The Five AI Professionals Companies Need to Succeed in 2019
It’s difficult to have a business conversation without the mention of artificial intelligence (AI). The technology has become a strategic imperative for companies to stay relevant and competitive. Businesses now realise that the key to lasting competitive advantage is integrating AI into the operations of the entire enterprise.
In fact, last year, from January to September, there was a 63 per cent rise in job openings related to emerging technology, and AI expertise was one of the top subject matter needs, according to US-based non-profit trade association Computing Technology Industry Association, or CompTIA.
Now, a new report by consulting group KPMG has identified five AI professionals companies will need to succeed in 2019. The findings are based on KPMG’s own AI projects and those they advise clients on. “The AI deployment of integrated and scalable solutions across the business requires more than just data scientists. It takes a robust team with a range of specialized AI and business skills who can help with every stage of the process. And right now few companies seem to have the right mix needed for AI to bring strategic value to an organization,” says Brad Fisher, partner (data and analytics lead) at KPMG (US).
The AI architect takes care of individual business processes, as well as the big picture organization, and determines 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 companies cannot successfully sustain AI initiatives, the report says.
AI product manager
The AI product manager works closely with the AI architect and serves as a liaison across multiple business teams to ensure solutions are successfully implemented. They also work closely with these teams and the HR (human resource) to identify organizational changes needed to ensure optimal performance of both humans and machines.
With the availability of growing data with companies, 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.”
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.
As we are still learning the ethical and social implications of the AI technology, companies may need to create new jobs tasked with the critical responsibility of establishing frameworks related to AI 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,” says Fisher.