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Artificial intelligence (AI) is transforming the way we live and work, and the pace of that change is accelerating across every aspect of the business landscape, from operations to the customer experience. As its capabilities expand, investment in AI continues to grow, reaching $67.9 billion in 2020 – a 40% increase from the year prior – according to the Stanford AI Index Report 2021.

Organizations that want to stay ahead know they face fierce competition for talent with in-demand skills like data scientists, data engineers, cloud engineers, and solutions architects. But too many have a blind spot to the need to develop AI acumen outside the technical space. And it’s the companies that do both that will ultimately win in the marketplace.

Artificial intelligence (AI) is transforming the way we live and work, and the pace of that change is accelerating across every aspect of the business landscape, from operations to the customer experience. As its capabilities expand, investment in AI continues to grow, reaching $67.9 billion in 2020 – a 40% increase from the year prior – according to the Stanford AI Index Report 2021.

Organizations that want to stay ahead know they face fierce competition for talent with in-demand skills like data scientists, data engineers, cloud engineers, and solutions architects. But too many have a blind spot to the need to develop AI acumen outside the technical space. And it’s the companies that do both that will ultimately win in the marketplace.

To develop, deploy, and manage big data and AI solutions requires recruiting, training, and cultivating a highly skilled AI workforce. But with demand outpacing resources, to compete for top talent means an organization’s leaders have to create the right culture to attract these individuals and the opportunities to keep them there. Among the key components of that culture:

• Support for their development and lifelong learning: AI talent is drawn to environments that enable them to hone their skills through rich learning opportunities and progressively more challenging projects.

• The resources to see projects through: They want to know that when they work on meaningful challenges, the resources are in place to shepherd those projects through to production, so they can see the impact of their efforts.

• An ethos of giving back: Beyond skill development, data scientists and other AI professionals increasingly have a desire to contribute not just to profits but to a higher order of things. A well-articulated mission to drive greater good can help tip the recruitment scales in your organization’s favor.

• Flexibility: The AI field is full of self-motivated people who are driven to learn more and embrace hard work. But they want flexibility in how they get that work done and will have greater job satisfaction in an environment that enables it.

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