“What’s Happening?”
This is probably the most often asked question among friends and clients as we try and sort through how this explosion of AI is impacting our daily lives. Microsoft is reporting that 25% of their code is either already written or will be written by AI very soon. They also announced layoffs. Other tech companies are doing the same. Some are related to AI, others not so much directly, but indirectly. Here are some stats generated by GPT-4o.
In May 2024, GitHub (owned by Microsoft) reported that 46% of code in Copilot-enabled environments is now AI-generated.
According to a March 2024 survey from PwC, 40% of companies are already reducing reliance on human customer support due to AI chatbots.
A McKinsey Global Institute report estimates AI could automate 60–70% of total work hours in some industries.
I heard in a meeting that college students are moving away from programming into other fields in anticipation of the impact of AI on their careers. We’re seeing customer support, research, and even consulting hours slashed by at least 90%. So the question then becomes: what happens to those extra hours?
Labor always finds its footing somewhere else. At least that’s been the case for the last hundred years. I’ll be running Hudson Cloud Systems with far fewer people as we grow. AI will replace total hours, and thus people. It means we can wear a few more hats in each role because the time to complete tasks is rapidly decreasing, which is the inverse of typical growth, where everyone wears fewer hats.
As an example, as CEO, it would be common for me to ask someone to research something on my behalf, and it could be in any department, from accounting to R&D to marketing. These individual projects could take weeks, and therefore, sometimes we’d have to add someone or shift responsibilities to get it done. Now the project can be researched and summarized in less than an hour. It means fewer people doing more work, and doing it broadly.
The same reduction in time holds true for our newsletter, customer marketing, and internal analytical debates. We use LLMs (Large Language Models) to fact-check and sharpen our arguments. We know it’s allowed us to be more productive in other areas. Even now, as I write this, once I’m done, I let GPT-4o correct it for spelling, grammar, and punctuation, which includes word usage. It cuts my editing time to nothing. I then spend that time doing other things. It’s usually research-related or planning for HCS growth.
We see a more profitable future while other companies are terrified of what this will do to them. We see all of this as a huge opportunity, while others see it as a potential threat, just as they did with the PC when it first came out and everyone claimed it would be a job killer. I actually think this is an exciting time, and I’m having fun with the constant change. I’m confident it will lead to great things still unimagined.