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Draw talent into your problems

A common refrain for many organizations, and government organizations, in particular, is that building an AI-ready workforce is particularly challenging because it is impossible to match the salaries offered by large, private-sector companies such as Amazon, Google, and Microsoft. Salary discrepancies between industry and government are unlikely to change any time soon, however. 

Many individuals choose meaningful work over a larger salary.

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Organizations today are often faced with a challenge: How do we move forward even if we don’t have all of the answers yet? A data engineer can have an impact across the application, from application performance to the semantics and meaning of the data flowing across the system.

AI technologies are evolving so quickly that any specific requirements might soon be overcome by advancement. For that reason, organizations looking to adopt AI need to grow a culture of learning. On the hiring side, that also means looking for people with a sense of curiosity. 

Organizations also need to focus on helping existing employees learn how to learn. The expectation cannot be that everyone will be able to easily add learning on top of days filled with back-to-back meetings and never-ending lists for deliverables. Organization leaders have to think about ways th...

To help individuals learn how to learn, managers can ask themselves the following questions:

Organizations today are working to assemble teams that can make bespoke pieces of AI, leverage them towards specific outcomes, and endlessly tune system components to arrive at assured AI systems, able to be deployed in a variety of different environments. 

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