Hello,

This is Simon with the latest edition of The Weekly. In these updates, I share key AI related stories from this week's news, list upcoming events, and share any longer form articles posted on the website.

When we read stories and use cases on AI, most include comments about efficiency and productivity gains. The success of these systems is often measured by both the time and money that have been saved. A recent report by Thompson suggests that "professionals using AI will save 5 hours weekly within the next year, up from 4 hours predicted in 2024, unlocking an average of $19,000 in annual value per person". Similarly, a National Bureau of Economic Research study suggests that users saved 26 minutes/day, around 2 weeks a year.

However, it's worth considering the net impact of these gains. With most of us still learning various AI tools and needing to set them up and manage them, there are also hidden costs. And this cost grows as you look at more complex use cases. Admittedly, there's little overhead for someone just using an AI chatbot to help rewrite an email, but if you are building more complete end-to-end workflows with data pipelines, etc, then this requires a much bigger investment. I don't have any stats that summarise the time spent, and it will vary massively, but it's worth taking into account.  

I am starting to see the phrase "AI shepherd" more frequently, which alludes to an individual who has to monitor and govern AI projects. Coupled with more recognised responsibilities like a Data Steward, you realise that it does take a small team to manage production-level AI projects, which, of course, comes with a cost.

How much time have you invested in managing your own AI efforts?

Mastercard is rolling out tools like Agentic Token and Agent Pay to empower AI “agents” to handle tasks like shopping and bill payments, while keeping consumers in control. These secure systems enable traceable, authorised AI transactions.

Why it matters: This demonstrates how everyday services from banking to groceries are evolving to include autonomous AI. It’s worth considering how trust and security are being built into this convenience.

OpenAI CEO Sam Altman predicts that AI will begin doing “workforce” tasks in 2025, automating chores like scheduling or healthcare coordination, and eventually assist in discovery and science.

Why it matters: This insight from a leading voice in AI shows readers that agentic AI isn’t sci‑fi and that it’s coming soon. It might reshape how we organise work and daily life.

BNY Mellon has introduced dozens of AI “digital employees” to handle routine tasks like code checks and payment validation. These could soon engage via email and chat tools.

Why it matters: This highlights how businesses and especially banks, are integrating AI agents into teams, offering a glimpse of what might be coming to our own workplaces.

Thanks for reading, and see you next Friday.

Simon,

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