Machine Learning: Is it time for one more seat at the Chief’s table?

As technology gained adoption in an increasingly broad range of corporate environments, new functions emerged that were based on these new technological capabilities. Along with the new functions came many new job titles, including Chief Analytics Officer (CAO), Chief Data Officer (CDO), and Chief Insight Officer (CIO).

Now that Machine Learning has begun to take off, is it a time to create Chief Machine Learning Officer (CMLO) role?

Machine learning is actually not a new technology. It was part of computer science curricula back in the 1970s J. It has been used in bioscience, the oil and gas industries, and other businesses for some time. As it has become applicable to more industries, however, it has gained more interest in the corporate world.

Typically, job titles lag the adoption of new technologies. For example, the term “Data Warehouse” was first introduced around 1980, but the first CDO was not appointed until around 2001, when companies like Yahoo and CapitalOne saw the need for this role. Let’s assume it took about 20 years for the technology to get mature and for corporations to start recognizing the value of data management practices. Over time, the role of CDO became defined more consistently, and now it is part of normal corporate org chart.

Jobs titles that include “Chief” were created for roles that are critical for the company’s existence. For example, finance is required for any company’s existence, so the role of Chief Financial Officer (CFO) developed. The Chief Operations Officer (COO) is responsible for the operation of the company. In some cases, the COO manages marketing and finance functions as well.  The CIO typically manages the information technology infrastructure part of the business. The CTO is typical for the companies with specific technical products. When data assets are critical or a core competency, the company should have a CDO. Bloomberg and D&B are good examples of companies in which a CDO is required.

With so many different “Chief” positions, what position will be responsible for machine learning technology? Should we start thinking about a Chief Machine Learning Officer or CMLO?

Currently, only a few companies are heavily dependent on machine learning, so in general, it is not necessary to create a dedicated position. However, as machine learning becomes more mature, more companies will move this technology from proof-of-concept shelf to business-as-usual. For example, machine learning is gaining ground in retail for its ability to predict customer buying patterns and to increase renewal rates. Legal companies are starting to explore the possibility of utilizing machine learning to help with document and case classification.

As this trend expands, companies will require more skills to blend data, technology, and business requirements. Someone needs to own this function. The CMLO would facilitate these relationships and advocate for the value of the technology in the enterprise.

Corporations will need to have roles with clear responsibilities for machine learning, although I do not think this role will have the “Chief” title. CMLO is difficult to pronounce and, having four letters, looks different from the other C-level abbreviations. :)

If the role of machine learning continues to expand, however, role might come to have wide acceptance. For the companies that are strategically focused on deriving value from data, the person that is responsible for machine learning will need to have seat at the “Chief” table even if they don’t have the title.