Speed, fast-pace, reducing time to execute, efficiency, innovation, change, more time for strategic work and idea generation, portfolio careers, AI agents specialised on certain tasks.
These were some of the main ideas or concepts that were discussed at the I love Tech conference over the weekend.
Speed was mentioned over and over, by a few of the presenters.
However, currently, there are situations where it takes longer to use AI for certain tasks.
Granted, these are the assistant (free or pro) AI.
Ethan Mollick, a professor at the Wharton School of the University of Pennsylvania who studies entrepreneurship, innovation and AI wrote in a recent newsletter about a paper called “Precision Proactivity: Measuring Cognitive Load in Real-World AI-Assisted Work” that had a group of 34 financial professionals do a complex task with GPT-4o and measured their cognitive load.
They had a productivity gain from using AI, but some of that seemed to be offset by AI presenting information in a way that overwhelmed them: walls of text, offers to pursue new topics, and discussions that veered away from the main topic. The people hurt most were less experienced workers.
On top of that, the AI mirrored back the disorganized structure the user provided while the user didn’t reorganize.
Moving from assistants to agents, AI agents seem to be the new hype, with the promise of reducing time spent on certain tasks.
In his newsletter, Ethan mentioned that Claude Code (Anthropic’s coding agent), OpenAI’s Codex and Google’s Antigravity can work for hours autonomously and work well. He points out that these tools are really built for programmers.
In my view tools produce quick answers, but human psychology does not adapt in a split second.
How do we help and support people there?
Not with the carrot and stick method: forcing them to use AI because it’s a requirement for performance reviews, or only those who use AI x% of the time will be promoted.
Rather by explaining:
* why it’s a good idea to use it,
* who it helps,
* how it helps,
* encouraging them to put their curiosity into practice,
* normalising mistakes,
* helping them make the mental transition and decrease resistance, through training, follow up & coaching.
I think companies can have an advantage by implementing better support for how people use these tools and not just focusing on using the tools no matter what.
How much mental effort does it take you to use AI for work?
