Does your organization need a Chief Generative AI Officer? Pt. I – What moves should the TTO make right now

This is Part I of a 4-part series. For a comprehensive understanding, read the full whitepaper here.


We speak to a lot of Top Technology Officers (TTO = CIO, CDO CTO etc.), and all have pressure from their CEO, Board, Vendors, Peers, and many others to articulate how their organization is taking advantage of GenAI. All the major consulting firms are hyping this – it feels a lot like the Chief Digital Officer wave that hit about 10 years ago.

Here are our observations on what the best TTOs are doing about GenAI.

First a bit of context. Many organizations have been using AI for some time and may have Chief Data Officers who have responsibility for corralling data (Data Engineering), Governing Data (MDM, Dictionary, Quality etc.) and delivering Value (both cost management as well as finding new revenue streams). But mostly they have been focused on structured data from both internal and external sources.

GenAI has, however, created new opportunities that enhance the utilization of structured data, but more importantly unstructured data, and the deep learning algorithms/foundation models that GenAI is spawning. GenAI is using data, images, sound etc. to “generate” the “next logical word/step/idea/sound etc.” as prompted by the user.


What moves should the TTO make right now

1. Put someone in charge. You are either going to drive this – or be driven. You may want to start with a Chief Data Officer, but if you have someone already focused on Data, then you probably need a Chief (Generative) AI Officer (CAIO/CGAIO).

2. The CAIO/CGAIO leader could be someone from Technology (or tech-oriented business leader), but also include a business leader (technologist), (and perhaps Product, UX, HR (3 or 4 in a box) as part of the team.

3. The CAIO/CGAIO leader should put together a governing committee that comprises: Business/Operations, HR, Legal, Compliance, Security, Technology/Data Officer, Finance. Why so many – because (Gen)AI has the capacity to change the way you deliver your product/service, your product roadmap, and perhaps your entire business model.

4. Articulate guard rails – that protect your data, reputation etc. (Hallucination is a feature – not a bug)

5. Define some immediate value scenarios – the most popular at present being – Development Copilots, Call center/helpdesk enhancements, (Gen)AI driven RPA, cost containment in manufacturing, supply chains, ideation, knowledge management etc.

6. Your (Gen)AI leader must understand the ecosystem in which your organization operates if s/he is to move at the speed required, and the ecosystems can be very different depending on your industry.


Author: Tony Leng

Please feel free to contact Tony Leng directly via email should you have any questions or would like to discuss the above or anything else further.


This is Part I of a 4-part series. For a comprehensive understanding, read the full whitepaper here.