Don’t Make the Mistake of Building Recruiting AI
When it comes to building vs. buying artificial intelligence systems for recruiting, it’s a definite buy. The AI thinkers at Boston Consulting Group characterize the decision to build or buy as “rarely an either-or choice,” and the question of working with AI vendors, a “how—not whether.” Yes, Censia is an AI company, but no matter the provider, we want to see recruiting AI proven in the marketplace. Unless you too are an AI company, in-house development of recruiting AI will not lead to its success at your organization. We strongly advise against it.
In addition to wanting to see recruiting AI succeed, Censia wants to see talent acquisition teams acting strategically on behalf of their companies. Overseeing the heavy investment in the talent, data and technology needed to develop and implement AI is a behemoth task that recruiting teams today simply aren’t equipped to take on. Even if it were possible, the process would be long, expensive and difficult. AI lets recruiters focus more, not less, on what they do best, converting candidates into employees face to face.
The War for AI Talent
Talent acquisition is a war, and its most intense, ongoing battle is for AI talent. Censia believes talent is the lifeblood of every organization, and AI teams are no exception. AI is still a relatively new discipline, so the supply of talent is still limited. Conservative estimates place the number of active AI job candidates at less than a third of total AI job postings in the US. Entry level salaries fall in the $300,000 to $500,000 range, while contracts with top talent in the field are beginning to resemble those of professional athletes.
Data and Technology
In our last blog post, we discussed how data is the foundation of any AI system. Most companies have enormous amounts of people data, which is where most of the temptation to home-grow AI solutions stems from. In that post, however, you learned that AI not only relies on data, but the effective storage, movement and processing of it, to make it usable. As data scientist Monica Rogati explains, those activities are just the bottom of the AI hierarchy of needs. To support an enterprise-scale solution, Censia utilizes multiple technologies in every layer of its technology operations, from data platform to infrastructure, to front-end client service delivery and the software development process. Assuming your organization possess the talent that knows how to develop and operationalize algorithms, the necessary technology is complex to both build up and maintain over time.
Bringing together the talent, data and technology necessary to make AI work is no small feat. The established organizations that are taking on the endeavor have already invested years and at minimum millions of dollars to do so. There is a lot of excitement surrounding recruiting AI, but that doesn’t mean companies should begin building their own to reap the benefits. To make recruiting AI a success, engage the right vendor effectively. In the coming weeks, we’ll dive deeper into working with vendors to bring AI into your talent acquisition function.