Artificial Intelligence (AI) still dominates the conversation, yet we are still in the early stages of understanding its potential impact. In most cases, companies have launched small or disparate experiments, leaving AI lingering in the pilot phase.
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To effectively move AI from the lab to scalable deployment—and realize its true potential—companies face a growing need for employees with specialized skills to build, manage, deploy, and then monitor AI technologies. In fact, according to CompTIA, from January through September of 2018, there has been a 63% increase in emerging technology job openings. And AI expertise is one of the top subject matter needs.
The entire AI deployment process requires more than just data scientists. It takes a robust team with a range of specialized AI skills who can help with every stage of the process—and right now, only the elite technology and consulting firms seem to have the right mix needed for AI to bring value to an organization.
With the surge in open AI roles on the horizon, companies are competing to build and diversify their teams to help them progress from AI pilots to integrated and scalable solutions across the business. Based on KPMG’s own AI projects and those we advise clients on, here are the top five AI jobs companies need to create/consider if they are to effectively build their AI capabilities:
AI Architect
These specialists look at individual business processes—as well as the big picture organization—and determine where they can inject and embed AI successfully.
They are also responsible for measuring performance and sustaining the AI model over time—ensuring it removes mundane tasks to optimize humans in the workforce. The lack of AI architects is a big reason why companies cannot successfully sustain AI initiatives.
AI Product Manager
Working closely with the AI architect, the AI product manager serves as a liaison across multiple business teams to ensure solutions are successfully implemented. They also work closely with these teams—as well as HR—to identify organizational changes needed to ensure optimal performance of both humans and machines.
Data Scientist
With the ever-growing amount of data available to businesses, there is a shortage of experts with the skills to clean this data, and then design and apply the appropriate algorithms to glean meaningful insights.
Software Engineer
One of the biggest problems facing businesses is getting AI from pilot phase to scalable deployment. Software engineers work hand-in-hand with data scientists to bring AI into production, blending business acumen with a deep understanding of how AI works.
AI Ethicist
As ethical and social implications of AI continue to unfold, companies may need to create new jobs tasked with the critical responsibility of establishing AI frameworks that uphold company standards and codes of ethics.
Initially, these roles could be fulfilled by existing leaders in an organization, but as the effects of AI fully take shape, it may need to be the responsibility of one person to ensure these guidelines are upheld.
AI is surely becoming one of the most prominent technologies across every industry. But for businesses to realize the significant benefits it offers, they must ensure they have the team in place to bring it from potential to reality.
Brad Fisher is a partner and U.S. leader of Data & Analytics at KPMG.