Agility, collaboration, and accountability are essential to an innovative culture, but they must work in balance. Here’s how to make that happen
How to make a career switch into AI: 8 tips
How can you switch from another IT specialty into AI? Experts say there’s still time: Try these transition tips to start building an AI career path
5. Get certified
“Once the foundation courses are completed, work on certification with one of the cloud platforms – Google Cloud, AWS, Azure,” advises Palaniappan. “While upskilling, start looking for projects where you can join as a data analyst or business analyst and try to apply your learnings.” Learning on the job can be the most effective approach.
[ Which certifications are worth the time and money? Read also: 13 top-paying IT certifications for 2019. ]
6. Find a mentor
If there isn’t currently a program in your organization to match up internal AI experts with those interested in the field, start one. “Pairing nurturing 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… given the heightened demand in the market for AI talent,” says Jarvinen.
7. Don’t forget to emphasize your soft skills
“Machine learning and AI are not a panacea for every problem. Understanding the fundamentals of the application, or working with people who do, is vital to having a robust end product,” Havens says. “Hence, communication, teamwork, and some business savvy can go a long way to being a successful machine-learning or AI architect.”
8. Always be learning
“Like so many fields in technology, success in AI will require continuous learning and training,” Jarvinen says. “Despite its evocative title, AI is remarkably similar to other fields in information technology, in that success comes through continuous learning, training, and great processes.”
[ Want lessons learned on AI? Get the new HBR Analytic Services report, An Executive’s Guide to Real-World AI. ]