There’s a revolution happening in enterprise artificial intelligence (AI), but is there enough skilled AI talent coming through to take advantage?
Gartner says that by 2020, AI will be pervasive in almost every new product and service. By 2025, the size of the AI market worldwide will grow to $59 billion, with the largest proportion of revenue coming from enterprise AI applications.
According to PWC’s Digital IQ report, only 20% of executives said that their organizations had the skills necessary to succeed with AI. And last year, Ernst and Young said 56% of senior AI professionals said that a lack of talent was the biggest barrier to implementation within business operations.
“In 2017, as businesses strategized how to integrate into their operations, they were hampered by a shortage of experts with the requisite knowledge of the technology. It’s about the people,” said Chris Mazzei, Ernst and Young Global Innovation Technologies Leader and Global Chief Analytics Officer.
A pattern has been set, with Silicon Valley giants like Facebook and Google hoovering up talent. This means that one big issue for businesses is that AI talent is scarce relative to demand. Another is that salaries are high for people who have the required set of AI skills needed to make a real difference to an organization.
Arshak Navruzyan, Chief Technology Officer at Sentient Technology, says “Businesses won’t be known for their work with AI. Now if you want to do AI work you go to companies like Google, Open AI or Facebook.
“The average Fortune-level company needs to think about how they make themselves attractive to machine-learning researchers and data scientists. How can they amass enough of this type of talent to make a difference in the business problems they want to solve?”
Think about the recruitment strategy for AI talent
It will be easier to hire inexperienced engineers than senior machine learning experts who have developed AI skills and have a background in the area. This means that organizations might want to hire people who show a commitment to learning on the job and who could grow into a role focused around AI.
However, businesses seriously thinking about AI will certainly benefit from having top-tier experienced talent in senior roles.
In addition, organizations serious about AI need to treat it as a core competency. It’s not about simply creating an ‘AI lab’. The businesses that will succeed will have made a serious investment, thinking along the lines of attracting and incentivizing skilled AI talent to work for them and grow their careers
1. Partner with universities
It will be worth businesses hunting AI talent to sniff around universities and centers of research to identify top AI talent who might already have practical experience of working in AI.
DeepMind, known widely as a leader in machine learning, has joined forces with UCL’s Department of Computer Science to deliver a Master’s level training module, covering some of the most sophisticated topics in artificial intelligence. Businesses in all industries could similarly build relationships with universities specializing in AI, and would be first in line when it came to skilled graduates.
2. Hunt for talent through hackathons and event sponsorship
Hackathons bring people with technical backgrounds together to solve a problem and code solutions. But they are also a great way of bringing together top coding and creative talent in one place. Recruiters attending these events can perform interviews on-the-spot with people who show talent, aptitude and passion for the technology these businesses might want them to work with day to day. Complimenting events like career fairs, hackathons will have people who are practicing code and are putting a lot of thought into what they’re doing.
Businesses might also want to think about sponsoring AI events, conferences or competitions to attract international AI talent, as well as build their reputation up as a supporter of AI. Sponsoring an event can potentially create links with the right people, as businesses will demonstrate the right authority to prospective hires, as well as gain credibility and awareness.
3. Hire talent from AI-focused degree and certification programs
Because of an increasing demand for AI talent, education institutions are catering for demand by offering specialized courses to train juniors to find jobs. Recently, Microsoft opened a ‘Professional Program in AI’ to the public, which is designed to provide job-ready skills in AI and data science through online courses that feature hands-on labs and expert instruction. Participants successfully going through the learning track receive a digital certificate which they can use for their CVs.
Susan Dumais, distinguished scientist and assistant director of Microsoft Research AI, says, “AI is increasingly important in how our products and services are designed and delivered, and that is true for our customers as well. Fundamentally we are all interested in developing talent able to build, understand and design systems that have AI as a central component.”
4. Retrain existing staff
Businesses may be better off training the right people internally, updating the skills of existing engineers, and it would certainly cut out the risk of new hires not working out. Larger businesses could do this with corporate training programs, or even bring in external trainers. They also have the option of apprenticeships and mentoring to skill up junior members of the team.
AI is not just about recruitment, it’s a culture change
Given time, effort and budget, organizations should have ways to find individuals with requisite AI skills. But that’s only the beginning. If the popularity of AI grows as much as experts claim, having selected people to deal with the technical and business aspects of AI won’t be enough. It’s not simply about having people with the right AI skills – it will be a cultural shift in making AI a central part of conversations when it comes to technology, business development and strategic execution.
Mark Troester, Vice President of Strategy at Progress, believes that businesses must avoid treating AI as the exclusive domain of data scientists.
He said, “Businesses should adopt a more holistic approach that moves beyond silos that treat the analytics and the app development teams as separate.
“App developers need to become more knowledgeable about the data science lifecycle and app designers need to think about how AI and predictive insights can drive the application experience.
“By ensuring that the teams within the organization can work together seamlessly business can get access to a much broader pool of skillsets and talent.”
According to PwC, it’s vital to align AI innovation with strategic objectives and performance indicators, rather than have scattered initiatives in isolation. Having pilot projects isn’t enough – it’s about taking a fundamental look at how AI can disrupt businesses, and seeing what threats and opportunities this can present.