Scroll down for the list of machine learning influencers (ML influencers).

Many “non-technologists” use machine learning and artificial intelligence synonymously. While they are related, it’s not the same. Below is a graphic 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.

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

The 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 who are tech sector and industry leaders. Here’s a Twitter list if you’d like to follow the conversation.

Many technology influencer lists are floating out there on the internet. Depending on how you measure influence or your objectives, this list will be an excellent 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

Take a look at these B2B social media marketing best practices. It’s a guide that will  help you use data and document the right plan to grow your business on social media.

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