The AI Ops Job Landscape

Welcome to another edition of the best damn newsletter in AI. Here we’ll break down AI topics that matter, open your mind to use cases, and keep you ahead of the curve.

Our #1 goal is to be useful. So please shoot us an email 📩 if you have questions or feedback, and especially if you implement something we share!

Here's what we're covering today:

• An overview of the AI Ops Jobs landscape, and where we think it’s heading

• Supercharge your customer research with this use case

• AI-related data scraping is coming under negative light

Let’s get to it! 👇

TODAY'S PERSPECTIVE

The AI Ops Jobs Landscape

Every executive will have a perfect and real-time assistant. Teams will have perfect memory of past projects and learnings to tackle new initiatives with hard-earned tribal knowledge every time. Individuals will have personalized mentors and be able to learn anything just by asking.

We’re not there yet, but this is what is unfolding.

The implementation of AI is hard to keep up with. But today we’re going to break down what we’re seeing.

Generative AI-related job postings were up 20% in May based on Indeed.com data. Most of the roles being classified as generative AI-related are currently AI Engineer. There are also of course Machine Learning Engineers, and another emerging group of LLM Engineers - both of whom build and train AI models from scratch.

But beyond those roles, a messier category is emerging: business and operational roles with a requirement to be “familiar with AI”.

Peruse job boards for roles in marketing, recruiting, sales, project management, etc. and you’ll quickly see - businesses and hiring managers know they’d be better off hiring with this skillset. But what are they looking for?

From our research, it’s messy. Common themes are a mix of automation experience, ChatGPT experience, and savviness with the latest AI tools. But it’s still so new that very rarely are employers specific enough for you to go build up a portfolio or skillset against. At least, not yet.

Another trend is the rush of talent towards AI Product > AI Operations

This makes sense. It’s often sexier to build something new, or sell a new service, than look internally.

Those gaps will be filled with people who are good at what we call AI Operations (AIOps).

These will be people who use their unique skillsets and perspectives to build out AI-powered systems and processes that help them delegate their work and do more stuff that they like doing.

But we are in the early early days. Change doesn’t happen overnight.

Beyond job requirements requesting “familiarity with AI”, we’re seeing —

1) Individuals bringing AI Operations into their current roles by:

1. Leading productive discussions in their workplace about the opportunities for their team to adopt AI. We love the AI Hackathons, a great way to ramp up a team and inspire.

2. Implementing small wins in your work to start showing the potential with AI. Prompt libraries are one of the easiest ways to start.

(Make sure you have permission and follow the data privacy protocols your company has set in place)

2) But not every company has these people, and that’s especially where consultants come in who are able to:

1. Attract high intent clients through mechanisms like social media and existing networks

2. Identify and go deep in a niche with enough early adopter interest to build a healthy consulting practice

And last, we’re going to be doing more of this “reporting from the ground”.

We appreciate all of the questions, comments, and ideas shared, always. 🙏 

We care deeply about democratizing insights about where AI, and specifically AI for work, is headed as much as possible.

And if you have an anecdote or data point that you think others could benefit from knowing — our doors are always open, shoot us a note ;)

USE CASE FROM OUR PARTNERS

Make better product decisions, 5x faster

Anyone who has done customer research knows that synthesizing insights takes hours, often piles of sticky notes, and you’re still probably going to miss stuff.

But BuildBetter made the whole process way better.

BuildBetter makes it easy to synthesize everything you’ve learned from customer calls through their AI-powered transcripts, purpose-build search and “summarizations so good it feels like cheating”.

For anyone looking to use AI to supercharge your customer research, check out BuildBetter.

And premium members - we’ve got a workshop with BuildBetter today at 2pm PT / 5pm ET. Grab your spot and we’ll see you there!

LINKS

For your reading list 📚

Data scraping is becoming mainstream…

• ChatGPT’s browsing feature was taken down this week due to data scraping

• Google confirms it’s training Bard on scraped web data, too

Twitter and Meta are at war, and Elon blames AI…

• Elon Musk blames data scraping by AI startups for paywalls on tweets, leading to the introduction of Twitter Blue's subscription service and restricted access for non-paying users.

• Meta unveiled their new ‘Threads’ app, to compete directly with Twitter

And if you’re really nerdy…  

• There is quite the controversy surrounding uncensored chatbots that lack the restrictions imposed by companies like Google and OpenAI, highlighting the potential opportunities and dangers they bring to the table.

• Tech companies like Amazon, Box, Salesforce, and Oracle are responding to the growing demand for workplace AI by leveraging start-up AI products aimed at enhancing efficiency and productivity.

That's all!

We'll see you again on Tuesday. Thoughts, feedback and questions are much appreciated - respond here or shoot us a note at [email protected].

Cheers,

🪄 The AI Exchange Team