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  • Writer's picturePaul Baier

Question #6. How Should I Organize to Grow and Scale My GAI Capabilities?

Talent and data, not powerful Gen AI tools, are the scarcity.


One thing is for sure, we know that there will be a scarcity of AI and GenAI talent for the foreseeable future. McKinsey recently released a report on the future of AI in the workforce, estimating that 12M people will change careers.


US-based generative GenAI job postings were up 20% in May. Searches for generative AI jobs jumped to 147 per million total jobs searched in May, from virtually zero a year earlier.




Savvy job-seekers in all industries know that investing the time to increase their skillsin GenAI will give them a career rocket, and incorporating GenAI into their business tasks will pay off both in short-term efficiencies and long-term career advancement.


Given this rapid movement looming in the job pool, one of your first steps is to focus on your internal talent pool. Here, I recommend 7 recommendations for retaining your top talent.


In addition to talent, we know that there is a massive need for reliable, quality data for inputs that the AI can learn from– and leveraging a company’s proprietary knowledgeis critical to its ability to compete and innovate.


As you think about organizing to grow and scale your GAI capabilities, both talent and data reliability have massive implications for how you organize your GAI efforts.


This effort to scale must serve two masters: one is the efficient creation of data, insights and actions – often called an insight factory. This is an apt label, as scaling insights across organizations often calls for investments in data, people and processes that go beyond one project. In addition, there’s a need to support teams doing breakthrough, innovative work. An innovation platform provides common data, processes and procedures with room to maneuver as your teams explore value-creating ideas. This latter is more prevalent in R&D organizations.


Need to know more?


Our Generative AI 2023 Bootcamp will go in-depth on the topics of talent and data sourcing in a number of sessions:

  • Professor David Edelman from Harvard Business School, and former CMO at Aetna/CVS will detail how to create a scalable set of actionable insights within organizations.

  • Dan Elton of Massachusetts General Hospital will discuss how they transformed MGH at scale

  • Joe Atkinson, Vice Chairman of PwC will lay out how both how they are using GAI within the $50B PwC organization and how they help their large clients scale.

One of the main reasons we decided to put together this event is to help the business community get off the mark quickly and in the right direction. We are excited about the coming business transformation, and are proud to be on the forefront of efforts to do it right the first time.


This is the 6th segment in our series of common questions executives ask about GenAI. The first 5 are:



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