By the end of 2026, the average person will spend more meaningful conversational time with AI than with any single human in their life.
This prediction, made in a recent Thomson Reuters article on AI, caused me to ask,
“What does it mean to stay human while using AI?
That is the question I will explore in this Substack. I’ll weave together research, real-world examples, and leadership insights with perspectives from AI-native companies and leaders across HR, Talent, and Technology.
My focus will be on the human side of AI: the fears, barriers, resistance, and false starts people experience as they learn to work with AI and, importantly, the strategies leaders and organizations can use to overcome them.
Ultimately, I’ll explore how we can nurture and grow the human capabilities of judgment, curiosity, creativity, empathy, and critical analysis in an AI-powered workplace.
My Substack posts will explore a range of issues such as:
AI Literacy as an Expectation for Employment: University of Phoenix reports that 73% of C-Suite leaders are mandating AI literacy. And 69% and 69% expect to embed AI literacy into performance management by the end of 2026. How is AI literacy defined and how to hire for this?
AI Gender Gap: Lean In research finds women are 32% more likely than men to worry they would be seen as cheating for using AI at work. What can be done about this so woman are not left behind?
AI Age Gap: University of Phoenix finds the younger the leader, the less hopeful they are about the impact of AI in the workplace. While 75% of Baby Boomer leaders report feeling hopeful about AI’s impact, that figure falls to 59% among Gen X leaders and just 47% among Millennial leaders. Does this age gap persist across industries and job roles?
New AI Jobs: EY is hiring a new Head of Agent Economics, as the firm examines if their AI spending is delivering concrete business benefits. The new executive will lead EY’s AI value realization office. What other new jobs will be created as companies increase their AI investment?
AI and the Ever Expanding Job: Recent research from HBR finds AI does not reduce work, it intensifies it. This can result in expanding workloads, cognitive fatigue, burnout and at times lower quality of work. What can leaders do to help employees integrate AI into their workflow without increasing burnout, and work creep?
One More Thing:
AI and Compensation: Humans are starting to ask if I just manage a team of agents, will I still need to manage humans to get visibility and access to promotions? How will compensation evolve as managers manage agent only teams and hybrid teams of agents and humans?