The biggest opportunity for AI is in employee engagement, perhaps even more than [investment] modeling.
One of the biggest challenges in employee engagement is making it relevant. Helping employees make better decisions requires customizing the message to their needs. Right now, that’s hard.
If you think about AI as the mechanism for creating more customized experiences, that could drive higher engagement and ideally better decisions. Even using AI to include a participant’s name in every interaction could create a connection.
Down the line, I can imagine applying AI to create 70-year-old versions of ourselves who tell us what retirement looks like, and how our decisions today can make a difference in the long run.
When I was early in my career, I worked in participant education where I met with employees regularly. I’d ask them to imagine their retirements. I described my own retirement vision — a house with views of the mountain tops and a double-sided fireplace in the center of a great room.
Today, I can imagine an AI-generated version of my 70-year-old self, talking to me about that double-sided fireplace and how contributing $50 more per week would help me get there.
These conversations and interactions could also generate valuable data for the plan sponsor. Imagine if AI could ask, “What’s keeping you up at night?” If most people talked about budget and debt concerns, that data could help plan sponsors respond better to employees’ needs.
Naturally, there would be a lot of data integrity and privacy concerns. But we are many years away from using AI for this kind of engagement. That’s why it’s important to think ahead and get our data in good order so we’re in a strong position to leverage AI effectively when we get there.