Excellent post, as always! :) I think AI has forced leaders to really define what it means to have a good product/workflow/team. This definition has to scale across an entire organisation, but also has to go deeper than quantification
Yes i agree - working with AI is not as simple as just using AI, and you need to look at people, workflow, and data as one big moving piece that needs to be transformed together
Thank you for sharing the perspective from these events! I resonated a lot with this quote "So the real value of AI here is counterfactual: its invisible in the short term, but defining over time." I think this is human nature but more profound in finance because the industry is very short-term driven.
In my networking session with AI tech folks in Korea we had a similar discussion. How do you get your organization to adopt AI better and faster? Even for tech people they need to cross the AI rubicon to become a believer and daily user. There are internal discussions about should we transform our organization to be AI-native vs. getting sales for the month. Of course the level of "AI-nativeness" that tech and finance talks about are fundamentally VERY different but all industry is struggling with it
So I think this speaks to the human nature of resisting change and the inability to act for the long-term. Each industry is simply at different places in the AI adoption spectrum and in order to "Move Quick" the industry needs to create a Ah Ha moment to move further along the spectrum. So whoever can does this better will gain an edge over time.
This is a great point - i recently was in SF and had a chance to connect with a lot of tech professionals at the heart of Silicon Valley. Fascinating to see how even in the heart of tech, AI adoption is not happening as fast or effectively as people may have hoped. Again, benchmark is different for what people define as ‘meaningful adoption’ depending on the industry, but it just confirms that every industry is still working its way around growing a pool of AI users and navigating the technical and cultural shift
Excellent post, as always! :) I think AI has forced leaders to really define what it means to have a good product/workflow/team. This definition has to scale across an entire organisation, but also has to go deeper than quantification
Yes i agree - working with AI is not as simple as just using AI, and you need to look at people, workflow, and data as one big moving piece that needs to be transformed together
Thank you for sharing the perspective from these events! I resonated a lot with this quote "So the real value of AI here is counterfactual: its invisible in the short term, but defining over time." I think this is human nature but more profound in finance because the industry is very short-term driven.
In my networking session with AI tech folks in Korea we had a similar discussion. How do you get your organization to adopt AI better and faster? Even for tech people they need to cross the AI rubicon to become a believer and daily user. There are internal discussions about should we transform our organization to be AI-native vs. getting sales for the month. Of course the level of "AI-nativeness" that tech and finance talks about are fundamentally VERY different but all industry is struggling with it
So I think this speaks to the human nature of resisting change and the inability to act for the long-term. Each industry is simply at different places in the AI adoption spectrum and in order to "Move Quick" the industry needs to create a Ah Ha moment to move further along the spectrum. So whoever can does this better will gain an edge over time.
This is a great point - i recently was in SF and had a chance to connect with a lot of tech professionals at the heart of Silicon Valley. Fascinating to see how even in the heart of tech, AI adoption is not happening as fast or effectively as people may have hoped. Again, benchmark is different for what people define as ‘meaningful adoption’ depending on the industry, but it just confirms that every industry is still working its way around growing a pool of AI users and navigating the technical and cultural shift