AI, HR and Learning
After a two month hiatus I am back to blogging. Below I am sharing what was top of mind for me this week in AI and HR.
The Future of AI
Don't be fooled by the magnificent seven's depressed stock prices this week—AI is still coming in a really big way. I do think we're in a place now similar to when the iPhone became big. Perhaps people don't quite know what to do with it, but the potential is going to create companies and move markets in a massive way. Anecdotally, I recently took a Waymo ride. Just a few years ago, people were saying that's not happening, etc., and now I can say that it is flawless and better than taking an Uber Black car. The ride was smooth, the tech seamless, and the experience felt like a glimpse into a future where autonomous systems are the norm.
This isn't just about self-driving cars. AI is poised to disrupt industries in ways we can barely predict. Think about the early days of the iPhone—people were excited, but no one could have foreseen the app economy, the gig economy, or the social media revolution. We're at that same inflection point with AI, and the people that figure out how to harness its potential will dominate the next decade. Investors might be skittish now, but the long game is clear: AI is the future, and it’s coming faster than most people realize.
HR Leadership's Future in AI
I continue to forecast a future where there will be a convergence of HR departments and IT departments. As AI becomes more integrated into workflows, the line between managing people and managing technology blurs. HR will no longer just be about hiring, firing, and employee engagement—it will be about ensuring that employees have the right technological tools to thrive in an AI-driven world. IT, meanwhile, will need to understand human behavior and organizational dynamics to implement systems that enhance productivity without alienating workers. This convergence is inevitable, and the organizations that embrace it will have a competitive edge.
IT departments are acting as HR departments for AI agents. Back in December, I hypothesized a future where a new job would emerge—the Chief Autonomy Officer. The idea being, companies need an accountability point to ensure people have all the right tools to be successful with AI and also ensure that management is providing the most autonomous and entrepreneurial environment possible. This role would bridge the gap between human potential and technological capability, ensuring that employees are empowered to innovate while AI handles the grunt work. Imagine a leader whose sole mission is to maximize freedom, creativity, and efficiency.
SaaS & AI
I think SaaS (Software as a Service) is going to be totally disrupted by upstart AI companies. Traditional SaaS platforms—think CRMs, project management tools, and HR software—rely on static workflows and user inputs. But AI is dynamic, learning, and adaptive. Why use a SaaS platform that requires you to manually input data when an AI-powered alternative can predict your needs, automate repetitive tasks, and provide real-time insights?
For example, consider a HRIS system (like Workday). A traditional HRIS requires administrators and users to log entries manually, configure reports inside the system, etc. I was recently at a conference where someone demonstrated that their company has used Microsoft Copilot to take the request from the end user (employee) and execute it in the HRIS on their behalf. Not only does it do this but it does it via the users preferred communication platform (in this case Microsoft Teams).
This much more user friendly, and efficient way of executing business processes is bound to disintermediate SaaS companies. They’ll be faced with an innovator's dilemma. In the example below you can see how the moat of Workday is becoming eroded by Copilot. Which could eventually lead to obsolescence.
Kids Learning Software & AI
I was teaching my kids how to use Turtle in Python, thinking I was giving them a leg up in the tech world. Then, coincidentally, the next day I saw an article on teaching kids—China is teaching 6-year-olds how to use AI. The article highlights how countries like Estonia and South Korea are also integrating AI into their curricula, while the U.S. and U.K. lag behind. This isn’t just about staying competitive—it’s about ensuring our kids aren’t left behind in a world where AI will be as fundamental as reading and writing.
The conclusion I’ve drawn is that I should also be doing this. Coding is will still be important, but AI literacy is the next frontier. If kids in China are learning how to interact with AI models, prompt engineer, and even build simple AI tools at age 6, we need to step up our game in the West.
I’m now exploring tools like Scratch for AI or even simplified versions of platforms like Hugging Face to teach my kids the basics of machine learning. If you have kids, I encourage you to do the same. The future belongs to those who can wield AI, not just code.
Performance Management Reform & AI’s Role
Remember when people were saying that no one should have performance ratings in the workplace and performance should just be a conversation? Nothing against them, but I feel like that has proven to be a fad. Conversations are necessary, but without structure, they can devolve into subjectivity, bias, and inconsistency. Performance management needs to be data-driven, transparent, and aligned with organizational goals. The pendulum swung too far toward "touchy-feely" HR, and now it’s time to bring back rigor—but in a smarter, more relevant way.
With all the Department of Government Efficiency (DOGE) talk, I feel performance management should be a BIGGER topic than compensation. In government and private sectors alike, performance management is often an afterthought, overshadowed by debates about pay and benefits. But here’s the thing: if you get performance management right, compensation becomes easier to justify, and efficiency skyrockets. Imagine a world where every employee—public or private sector—has logical, justifiable, clear goals, real-time feedback, and a consensus on how they can drive the most impact. That’s the future we should be aiming for.
Currently, it is too hard to understand how companies (and government employers) performance manage from both the inside and the outside. Job seekers have no idea how they’ll be evaluated, employees often feel blindsided by annual reviews, and management / boards lack visibility into their own companies. We need a radical rethink—perhaps even a "Department of People Efficiency" (DOPE)? This could be a centralized effort to standardize, modernize, and digitize performance management across sectors. AI could play a huge role here, making processes more visible, suggesting improvements on metrics, timetables, identifying patterns, and suggesting interventions. The future of performance management is about getting it right at scale and I expect innovation here.