INBOX INSIGHTS: Artisanal vs. AI, ChatGPT and Job Losses (8/2)

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AI-driven versus Artisanal

30% of jobs, 80% of jobs, 100% of jobs. AI will take all the jobs. These are the headlines we read every single day. Worry about AI. Your job is not safe.

“A person skilled at AI is more productive than a person who is not” – Chris Penn

“By 2030, activities that account for up to 30 percent of hours currently worked across the US economy could be automated—a trend accelerated by generative AI.” McKinsey & Company

We’re all scared to lose our job to AI soon, right? AI is going to make processes more efficient. AI is going to take repetitive tasks. AI is going to run your life.

I don’t know. I have a different perspective on this. I agree that AI is going to do all this, and more. However, I also feel like there will be space for those that choose not to let AI run everything for them.

The best example I can give is Amazon versus Etsy. Amazon, in this example, is the AI-driven store where processes are efficient, prices are low, and they deliver goods within hours. Etsy is the artisan shop where prices are higher, goods are hand-made, and delivery happens with the item is ready. I’m aware that Amazon has a small business, curated good section, and that some Etsy shops operate like Amazon. But for the sake of this post, let’s pretend we don’t know those things.

Let’s explore the pros and cons of AI-driven versus Artisanal. Also, if anyone can suggest a better word than artisanal, I’m all ears.


In this example, goods are mass produced by Amazon and hand-made to order on Etsy. If you think about the marketing you do there are going to be cases where mass produced things are good. There are also going to be cases where you want something hand-made. If you are running ads and trying to test a lot of variations and adjust bids and targets, AI is good choice. However, if you’re developing a piece of thought leadership content meant to demonstrate your authority and brand voice, using AI is not the right choice. You will want something hand-made, or “artisanal”.


There is no doubt that over time, AI can save money due to the efficiencies. If you buy something from Amazon, you can find goods that are low in cost and delivered for free. If you’re purchasing from Etsy, you’re likely to pay higher and foot the bill for shipping. This is a tough one – as the saying goes – you get what you pay for. Maybe you need a high volume of things created for your marketing and you have budget constraints. On the other hand, maybe you need only one or two pieces that are specifically tailored to one audience. In that sense, spending more money of the customization could be worth it.

Customer Service

When it comes to customer service, you will find people that only want to deal with chatbots and people that only want to deal with other people. When you reach out to Amazon, you’re not getting a person. You’re getting an automated system first. With Etsy, you’re reaching out directly to the shop owner who will talk to you and answer your questions.


Sometimes, you need it now. You need it yesterday. In that case, AI is a good option. Amazon can deliver to you within a few hours, sometimes faster. If time is not an issue, something hand-made that takes longer can work.

Here’s the point – I can imagine a world where both options have space in our industry. There are companies that will want to cut costs, make processes more efficient, and offer convenience. There are also companies that will opt out of being AI-driven. They will continue to hand-craft and customize their products and services. Both can exist. Both examples are valid.

When I think about “will AI take my job?” – the answer is at some companies, yes. But at some companies there will be a place for you to do things by hand. You have to make the choice which direction you want to go and what customers you want to serve.

Are you worried about AI taking your job? Reply to this email to tell me about it, or come join the conversation in our Free Slack Group, Analytics for Marketers.

– Katie Robbert, CEO

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Binge Watch and Listen

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss takeaways from the recent Marketing AI Conference, MAICON 2023. We talk about the growth of the event, Chris’s generative AI keynote, and share highlights from other speakers on AI regulation, ethics, and impact on jobs. We debate whether agile development processes are still needed with AI. Katie challenges the idea that QA processes can be fully automated. We speculate on an artisanal future where automation and human craft co-exist. Join us for a lively discussion on where AI is taking marketing and business.

Watch/listen to this episode of In-Ear Insights here »

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Data Diaries: Interesting Data We Found

In this week’s Data Diaries, let’s look at the supposed impact of ChatGPT and similar tools on jobs. One of the great fears people have is that AI is going to devour all the jobs, and while there will be many, many tasks that we will turn over to AI, the technology is still insufficiently advanced to do entire jobs (assuming a job is more than one task).

So, how would we know AI is becoming a problem? What would be a good indicator? A candidate source would be the number of open positions in jobs that would be heavily impacted by generative AI. For this newsletter, we’ve picked three categories: information jobs, marketing jobs, and software development jobs. Generative AI impacts all three; by some estimates, 70% of ChatGPT usage is by developers, so all three should be the proverbial canary in the coal mine.

To do this, we can turn to the data provided by to the US Federal Reserve Bank of St. Louis, the FRED data system. Indeed has published a relative index of job openings in a variety of fields since just before the pandemic, with data normalized at 100 for February 2020.

Let’s take a look at the big picture:

What we see in the first chart here are the three fields we’ve chosen, and their relative indices throughout and after the pandemic. Note the black vertical line: that’s the day ChatGPT arrived on the scene.

If ChatGPT had a disastrous effect on jobs, we would see a substantially sharper decline in the post-ChatGPT period than we do. Now, one of the challenges with a dataset like this is that the pandemic itself imposes enormous distortions on the data. These effects are impossible to see with the unaided eye; to identify it clearly, we need to do a mathematical comparison of periods in the data when the pandemic wasn’t happening to periods when it was – as well as account for the presence or absence of ChatGPT. To do this, we use a statistical method known as propensity score matching, which is a form of retroactive A/B testing.

When we perform this test, what do we see?


We see the pandemic control, which makes perfect sense. There are fewer pandemic days since the rollout of ChatGPT than there were prior, so that number should be in the negative. That tells us the basic mechanism is working correctly.

And we see that marketing jobs, developer jobs, and information jobs on average have INCREASED proportional to similar time periods after the rollout of ChatGPT rather than before.

So what? What does this tell us? As is normal for humans, we overestimate the short term impact of a new technology and we underestimate the long term impact. This system of measurement helps us to discern changes over time, and is something – assuming the data remains available – to monitor in the months and years to come. Techniques like this will help us to see the changes as they happen, and they will be slower at first until they’re not. By running an analysis like this regularly and frequently, we can monitor for these changes and know to take action sooner rather than later.

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