Will ChatGPT change the world? To answer that we need to look at the adoption of previous generations of automation technology. How fast have they been adopted? And by whom?

Getting Paid

I've had trouble with late payers recently. More than usual. Sadly, after 17 years running my own businesses, I've come to expect a few invoices to be overdue here and there. But this was a lot of invoices, very overdue. It was stressful. For both me, and my clients.The people I work with in client organisations rarely have much control over what gets paid and when. Even if they are senior leadership. They can chivvy and chase, but they can't make it happen. It's embarrassing for them.By way of explanation or apology, clients have sometimes let me in on the internal machinations preventing me from getting paid. These stories are no longer shocking, but the interminable bureaucracy of large organisations* is always disappointing.The conversations bounce between time zones and departments. Finance, IT, operations, marketing, procurement, HR. Many people are involved. Ultimately, the problem is usually simple. Two digits are transposed in my bank details and somehow IT have to get involved to deal with a change request. Someone just missed an email, or was dealing with a backlog of work and holding up everyone else.There are no good excuses for late payment. But occasionally I have a little empathy. How much must these failures cost the business? How many hours of time? Across how many people? How much lost hair and how many sleepless nights?

Bug or feature?

You won't always see it as a supplier, but most companies now have some sort of process automation wrapped around their procurement. In fact, around most of their processes. The idea of these systems is to streamline things, make them more efficient, and avoid errors. Or is it?The evidence would suggest they're not very good at getting suppliers paid on time. Judging by the feedback from Twitter followers when I whine about late payments, my experience is pretty universal. And failures seem to create enormous inefficiency at the client end, costing them time and money.So what are these systems really for? And why do companies keep using them?One reason is to control spending. Leaders naturally want to know where their company's money is going and who is spending it. Another reason is fraud prevention - or at least ensuring that there is a good paper trail to prosecute those who do commit it. But couldn't they do these things and make things more efficient? Certainly, that would have been the promise of whoever sold them the system.

Humans failing the technology

The answer is that of course the system could be more efficient, as well as creating the appropriate controls and paper trail. But it's not (usually) the system that prevents that from happening. It's the people.Who benefits if the system is more streamlined? Headcount can go down. Fewer people are needed in finance and IT. The business might benefit but those people don't.Bosses would have more time on their hands. But they would manage fewer people. Have a smaller budget. They would lose prestige. They don't feel like they would benefit.This isn't to say that people are consciously sabotaging the system. They're not. They're doing their job. The same job they did yesterday, and the day before. Things that feel right, good and rewarding. They are making sure the processes are followed. Making sure no bad transactions get through. That's what they're there for, right?What they are rarely incentivised to do is fix the broken bits of the process and do themselves out of a job. And so, they don't.In fact, even when a new system comes in, they tend to keep doing what they did before. They bend the system to their old behaviours. Without enormous and often disruptive interventions in changing behaviours - and sometimes people - as well as technology, things largely stay the same, just with new software.

Is ChatGPT any different?

While all this late payment shenanigans was going on, my timeline was filling up with examples of the latest iteration of OpenAI's work, ChatGPT. A machine learning system trained on a sea of data to create new things based on simple text instructions. It can write a story, a press release, code or even a multiple-choice adventure game.At first glance it looks like some kind of doomsday device that will destroy employment in a variety of sectors. But analysed in the context of my experiences trying to get paid, I'm not so sure.Process automation technologies like the ones that should have seen me paid on time with the minimum of fuss are not new. And yet years - decades - after their introduction, human beings are still stopping them from delivering on their promise**. Out of self-interest, lack of interest, lack of incentive or support, we've stymied much of the promise of efficiency.Why should ChatGPT be any different? In many corporate contexts, I suspect it won't.

Beyond the corporation

Outside the walls of the corporation or other large bodies though, the situation looks very different. ChatGPT and its brethren are weapons of wicked efficiency for the lean - and the potentially unscrupulous.Twenty-something years ago I was working on the marketing efforts of a large US software firm. Let's just say they were involved in video, for fear of upsetting any old clients. The company's revenues always seemed slightly out of kilter with the small number of case studies we were ever able to offer. A few high profile sports leagues and a couple of broadcasters didn't seem like a significant enough customer base to justify the numbers they were doing. The reason, we all knew, was that the biggest chunk of revenue came from the adult industry. And no-one wanted to talk about that.Who was the earliest to latch on to the potential for streaming media? It was the adult content providers***. The same group were very early to the potential for the tablet. I heard an anecdote from someone in the adult industry that the day the iPad launched, the wholesalers (yes, pornography has wholesalers) were ready with all their content refactored to the appropriate screen sizes.Translate this behaviour to the here and now. Who will be the companies making the most out of ChatGPT?

High volume, tight personalisation, low quality

ChatGPT doesn't turn out amazing quality writing. Yes, it's better than a lot of first drafts I've seen from many writers. But it's not going to win a Pulitzer, or even get past any decent newspaper editor. If you have high standards for quality control, you're not going to be using it. Or at the very least, you will be doing a lot of editing before you publish.But there are a lot of places where quality is much less important than volume, and tailoring. Anywhere you want a lot of words about a particular niche, ChatGPT will be useful. As will equivalent platforms: while OpenAI might have content moderation, other platforms do not.Two industries spring to mind. The adult industry first of all, just like in the old days of streaming media. Sure enough, there is apparently a thriving community of people using large language models (the generic term for tech like this) to write niche erotic fiction. Whatever your particular peccadillo, you can now get an endless supply of tailored fiction to meet your needs. The web will be awash with it soon enough, as it will with its image, video, or interactive equivalent. Combine an AI-written script with deepfake tech and you have generative pornography.Then there is the search engine optimisation industry, and the web content industry more broadly. Tech-savvy people who are trying to maximise the return on investment of their time. Want to create a website that looks like the authority on any particular topic? ChatGPT could be your answer. Of course, Google's algorithm could be tweaked to spot AI-generated content (read enough and it has a noticeably idiosyncratic style). But that's just the latest round in an ongoing battle between those building websites and the businesses trying to help us navigate them.

Many niches

These aren't the only applications where ChatGPT will be successful. There are likely many more niches where cost and tailoring are more important than outright quality. But I think they are representative. And in every niche, this generative technology presents the same problem: navigation.We are already struggling to navigate the digital world. There's too much of it. Too much content. we struggle to choose the best use of our time, facing constant FOMO. What happens when there is a 10x, 100x, 10000000x increase in the volume of content out there? Without a meaningfully better way to filter and navigate, we will be lost, swamped by it.Technologies like ChatGPT will not just swamp us in content, they will drive us into ever smaller niches. Arguably the reason that so much investment goes into franchises like Marvel and Star Wars these days is that they are some of the few brands that can still attract a mass audience. With so much choice in front of us, it will be easier and easier to sink into a niche of one. That might sound appealing but it's not always healthy. We need content that connects us and creates a shared conversation. And I'm not sure a robot is going to deliver that any time soon.##*A journalist on Twitter asked for a good book about 'business' the other day. I pointed out that there's often very little difference between the internal workings of large organisations and the state organisations with which he is more familiar. This is more true than many in the 'dynamic, efficient' private sector would like to admit.** Note, it's not just humans. Some of the software is just crap.*** They weren't the only ones obviously, but they were operating at enormous scale very early. See also, online gambling.