According to IDC, spending on Generative AI solutions will double in 2024 and grow to $151.1 Billion by 2027
In other words, if you’re not already involved in some kind of AI pilot/implementation/POC, etc., project - you will be, by 2027 latest.
Now, the trouble is, many organizations stumble when introducing AI. Often, it's either a top-down mandate ("We need AI, because everyone else has it!") or a bottom-up techie crusade (“We need to have AI because it’s fun!”). Both approaches lack a crucial ingredient: understanding the business value and specific needs.
Here's the key to giving your AI initiative a fighting chance: get everyone on the same page. That means the executives and sponsors, the marketing folks and business owners, AND the IT/Tech crew. They all need to speak the same language and understand each other's perspectives.
Many companies try to solve this with generic AI training for everyone involved. These courses, however, are usually too technical for business folks and not deep enough for techies. In many cases - a waste of time.
Instead, let each group dive deep into their specific roles while simultaneously gaining a basic understanding of key AI concepts and shared terminology.
And the good news? I've got some top AI resource recommendations for each group, coming right up...
For CMOs / C-level executives
Google’s Generative AI Primer for Executives, especially the associated presentation
You’ll find everything that corporate managers love:
For Marketing Professionals / Loyalty Managers
First, start with an oldie, but goldie AI for Everyone by Andrew Ng.
Honestly, I’ve recommended this course to probably over a hundred people from all sorts of backgrounds, including roles in Loyalty/Digital Marketing, E-commerce & CRM Managers, Product Managers, Analysts, and so on over the last couple of years. Every single time, I’ve heard what an eye-opener it was. It really takes everyone from the buzzword level to having a really good general understanding of what AI is and can be (or cannot be) used for and what to expect from the tech teams delivering these solutions.
A very good extension to AI for Everyone focusing on Generative AI, which is on everyone's minds nowadays, are these two courses:
The first one is also Andrew's creation, and the other one is a comprehensive course by Google if you’d like to hear someone else’s voice after going through the first one.
For IT, Software Engineering Managers and Developers
Alright, now for all the techies out there rightfully tempering the marketing hype around AI, here's something for you:
Stanford CS 329S: Machine Learning Systems Design
This course is not yet another tutorial where you'll be building another neural net classifying an MNIST dataset, but instead a very practical set of materials covering what it actually takes to build and run AI & ML systems in production. Because just like any other system - running it locally or for testing is one thing, but making it work at scale, monitoring quality, integrating with other systems is a whole different story (different also to what most know so far from running and developing non-AI systems). One of my best finds of last year, for sure.
Lastly, if you’re just looking for some cool ideas for a side-project you can watch a video of 24 demos of the 2022 Stanford Students who were actually taking this course as part of their degrees.
