Part I - Why do large enterprises need a Chief AI Officer?

Why do large enterprises need a Chief AI Officer

The Problem statement - Gap in the org design

In 2024 - I don’t believe we need to still make a case for committing to leverage AI and I say that in an overarching terms for both predictive and generative AI. Having worked with various enterprises in the last few years - this is what I saw - departments where this emerging capability tried to find home

  • Innovation Labs
  • Shadow AI projects
  • Business sponsor + external vendor (insert SI, ISV, Saas - you name it)

and the problem with this approach is - when there is a platform shift of this nature and size - creating value from it requires a significant level of cross collaboration. Each key office/individual of of influence has something to add.

  • Business Unit Leaders - All of them have a detailed understanding of their business process and workflows
  • Technology Leaders - have the tech wherewith to adopt and fast track implementation
  • Partners - Providers of staff of augmentation, development accelerators, turn key solutions via ISVs, SaaS
  • CXOs - (re)imagine the business once they understand the art of possible with emerging technology

However - with the patterns I described at the start - this value is lost or diluted at best if there isn’t a forcing function stitching it all together, delivering/measuring actual value unlocked.

Turns out as I was thinking about this idea - I found out that there was plenty already written about the role - but in all the posts I found that it was written from the angle of a job spec. However - I feel it misses the point For the role to be successful or for CXOs to see the value of the role a deeper dive of areas of partnership and alignment is required.

Where does the Chief AI Officer fit in?


The CEO and COO are critical to setting the direction and running the day to day operations of the business. They have the uber view of strategic initiatives across the company and are critical “end customers” for the role. The CAIO can work with them on the following focus areas:

Organisational Alignment

Sitting in the various steering meetings the CAIO can bring in insights on how some of the goals could be delivered in a market differentiating way (insert cheaper, better, faster - whatever works best for the business). The CAIO can then also use this opportunity to be “air traffic controller” for various AI lead interventions to ensure that a capability created for one of the initiative is leveraged elsewhere reducing the overall investments.

Often organisational/business unit’s objectives that when not pursed in tandem can have a negative impact. Imagine a retailer - who has an initiative to improve recommendations to increase top line - while the logistics team is trying to reduce time to delivery / scale for increasing demand. If the first one succeeds it puts pressure on other initiative - either adding to the delivery costs, delays, loss of customer satisfaction or alt. the second team implements efficient logistics but no where near the size of orders coming through - to justify the overall investment

Often a CAIO can be the voice of reason to look at these initiatives through the customer journey / end to end process which business owners for a specific function tend to miss.

Bridge technical and business requirements

Often solved via setting up of COEs (and I seen enough cloud and AI COEs that solve that in parts but mostly end up being a push model rather than a pull mode due to lack of a central owner with an exective sponsorship). A successful AI Implementation requires this critical aspect of bridging the technical and business requirements - as not all organisations have a product team - traditional organsations like banking for instance have functional production owners - who own a business process alone but not always own their end customers experience - typically managed by the CDO instead. This also includes the much needed “change management” for adoption of the new AI enabled process which is often left to the IT team resulting in poor adoption or an incomplete feedback loop.

Ensure ethical and Responsible AI deployment

Taking a local view of a project (inside a business unit or a function e.g. engineering) often misses the wider impact the project can have. Sitting on the outside - this role can make an outsized impact by defining what is “ethical and responsible” in alignment to the prevailing laws, company’s vision and mission statement.

A google for example - the AI review process is widely written about including on the company blog . The CAIO in the organization can setup an office to ensure these reviews are done independently, fairly and at speed to ensure it does’t stifle time to market or an oppty cost.

Secure Exec Sponsorship via Advocacy

This aspect is so critical and often an afterthought. I have seen several projects that don’t live beyond the initial round of capex funding. This is often because the initiating BU gets really busy with the delivery and implementation. with no one advocating the progress, accomplishments and blockers to the sponsors. This goes beyond status updates - which is what often they are relegated too but when done well involve:

  • Continued engagement with industry thought leaders, peers to bring in fresh thinking around the impact of the AI Initiative
  • Often work with multiple functions like IT infrastructure, finance, product owners to come up with the “real/net” value delivered - this helps weed out the vanity projects from the ones that make a real net impact to the business
  • Create a framework/model to represent impact to then be replicated at scale across the company
  • Also on the tactical front a few other ideas that that the CAIO can do on the ground
    • e.g. understand the key priorities of the sponsors and ensure the narrative of the impact is aligned
    • identify allies, testimonials, early wins and share them widely
    • build wider network of relationships in the organization to feed into future opportunities

CTO - Develop and execute AI Roadmap

This partnership when done well will ensure de-duplication and acceleration of adoption. A couple of ideas for partnership

  • AI Project selection framework - The CAIO can help put together a project selection framework with the CTO using the wider lense of company vision, local laws, policy, data strategy.
  • AI Technology choices - Given the CTO is responsible for running the tech stack and also the future of the technology roadmap - AI being one of them - the CAIO can take on the AI specific aspects of technology choices to ensure that CTO has the bandwidth to continue doing the current role and benefit with the aide. Some of these areas could be
    • Enterprise architecture approach to AI
    • Evaluation of Tools / Frameworks and ISV/SaaS providers
    • and; talent acquisition and training specific to AI roles and skills

CISO - Governance and Security

Often I hear CISOs going through a refresher on what the potentials are with AI. Sadly its often left to one/few training sessions or the CISOs own interest in this area. Eitherways its a very subjective approach to ensure that the CISO can make an informed decision about supporting an AI initiative. Leaving this as a gaping hole, a missed opportunity. The CAIO can partner with the CISO to ensure they can be educated “in-context” with new skills and capabilities that would be required to unlock value of such a significant platform shift. Often in its absence the AI project sponsors are left skirting around the edges where they do deliver something of value but often far less than what would be needed to make the organisation market differentiating.

CHRO - Influence Talent Acquisition / Retention Strategy

Often this function works in a pull mechanism - esp. when there is a paradigm shift happening in a different functional area. They end up “consulting” “experts” in the organisation on what needs doing tactically in the organisation to support this. Having a well defined collaboration strategy will benefit both in

  • Identifying, attracting talent to fuel various AI initiatives; but also
  • define and execute a plan to “build experts from within” - strengthening retention strategy

While this list could be a lot longer, this is such a new opportunity that it can pretty much be what it needs to be as the enabler and accelerator of technology adoption in the organisation. In my follow up post this - I will also cover some of the success metrics to measure the impact of this role.

Are you doing a similar role in the org or feel this is limited to only “very large” organisations? I would love to know more about your thoughts on this.

Photo by Scott Graham on Unsplash