Explainer
On January 27, 2025, a stock market rout among computer hardware makers, including Micron, AMD, and most notably Nvidia (which lost 17% in a day!) was attributed to DeepSeek-R1, a new model from a mysterious Chinese company. There has since been a lot of (mostly terrible) commentary on the event,
Anthropic
Generative AI can make realistic images, write books, and code websites, but there is a major barrier to using it for business: integration. Businesses use a range of common and bespoke software to do their work – Excel, Salesforce, custom tools, etc. But while generative AI systems exist in the world
Explainer
At AI For Business, we’ve mostly focused on text-based generative AI tools to date. That’s for good reason – most of business is conducted in text, whether it’s reports, tables, charts, numbers, etc. But it’s also because text-based GenAI tools have so far simply been better than
Analysis
Repeat after me: “This is the least capable, most expensive Generative AI landscape we will ever have.” This maxim is core to every future development in AI: every system from here on out will be at least as capable as today’s systems, at least as fast as today’s
Case Study
A central challenge for Generative AI adoption so far has been integration. Most human employees don’t just use the same webpage for all of their work; they read some emails in one program, then consult some information in another, then type their results in a third. GenAI systems today
Analysis
At Apple’s WWDC 2024 event this week, the company unveiled the latest integration of AI into their products. While this “Apple Intelligence” (oof) isn’t going to transform the business world, it paints a unique and intriguing vision about the potential future of generative AI in every day life.
Case Study
So far, the most common business pattern for Generative AI has been “experimental”: choose one or two applications, try some limited and low-cost implementations, assess the results. While there have been some big partnership announcements connected with AI, major commitments have so far been rare. Australia’s CommBank is bucking
AI
I follow a lot of nerd stuff to bring you the best insights on AI for business. Developments like specific chip technology or hardware generations are not things business leaders should have to worry about. Your focus should be the processes and outcomes, not the hairy details of the underlying
Case Study
Customer support is one of the most challenging cost centers in business. It’s a requirement for a positive customer experience, but it’s labour intensive, repetitive, and has historically been resistant to automation. (Especially for business customers, an FAQ just doesn’t cut it.) That’s why customer support
AI
Generative AI can be an incredibly powerful tool with a wide range of applications- taking notes, drafting documents, and providing customer support, just to name a few. But today’s commercial offerings from Google or OpenAI come with a major risk: privacy. To use their services, you must send your
Case Study
I’m always on the lookout for great stories about how real people are using generative AI in their workplace. In two recent articles in the Wall Street Journal, professionals in six different fields, ranging from medicine to law, described their generative AI success stories, how it accelerated their work,
GenAI
It’s only been a year and a half since Generative AI began reshaping the world of business. While many businesses have begun experimenting with it, much of that work to date has been informal – just seeing if the technology works in one application or another, without establishing hard metrics