Why I'm Building Digitising Events in Public: The Consulting Model Just Died

A personal note on digitising events: why I have willed it into existence.

The realisation hit me gradually, then all at once at the beginning of 2024. Our consulting business, the tech advisory work we'd built around media and events, had just been kicked into touch. Not declining. Not evolving. Fundamentally obsolete.

Let me give you a specific example. We were previously rewarded for creating queries on top of GA4 Google Analytics exports to feed into Looker Studio dashboards. The creation of those queries required specialist knowledge, an intuitive understanding of how BigQuery worked, and sufficient domain expertise to navigate its quirks. We'd built up that resolution over six to eight months when the capability first came out.

Now? You describe the outcome to a GPT, tell it how you're getting the data, and it writes a perfect version of what we used to charge for in a matter of minutes.

Don't get me wrong—you still need some domain knowledge for the odd quirks and edge cases. But it's doing in minutes what took us months to master. That form of consulting, where your value is time, is dead because many things that used to take time no longer do.

The same applies to tracking guides for media sites using GA4, optimising WordPress installations, creating real-time reporting from registration feeds—all of it. I now know empirically that you can do these either directly or very quickly with the help of a generative model.

The Surface Problem

However, what I've realised is that the average person starting to use AI never really goes beyond the surface of it.

It's similar to when Excel first came out. People still do this—you use Excel or Google Sheets to quickly sum up columns or do some calculations on lots of numbers. But very few people then start digging further and asking: What can I do with pivot tables? What can I do with all these other functions? What about that function that lets me get exchange rates in real time so I don't get caught on the wrong side of FX calculations?

The same is true for generative AI and the capabilities it spins off.

For example, we can now do vector embeddings much more easily and cheaply than we've ever been able to do before, as a direct result of the generative AI revolution—let's call it what it is, it genuinely is a revolution. Very few people realise that all the spin-off capabilities now available at a low cost can enable you to do amazing things.

Vector embeddings basically mathematically encode meaning. If you now know the meaning in a mathematical context of every single piece of content, there's a lot of crazy stuff you can now enable.

The Charlatan Problem

As a consultant or someone wishing to specialise in this and help small businesses activate this technology, I would feel like a charlatan if I hadn't tried it and experienced it "in production" first hand.

I don't personally feel comfortable going to a business saying, "Hey, I think this will work, let me try it." Because you'll never get the chance to try it to its fullest extent, having worked in small businesses, I know that when you're running a business with paying customers and audience expectations, it's very hard to go in and properly disrupt those.

This is one of the unique things I can bring to the table, as I have a deep understanding of the dynamics of a small business. Many people commenting on AI lack knowledge or experience of it.

And in their language, when they say "startup," they don't mean startup in the way I've been used to—where you've scraped together maybe £150,000 or £200,000. What they mean is you've scraped together £10 million and you've got enough fat to burn to do things wrong and so on.

That's not the reality of a small business.

The Birth of Digitising Events

All of that led me to the conclusion: to help clients effectively, I need to run a business that resembles the types of companies I want to assist, and do it in real-time.

If I do learn something, I know empirically that it will work before I can apply it to a customer.

That is where the idea of Digitising Events was born, and that is what I am doing on this site.

A Different Mindset

It's somewhat of a different mindset, though—I'm going to be honest. For the first time, there is value in sharing very openly when things fail, and there is value in sharing very openly when you don't know the answer.

Let me give you an example: SEO.

With publishers, there used to be an unwritten value exchange between you and the search engines. You wrote content. You put energy and effort into making it surface when people asked questions your content could answer, and that effort rewarded you with traffic.

Now, anybody looking at the AI-generated results pages will know that those are so comprehensive—taken from various sources and created in a way that they almost look like a Wikipedia page or a terrible website out of the 1980s—but it still has all the information there. There is genuinely no reason to go and click over to another site.
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Therefore, if you are a consultant to independent businesses or part of the publishing industry, you need to recognise that this is no longer the case. When you come up with your recommendations about "Hey, I'm going to improve your traffic," the five slides that cover SEO? You may as well burn them.

That is the reality of how quickly everything is changing. You don't understand that and realise it unless you are actively in practice.

Again, Digitising Events—that's why I created this site.

Everything Is an Event

You'll notice, though, that I'm taking a looser definition of "digitising events" because I think everything is an event.

While in the past it may have meant literally an event where people come together—such as webinars and the like, which we've consulted on in terms of those strategies—now I'm talking about everything. Everything is an event that generative AI is disrupting.

And I'll take that one step further: Generative AI is also disrupting productivity solutions and changing how businesses implement them. That is a fact.

Here's an example. I've worked with a business where editors wrote their entire content in Google Docs. Their editors wrote on Google Docs, collaborating on it; Google Docs is an excellent platform for that, and then the final article was completed and migrated onto their CMS.

I know for a fact that they pay a hefty sum for a software-as-a-service solution that takes a Google Doc and literally converts it into HTML so that an automation can load into the CMS.

