Ketaki Sodhi, PhD

ChatGPT's Code Interpreter/ Advanced Data Analysis is a great way to access code and run complex analyses. More recently, the Copilot in Excel has been exceptional as a data and viz companion.

An advantage of current GenAI technology is being able to create complex, personalized simulations. Use those to create a custom tutor or similar assessment that allows you to practice and get real time feedback.

Digital literary means so many different things today. With the pace at with tech is evolving, advanced topics today can be mundane, general knowledge tomorrow. With that in mind, it is critical to start by understanding where people currently are and right-sizing your literacy efforts to meet them where they are. This is a goldilocks problem - too basic and you'll lose people, too advanced and you'll lose people. Having a systematic (and ideally adaptive) way to assess or figure out where your target is and using that data to target content is the best way to meet people where they are.

Start with a job or team analysis to figure out what are the core knowledge, skills, abilities required. If you have talent management or IO psychologists at your company, they are well equity to help! Using this, consider the best ways to assess specific skills - technical ones might be more straightforward; while non technical skills can be assessed by triangulating different sources of information like surveys, written feedback, reviews, etc.

Managing the change is as much about the technology as it is about the people. Focusing on building the right capabilities, culture, and conditions in addition to data, infrastructure, and use cases can ensure you get the most business value from leaning into AI.

With the rapid development of AI agents, we can delegate draining tasks to AI and not other humans. It unlock the ability to focus on energizing and/ or important tasks while having an AI system handle the draining, admin tasks. This type of job redesign has huge implications for worker wellbeing!