Experts are divided about whether enterprises need a Chief Artificial Intelligence Officer (CAIO) and how the role relates to data scientists and CIOs. The argument against the role is that you don’t want a C-level position focused on a technology. In this view AI is a tool and it makes no more sense to hire someone at that level just to implement AI than for other tools.
Over the next few weeks I hope to demonstrate how far reaching AI is. I also will argue that the winners and losers in most industries will be determined by AI more than any technology since the PC revolution.
’AI’ isn’t your movie monster
The term “artificial intelligence” has morphed away from referring to artificial general intelligence (AGI). AGI is the pursuit of “true” intelligence, architected to mimic biological intelligence. That is what you see enslaving mankind or falling in love in the movies every summer. Today “AI” is an umbrella term that includes more practical and readily available technologies.
Machine learning, deep learning platforms, natural language processing, natural language generation, virtual agents, speech recognition, hardware integrated AI, decision management and, ultimately, big data and analytics are part of a single “AI landscape” and necessary for a competitive enterprise strategy. In the coming months I will explain these, and how enterprises are applying them to drive fundamentally shifts in their industries.
Whether leaders realize it or not, every enterprise is a data company. Amazon started off as an online bookseller with a strategy of making massive investments in technology. Their commitment to “data-first” led them to become one of the biggest innovators in AI. This enables Amazon to compete and ultimately disrupt diverse markets from cloud infrastructure and e-commerce storefronts to streaming media and grocery retail and delivery. To a business school from the 1980s they may look like a conglomerate. Amazon is a new type of business platform that demonstrates you can layer many businesses on top of a learning organization.
The lesson here is that no business is safe anymore. Because of this AI landscape, competitors can come from anywhere, even in ways the internet didn’t allow. AI also has unprecedented potential to drive “winner-take-all” disruptions which means simply copying or following the leader is as risky as doing nothing. Who are your second and third favorite online book sellers?
AI requires rethinking of critical business processes. It is business change facilitated by technology. AI is complicated and highly technical and will change dramatically as it matures. But, AI isn’t something technologists develop and deliver to the business. And the AI technical community is short of people who can bring technology and the business together.
The CAIO isn’t a data scientist or a CIO
Your data scientist can help unlock massive potential, but a CAIO is needed to make sure the vision has buy-in. It is essential for the enterprise to have a separate, senior level committed to evangelizing AI’s potential.
The time of a Chief AI Officer should be devoted to finding opportunities that allow a company to exploit the advances in AI for its benefit. To fulfill the role, a CAIO would have to work together with the CIO, CTO and general and functional business leaders.
The future winners will not simply leverage AI to solving existing business problems. AI needs to ultimately be a rallying cry to rethinking entire businesses. The CAIO will need to be a true agent of change and to advise the leadership team on strategy.
As with other transformative moments, hiring a CAIO will cause disruption in the leadership team of a company, with some CIOs fearing their turf is being threatened or that they are missing out on high profile opportunities. But few CIOs tell me they are short on job scope and long on time for more initiatives.
AI evolves so quickly that CIOs can’t expect to figure it out they you go, continue to cover current responsibilities and to realize AI’s potential. AI can be deeply disruptive to technology departments too, so an outside perspective is helpful. And for the next few years, most CAIOs will need to come from outside the organization, complicating a difficult job.
A CAIO can report to a CIO with lots of political capital and business savvy but only if they are truly committed to disruption as a business driver. Organizations that reward CIOs for large budgets and big teams are at real, long term competitive risk.
Compared to the strategy of innovative startups, many enterprises maintain or improve their market position do so because they exercise caution and increment change methodically. Risks are mitigated carefully because the enterprise risks more and can jeopardize valuable businesses. But AI can have a sudden impact. This requires rethinking the ways innovate and this is scary and risky. AI is a set of technologies that has the potential to reorder the winners and losers of most industries in a relatively short period of time. Expect the winners will be those who attract and leverage the best “AI landscape” talent and to turn it into transformation.