And here's where GenAI disruption comes in, and I have proven this.

You can now go into one of the GenAI solutions—OpenAI, Claude, whichever one you're using—and you can say something like, "Hey, I'm using Google Docs to write my content. Is there a way of automatically taking that, turning it into HTML, and pushing it into"—Webflow, in our case, because that's where I've tried it.

And the AI will write the function that performs that task.

Suddenly, you have the ability, even though you may not be a programmer, if you can have programmatic thinking, you can write these microservices that, for a small business, save you a ton of cash.

The solution I was talking about that did that? It costs around £150 a month. The microservice that does it, at the same scale, and you have more control over? Costs about £3 a month.

I think small businesses need to start utilising this toolkit and understanding what it can now do for them in terms of outcomes—facilitating positive outcomes, improving productivity, and reducing operating expenses (OPEX).

The Question Nobody's Answering

Why am I so hot on this? I get very passionate about this side of things.

Fundamentally, there is one huge question that no one is trying to answer. Everybody is shouting out that it may well be a problem, and it will be, but putting some effort behind answering it is what is needed.

And the question is this: How is GenAI creating jobs?

In the publishing and events domain, I can clearly see where it is taking away jobs. Let's differentiate between jobs and work—the two are different, and I'm not going to go into the nuances of the differences; I think you get it.

But when I can so clearly see the jobs that I no longer need—or I'm no longer going to look towards "Hey, that is a team of people who are going to do that"—if I can so clearly see where the displacement of jobs is going to be, surely we all need to start on the exploration of: OK, if we can see that, what new work do we need to do that truly requires human creativity and intelligence?

Having worked with AI for over two years, we definitely need it, because these systems can't join dots like we can.

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The Labelling Nonsense

Ironically, everybody is going on about, "Oh, you know, we need to label if AI generated it." I think that's nonsense. It genuinely is nonsense.

I'll give an analogy here. When I was growing up, I got really into James A. Michener. I loved his books—his historical novels that spanned generations to tell the story of a geographical place: Alaska, Chesapeake, The Source, and Poland. And his books, you know, I've since learned—he was one man in a corner taking the credit for sure, but he had a vast team of researchers helping him.

If James Michener were looking at the problem today, he'd have a huge team of AI helping him do the research and pull it all together.

But the point I'm making is that you still need that person at the centre to join things together and tell that story so that it resonates with a reader or the person you're telling it to.

And that is, I think, one of the things that will—I believe—forever remain a role within a publishing business.

Critical Non-Essentials

We need to invert the thinking. Because if we say that, actually, that is where I want to put all my effort—and if I can, I'm not going to lose the number of people I have in my business, I'm just going to change the work they do—it is entirely possible to offload all the stuff that was creating work for incremental returns.

Or things that, you know, as Clive Woodward said in his book Winning, are "critical non-essentials." If you've written a great article, numerous critical tasks and a plethora of critical non-essentials need to support the article. A cover image, or if you're a data journalist, you may want a graph/infographic done, because that will help tell your story.

All of those things—critical non-essentials. I believe that's where AI sits, and that is how we should activate AI.

And small businesses have a superpower. The superpower we possess is that we can, much more effectively than large businesses, adapt our operations and move quickly, taking advantage of this opportunity. And we need to.

The Outcome-Centred Approach

But for me, I would have never really come into this insight about offloading creative work—in terms of trying to identify what's a critical non-essential and what isn't, and to keep the human at the work that requires deep joined up thinking, storytelling, and all of the essential elements—if I hadn't gone through the process of creating this site myself and feeling that pain and going, "OK, how do I solve this? What is the right thing? How do you rip apart work?"

And the way I have approached that is by defining our work around the outcome. What is the outcome? The outcome is an excellent piece of content that's informative and helpful. What's the role of the human mind, which is so powerful and unique? And what jobs can we push into this generative AI world?

It requires a very different approach to the problem than we've needed to think about in the past. Because in the past, our only solution has been the human mind, which is—in the parlance of the technologists—multimodal. It is so advanced and unique... No one has replicated it yet, and it's still a long way from being reproduced.

We're certainly not ready for that to happen right now. It's bad enough what generative AI is going to do.

However, because our go-to has been the human mind, we have assigned it tasks and jobs that overburden it with noise, adding no value to creativity, imagination, and adaptability.

The Live Exploration

So, that is the reason I created and run Digitising Events.

If you've read this far, thank you. And I hope the content that I create—and the reason why it's just me at the moment—is part of one of the other thought experiments, for want of a better word: How far can one person go creating and maintaining a site like this with the use of generative AI?

And what does that teach? Only by having gone through all of that myself can we emerge from this entire experience as a technology advisory consultancy that truly understands how to apply AI to create transformative business impact.

One thing I have realised is that this thing is so new; I call it the COVID of tech. No one has the playbook, and anybody pretending they do is lying.