The role of a Chief Automation Officer (CAO) for businesses was first espoused a few years ago as reporters, analysts, and automation vendors started to see the growing burden on the CIO and the need for more IT executive leadership positions.
Digital Innovation Drives Heavier
According to Gartner research, digital revenue is expected to double in the next five years, reaching its tipping point in 2019. As businesses increasingly adopt digital practices, CEOs are relying more heavily on CIOs and CTOs, but not in the same way they have in the past.
Traditionally, CEOs have depended on CIOs to manage all of the businesses’ IT needs- ensuring the proper infrastructure is in place, overseeing that hardware/software solutions meet business objectives, and providing general technical guidance. However, as businesses start embracing digital practices, CEOs are relying heavily on CIOs and IT to drive this digital innovation AND keep performing their traditional responsibilities.
The problem with this approach is that there’s just not enough time and resources for the CIO to lead the path to digital innovation and manage traditional IT needs. The CIO can’t plan the businesses’ digital innovation if he’s weighed down with operational day to day challenges that constantly come up.
In fact, one complaint we here often from CIOs at industry conferences is that they feel they spend too much time on tactical execution and are stuck in a cycle of planning one project a time, rather than acting as a strategic partner to the CEO.
So Where Exactly Does the CAO Come In?
The Chief Automation Officer oversees enterprise automation as a whole, building the pathways to support the automation of business and IT Processes. This lets the CIO focus on developing new processes and implementing new strategies while the CAO underpins this innovation with the necessary automation to make it as smooth, quick, and reliable as possible.
As a result, instead of developing a process and automating it later, automation comes first in the development and design of a project. Personnel time is better spent, repetitive work is automated, and departments have a much more orchestrated approach to automation.
But as a quick search on LinkedIn revealed, widespread adoption of Chief Automation Officer positions isn’t a reality yet.
As the roles and responsibilities of CIOs have grown tremendously over the past decade, we’ve seen more C-level titles crop up, from Chief Data Officer and Chief Security Officer to Chief Cloud Officer, but the role of Chief Automation Officer hasn’t experienced the same level of acceptance.
Predicting the Rise of the CIO
One reason for this is that organizations often take an elemental approach to automation- meaning they automate project by project or application by application, without any holistic view of the entire organization.
Oftentimes we see individuals or teams devoted to IT Process automation or runbook automation or DevOps automation, without any organization-wide strategy with insight into the other team’s implementation, challenges, or successes. This leaves a lot of opportunity on the table as there may be overlap between different automation solutions and strategies within the organization, but there’s no central unifying person to tie it all together.
The good news is that we are seeing an increase in the number of automation-specific positions with titles such as ActiveBatch Administrator or enterprise automation architects. These positions, while not C-suite, are heavily focused on bridging the gaps between business processes and IT on an enterprise scale.
While widespread hiring of CAOs is not a reality today, it doesn’t appear to be too far off. With recent examples of outages due to automation breakdowns making the headlines, as well as the growing complexity of IT Operations, the need for an individual or centralized team that can deliver automation engineered from the top is growing.
Intelligent Automation & Enterprise AI Governance
Deploying advanced cognitive automation and intelligent algorithmic systems across enterprise operations demands a disciplined equilibrium between automated efficiency and institutional accountability across every departmental touchpoint. Organizations advancing automation maturity must first establish the integrity, security, and traceability of underlying operational data pipelines before deploying autonomous execution engines into mission-critical workflows. Instituting explicit ethical guidelines, human-in-the-loop exception checkpoints, and granular audit logging frameworks ensures automated system outputs remain thoroughly transparent, verifiable, and compliant with evolving international regulatory mandates. Without standardized data engineering foundations, automation initiatives inevitably risk accelerating legacy operational inconsistencies across interconnected business units.
Sustainable automation scale demands a centralized center of excellence that seamlessly integrates systems engineering with frontline business domain expertise throughout project lifecycles. By maintaining continuous visibility into cycle times, operational throughput, and process exception rates, management teams can systematically prioritize high-value business processes for iterative architectural optimization. Concurrently investing in human-centric change enablement and structured workforce upskilling empowers personnel to transition from mechanical administrative routines to high-impact strategic advisory responsibilities. This collaborative operating philosophy ensures enterprise automation delivers sustainable productivity gains, enhanced auditability, and measurable competitive differentiation.
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