The HR community is enthralled by the idea that artificial intelligence (AI) can provide tangible benefits in the quest to effectively source and hire in a tight labor market. But how does this work in practice?
It starts by understanding a branch of AI called deep learning. Deep-learning algorithms, which are inspired by the actions of the human brain, continuously analyze data with a given logical structure. This structure encompasses multiple layers of algorithms called neural networks.
Deep-learning algorithms can’t predict the future or give answers that a human would agree with 100%. Yet they are still valuable. If you’ve ever used a modern search engine and been amazed by the results or if you’ve ever watched the perfect show recommended by your streaming network of choice, you have experienced the power of deep learning.
The main challenge of deep learning is data — specifically, the massive amount required. The talent space alone needs billions of data points about people, career trajectories, skills, and experiences.
But while AI’s reach was once limited by computing power and the availability of data, that’s no longer the case. Today, global neural nets can identify more than a million skills across the world’s 8 billion people.
Then, using this data, AI engineers can develop deep-learning algorithms to determine the best answers to a defined class of questions. In the case of deep talent, such questions might include: Who is the best fit for this specific job requirement? What job is this individual most likely to hold next in their career?
Understanding deep learning’s ability to harness a massive amount of data is only the first step, however. Next, we must explore how deep learning can help us identify skills and transform how we hire people.
The Power of Skills Adjacency
Skills adjacency refers to the inference that a person good at skill A often excels at skill B, and it helps us complete our picture of a human’s true potential and the transferable skills they possess.
In my recent book, “Deep Talent,” my co-authors and I tell the story of Nico Iannotti, a top sales engineer in Europe. Nico wasn’t always involved with either sales or technology. He was, however, previously involved with customer service as a sommelier and waiter. As he put it, skills are interchangeable assets that individuals can leverage in a variety of industry roles and life situations.
“Many of the skills I acquired prior to my corporate career have been very helpful in my role as a client-relationship manager and solution engineer,” he told us. “What is the link between pairing wines and selling software? Both are customer-facing roles, and both provide solutions to a customer’s problem. In both cases, you are building relationships, demonstrating empathy, and selling an emotional experience based on a specific budget. It’s just a change of context, not a completely different skillset.”
For the rest of the piece, head over to the UKG Workforce Institute.
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