The C-Suite grows merrier by the minute as increasingly more executives join the party at the top. From just a handful of head honchos, many companies now employ a full roster of “chiefs” — including chief data officers, chief customer officers, and chief culture officers — to take on crucial, enterprise-wide functions. The latest title to generate buzz and wiggle into the boardroom is your controversial Chief AI Officer (CAIO).

Chief AI officer is still a nascent corporate position and might take a few years to become a standard C-level title – if ever. A cursory public search on LinkedIn revealed less than 10 persons with such a title. Meanwhile, only two professional groupings contained the term, with their total membership clocking in at around a dozen. In contrast, a search for “chief wellness officer” returned around 250 profiles.    

But as organizations evolve and become more complex, the need for specialist leaders to helm critical aspects of a business understandably intensifies. With artificial intelligence and component technologies — machine learning, natural language processing, robotics and computer vision — already fundamentally disrupting markets, workflows and our way of life, pundits predict a rising need and urgent demand for CAIOs.   

Not everyone agrees on the impact of artificial intelligence on work and society. Tech luminaries like Elon Musk and Ray Kurzweil disagree on the level of existential peril humanity faces as AI matures to full potential. On a less alarming topic, experts are also divided on whether companies actually need a Chief AI Officer.     

If the prior trend of hiring Chief Data Officers (CDO) is a predictive indicator, the inertia currently preventing the wholesale acceptance of CAIOs may dissipate if AI transitions from overhyped to standardized technology. In January 2016, Gartner predicted that 90 percent of large enterprises will have a CDO by 2019. By August 2016, Forrester found nearly half (45 percent) already did. Meanwhile, the number of professionals on LinkedIn brandishing the CDO designation exceeds 3,000 while membership to Chief Data Officer groups surpasses 10,000.

Big data and artificial intelligence are related technologies offering tremendous benefits. But the Chief AI Officer may still tread a different path from the route taken by the CDO.

 

The Case For CAIOs

Leading AI and machine learning expert Andrew Ng practically started the debate when he wrote on the Harvard Business Review that data-rich companies with low AI knowledge need a CAIO. His peers and other authorities on the subject soon took sides.   

Andrew Ng has served as Chief Scientist at Baidu, co-founder of Coursera, and led the Google Brain Deep Learning Project which developed massive neural networks that autonomously learned concepts by merely watching videos. He continues to teach and conduct research on machine learning and data mining, recently announcing a new venture, deeplearning.ai

Ng’s primary arguments in favor of a CAIO are:

  1. A Chief AI Officer will ensure that AI gets applied across all the silos in an organization.
  2. A dedicated AI team led by a CAIO can help attract rare AI talent.

Karen Lawson, who has held CIO and CTO positions at several companies, agrees. In an article published by Information Management, she argues that a CAIO is a critical evangelist for championing people, processes, and tools that will drive real business value with AI. 

Meanwhile, NASA’s Steve Chien reveals that the Jet Propulsion Laboratory where he serves as head of artificial intelligence is considering opening a CAIO position to lead the unit’s efforts in robotics, AI and machine learning. Commenting on the growing need for such a role across other sectors, he emphasizes“You’ll want every employee thinking about how A.I. can improve what they do and you’ll want a chief A.I. officer overseeing all of that.”

 

The Case Against CAIOs

On the other side of the debate, Kristian Hammond, Chief Scientist of Narrative Science, questions Ng’s call for companies to hire CAIOs. 

“The effective deployment of AI in the enterprise requires a focus on achieving business goals,” he clarifies. “Rushing towards an ‘AI strategy’ and hiring someone with technical skills in AI to lead the charge might seem in tune with the current trends, but it ignores the reality that innovation initiatives only succeed when there is a solid understanding of actual business problems and goals.”

Neil Jacobstein goes even further. In an interview with The Wall Street Journal, the head of artificial intelligence and robotics at Singularity University said centralizing AI across an enterprise might prove unwieldy compared to having small teams exploring how AI can solve their specific business problems.

In his words, “it’s very important to match the speed of the technology with the nimbleness of the teams. And having a centralized AI guru at the top, where everybody has to ask questions of that person, is unlikely to be as fast and effective as having a decentralized organization with powerful teams.”  

 

What Both Sides Agree On

The decision to have a CAIO or not might separate experts into opposing camps. But there remains a sweeping consensus: no one argues against the notion that artificial intelligence will radically transform the landscape and any business without an AI strategy will flounder.

McKinsey Global recently reported that investments in AI have been growing fast and will usher in the next wave of disruptions. Early adopters will reap tremendous benefits while players on the sidelines must hustle to catch up or risk being left behind. The figures are persuasive. Tech giants have spent $20 billion to $30 billion on AI-related research and acquisitions in 2016 and are projected to spend over $650 million in recruiting AI talent annually. 

Given the glaring importance of AI, every business wishing to future-proof profitability needs to have an AI strategy now, with or without a Chief AI Officer.