Does your organization need a Chief Generative AI Officer? Pt. II – Ecosytem & Next Steps

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

Your Ecosystem

If you track the VC’s they are investing heavily into GenAI and there are multiple themes. Examples:

  • Full Stack (end user apps with proprietary models).
  • End Apps without proprietary models focused on: Sales and Marketing, Customer Support, Engineering, Design/Collaboration, Data Science, Enterprise Search, Speech and Video.
  • Infrastructure Tooling – platform and tooling used to build, test deploy and monitor Apps. Then there are the Proprietary Models (OpenAI, Anthropic, Cohere etc.), Open Source Models, and Model Hubs (Hugging Face, baseten).


But your traditional vendors (SAP, Workday, Salesforce – and most others) are offering GenAI capabilities as part of their product set. Microsoft, Google, and Amazon are also developing significant offerings, and if you are a Microsoft shop, step one is probably to understand what they can do for you (while protecting your data etc.)

There are only a few organizations that can attract GenAI talent and have the budget to build their own Foundation Models – so most will leverage what the market/ecosystem offers.


Your GenAI leader thus needs to understand your business, and the market, so that s/he can leverage the ecosystem and work toward value adding decisions that positively affect the company.


What are your next steps

  • Appoint a leader. This person can be a Chief Data Officer, a CAIO, CGAIO, tech-oriented Business Leader or some derivative of that.
  • Ensure that a Governance Committee is instituted for GenAI. Responsible AI is an imperative. RAI should always include topics like transparency, explainability, interpretability, IP risk management, liability and compliance, Information security and privacy. Simply put – define guardrails for your GenAI initiatives.
  • Start well defined quick win initiatives, but also focus on the long-term impacts that GenAI can have and plan for the medium and long term impacts on staff, business models etc.
  • Start education and training programs for staff on GenAI.
  • Modernize your Data Platform if not already in process. No matter your size, your data is an important ingredient in any GenAI initiative and needs to be managed effectively.


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 II of a 4-part series. For a comprehensive understanding, read the full whitepaper here.