For a company to become an AI-first organization, it must first go through a transformation journey and become data-driven. Most organizations have started by exploring and testing what benefits they can achieve by data and analytics; then moved on to more mature states where a dedicated Data Team is formed, possibly under a CDO; then moved to democratizing data and making it available through self-service to everyone (qualified) in the organization, to use as part of their BAU. That is the point in time, most organizations start (or should start) exploring AI.

As AI needs data as fuel, it only makes sense that these two functions (Data and AI) are located close together within the org chart. To take this a step further, while AI usage is in its own exploration phase, it would make sense for AI to be part of the Data function as well. So at least in the beginning, we should be talking about a Data & AI Team.

As this Data & AI Team matures over time and has produced a solid Data Strategy, the balance within the team will change from having Data Engineers as the majority to having Data Scientists, ML Researchers, and Engineers as the majority.

Once the organization has reached the state of data democratization, then it should shift to a more agile structure, where AI roles from the Data & AI team will be rolled into the various product/service teams, operational teams, and so on, to deliver their expertise as part of a team with end-to-end responsibility. However, all this Data & AI talent that is allocated to product and/or service teams still needs to operate as a coherent unit to continue maintaining the Data & AI strategy. A role such as the Chief Data Officer/Chief AI Officer can ensure this.

So, a conclusion one can make at this point is that to help the data maturity process, an organization will need to set up a team of experts, the ‘Data Team’ with the CDO as their head and have the ‘AI Team’ grow within this structure. The CDO will also have the AI leadership. This team will drive the organization to a maturity level, where every employee will be able to use data and insights for BAU, in self-service mode.
From that point on, the ‘Data & AI Team’ will blend with every product or operational team needed. Does this mean that the Data & AI Team is a temporary organizational structure? Well, the same way that a Chief Digital Transformation Officer is temporary in nature, though active for years (but because of continuous change ends up being a never-ending journey). The Data & AI Team will gradually grow, reach a peak, and then fused into the organization as discussed, but will continue to function as a virtual team.

OK. So where does this function report to? It is best placed somewhere within the organization whose role is horizontal and serves the entire business, to avoid limiting value creation to one specific business domain (e.g., marketing). Therefore, the Chief Data & AI Officer is best placed either under the COO or the Chief Digital Transformation Officer or under the CIO/CTO. This immediately places the role at -2 or -3 from the CEO. It can even be lower or higher depending on the state of the organization in terms of their journey to become data-driven, it also depends on the organization’s culture and so on.

PS. IMHO, there is a tendency to have all these new roles (CDTO, CDO, CAIO, and so on) outside the domain of the IT function. To me, this shows a lack of faith that the organization has towards its IT capabilities. A ‘Digital-Era’ CIO, should deliver on the ‘I’ in their title. It stands for Information, which is based on data. A ‘Digital-Era’ CIO should act as a catalyst for change, should bring technology to the core of the business by democratizing data analytics and AI, and drive Digital Transformation Initiatives. If an organization does not have such a person holding the CIO position, perhaps it should re-evaluate the position entirely, and call it something like IT Operations Director, placing IT under the COO, and so on.