experts say might have a good aptitude for building AI skills.
- Data scientists and analysts: “Data scientists and technical data analysts often have the base skill set that is needed and would do particularly well if they had engineering support,” Macskassy says.
- Anyone who works with a lot of data: “We generally find that team members that operate with a lot of data tend to be the first choice,” says Kashyap from Awake Security.
- Engineers with math and stats backgrounds: Engineers with a strong math or statistics background also make for great candidates, since many AI/ML projects require a foundation in those areas,” adds Macskassy.
- Strong collaborators and problem-solvers: Johnson from Robert says that technologists with strong collaboration, problem-solving, and strategic thinking abilities are good bets for AI success. Kashyap agrees: “We find that problem solvers and critical thinkers in general seem to adapt best to any technology trend including AI. These people always have a desire to take on complex challenges and master them. Having the ability to look beyond an obvious answer and drill down to the core of a problem will behoove workers reskilling for AI,” he says.
Ultimately, any IT pro who’s enthusiastic about learning and interested in AI might make a good fit.
“The reality is that there are opportunities across all of our systems to improve through AI technologies,” Reihl says. “We want all engineering roles to understand the types of problems that can be solved so we can leverage the technology across all of our systems.”
Johnson echoes the notion that just about any IT pro could be a good fit, in part because so many IT roles will eventually have to interact with AI technologies and processes, if they don’t already today. Identifying the “right” people comes back to the idea of asking and empowering your team to identify the best uses for AI in your business.
“By doing so, you will identify team members that may be ready for the next step in advancing their skills within the AI world,” Johnson says.
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