Scroll down for the list of machine learning influencers based on several data points and influencer analytics.

Many “non-technologists” use machine learning and artificial intelligence synonymously. While they are related, it’s not the same. Below is graphic that I found on Edurica that illustrates how machine learning is a subset technology of AI.

The most common way to measure influence is to combine reach, relevance and resonance, and then a layer in a weighted algorithm to stack rank each one.

This is definitely a good start but there’s an additional data point that must be considered to maintain the integrity of real influence. I refer to it as reference.

Reference requires a manual lookup and cross reference of 3rd party mentions by a particular group. This could be the media, analyst reports or social mentions by a specific audience like c-suite executives, commercial real-estate agents or software engineers.

Below is a carefully curated list of machine learning influencers that are industry leaders in the tech sector. Here’s a Twitter list in case you’d like to follow the conversation.

There are many technology influencer lists floating out there on the internet. Depending on how you measure influence or your objectives, this list will be a good start to understanding the machine learning landscape.

At the bare minimum, you should be listening to this group of influencers so that you can get a clear understanding of the context of their conversation. This is the first steps of preparing for an organic influencer marketing program.

Here are a few other influencer lists in case you are interested:

• AI Influencers
• Data Science Influencers
• Blockchain Influencers
• IoT Influencers
• 5G Influencers
• Digital Transformation Influencers
• Clubhouse Influencers

I talk a lot about managing and deploying influencer marketing programs on my YouTube channel and it’s not just theory or ideas. It’s all based on real life experience, testing and learning, and sometimes failing. Please subscribe.