Top

CAIO or NO CAIO: Customer Experience Depends Upon Structuring People to Manage Information

Joseph Michelli, Ph.D. | Jul 13, 2017 66 views No Comments

Share on LinkedIn

I first heard about “it” in a Harvard Business article in 2016 and subsequently have been asked about “it” by clients and colleagues alike. “It” is yet another entrant into the C-suite. “It“ (actually a she or he) is a Chief AI Officer (CAIO). That’s right a human Chief Artifical Intelligence Officer (not a machine or robot occupying an executive office).

The Transformational Power of AI

In his thought-provoking HBR article, Andrew Ng suggested artificial intelligence will produce social transformation on par with electricity from 100 years ago and the internet from approximately 20 years back. Andrew, the chief scientist at Chinese internet behemoth Baidu Inc., also linked the emergence of the internet with the evolution of the essential corporate position of Chief Information Officer (CIO). All of which set the frame for Andrew’s central argument:

“To the majority of companies that have data but lack deep AI knowledge, I recommend hiring a chief AI officer or a VP of AI. (Some chief data officers and forward-thinking CIOs are effectively taking on this role.) The benefit of a chief AI officer is having someone who can make sure AI gets applied across silos. Most companies have naturally developed siloed functions in order to specialize and become more efficient.”

We’ve Been Here Before

It is this “same logic” that drew my support for the chief customer officer (CCO) concept around 2006. For historical reference, the first customer officer, Jack Chambers, was appointed in 1999 at Texas New Mexico Power but the role didn’t gain significant visibility for many of us until at least 2003, when a small but impressive group of CCO’s began to surface (e.g. Jeff Lewis at Monster.com and Marissa Peterson at Sun Microsystems). In the early days of the CCO movement, the case was being made (and continues to be made today) that Chief Customer Officers are needed to “break down silos” and “focus on enterprise-wide strategy placing the customer at the center of all corporate decision-making.”

Decentralized and Nimble

Despite the general attractiveness of placing senior level leaders at the helm of enterprise-wide efforts, I’ve found myself resistant to the slowly emerging Chief Artificial Intelligence Officer (CAIO) movement. It wasn’t until I read 2017 HBR article from Kristian Hammond that my unsettled feeling was given voice. Here is Kristian’s key thesis posited in his article so aptly titled,  Please Don’t Hire a Chief Artificial Intelligence Officer:

It’s not that I doubt AI’s usefulness. I have spent my entire professional life working in the field. Far from being a skeptic, I am a rabid true believer. However, I also believe that the effective deployment of AI in the enterprise requires a focus on achieving business goals. 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. For AI to work in the enterprise, the goals of the enterprise must be the driving force.”

From my vantage point, AI is a monstrously powerful tool baked into the fiber of all aspects of data-savvy companies. It is best managed by agile teams that leverage Artificial Intelligence as a solutions and innovation tool. Neil Jacobstein the head of artificial intelligence and robotics at Singularity University went further by telling the Wall Street Journal  that:

“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. Centralizing AI across an enterprise might prove unwieldy compared to having small teams.

AI Itself Can’t Solve This

Invariably large, data-rich organizations will wrestle with the question “to add or not to add” a CAIO. Until I hear a more convincing case for this new position in the C-Suite I doubt I will be recommending the change.

The big takeaway for all of us is an appreciation of the transformational power and potential of big data, machine learning, and artificial intelligence. Also, it is the awareness that machines won’t likely solve issues like how to structure our teams and leaders to use that very data as we pursue key business objectives. Some things can only be left to the intuition and modifications of people!

Print Friendly, PDF & Email

Republished with author's permission from original post.


Recent Editor's Picks:


Categories: BlogCustomer AnalyticsCustomer ExperienceLeadership

66 views

No responses yet, why not leave yours?

Add Your Comment (All comments are reviewed by moderator, no spam permitted!)