The results of LinkedIn’s latest Emerging Jobs Report in December came as little surprise to those of us in the AI space — machine learning engineers and data scientists are the two fastest-growing new jobs in the U.S.

And that’s not just in the technology industry. LinkedIn’s report tracks the full range of jobs across all sectors, from real estate to health care, retail, manufacturing, and travel. The rapid growth of AI-related careers is yet another reflection of how AI is poised for a breakthrough transformation in our business and personal lives.

As the chief people officer at Aera Technology, I’m in charge of building out our global workforce. Interestingly, when it comes to AI in business, distinctly different roles — say, in development and customer-facing positions — share similarities when it comes to seeing the potential of using AI to improve an organization.

For instance, new hires for development roles such as machine learning engineers, data scientists, and UI developers may not have deep domain expertise in subject areas such as finance and supply chain. However, as AI experts, they immediately see the huge potential for AI to transform data-intensive and dynamic processes.

Conversely, we tend to hire seasoned professionals with domain expertise for customer-facing roles such as engagement managers, client directors, and customer success team members. They might not have a strong background in AI, but they are intimately familiar with the weaknesses of traditional software solutions. They quickly grasp how and why AI is ideal for business optimization.

As AI expands across our business and personal lives, I field many questions from potential job seekers on prospects in the AI field: What do I need to learn? What skills are required? Is a career with an AI company a good fit for me? My answer usually starts with that trusty caveat: “It depends.”

The most successful employees in the AI field relish a challenge. They’re entrepreneurial adventure seekers who thrive on disrupting the status quo. They’re thrilled to take a leap into the future and love making an impact. They welcome learning and innovation in a fast-paced environment and pushing the edge of the possible.

So, a career in AI is not for everyone. Plenty of people are satisfied with a more predictable job and career path. But if you have an appetite for the challenges and rewards of an AI career, I can share a few thoughts on why to jump in and how to get started.

Get in on the ground floor

Despite its rapid growth, AI remains in its infancy. Those who get in on the ground floor are seizing the first-mover advantage in skills, expertise, and leadership. In a few years, that experience will pay off with more job opportunities, greater decision-making responsibilities, and higher wages as companies apply AI in virtually every industry and job function.

Make a genuine impact

Whether the role is as a back-end data scientist or a customer-facing solution consultant, personnel at an AI technology company have the opportunity to shape the future. Working side-by-side with visionary leaders and colleagues opens new avenues for collaborative brainstorming and problem-solving. That translates into real-world impact at customer organizations and the personal gratification of driving change.

Build your credentials

Whether you’re new to AI or already have some background, invest in building out your knowledge and resume. You’ll find a wealth of online courses in many aspects of AI, from entry-level to advanced, as well as meetups both in person and online. Those are a great way to learn, network, and share. A resume that reflects proactive AI pursuits can be a big plus in landing a job.

There may never be a better time to focus your career path toward AI. Gartner, for one, predicts that AI will create 2.3 million jobs by 2020, though automation may eliminate 1.8 million positions elsewhere. Choosing an AI career is a sound way to stay ahead of the curve.

Emily Hallowell is the chief people officer at Aera Technology, cognitive technology for the self-driving enterprise.