Martin Jackson — your intelligent automation partner

The “AI-Enabled Generalist” is Bollocks (Unless You Fix This First)

Martin Jackson
Martin Jackson
Pop art illustration of a smartphone and keyboard in bright, multicoloured gradients with the text: 'OpenAI The AI-Enabled Generalist is Bollocks'.

OpenAI just dropped research showing 28% of workers use ChatGPT at work. Everyone’s celebrating. Tech blogs are going mental about the “AI-enabled generalist” – one person doing the work of three departments.

Sounds bloody brilliant, right?

Here’s the thing nobody’s saying: You can’t automate chaos.

And most SMEs? Their business processes are absolute chaos.

What the Research Actually Shows (And What It Doesn’t)

The numbers look impressive on the surface:

  • 28% of US workers use ChatGPT at work
  • 45% of people with graduate degrees are on it
  • Young workers (18-29) use it twice as much as the over-50 crowd
  • Top use cases: writing, research, programming, analysis

Tech teams love it. Marketing teams love it. Everyone’s saving time, getting more done, becoming these magical “generalists” who can handle multiple departments.

But here’s what the research glosses over:

Most people are only scratching the surface. They’re using basic features – search, simple data analysis. The advanced stuff? The really powerful capabilities? Barely touched.

And there’s a reason for that.

The Problem Nobody Wants to Talk About

Abstract pop art collage of angular, textured polygons in red, blue, yellow, and beige, with the text 'Disconnected Polygon Web' visible.

BBVA – massive Spanish bank, proper resources, dedicated IT teams – deployed ChatGPT Enterprise. Result? 80% of users saved 2+ hours weekly.

Sounds amazing, yeah?

But they also faced “significant challenges integrating ChatGPT with their existing systems.”

Let that sink in. A major bank with unlimited budget and tech expertise struggled with integration.

Now think about your average £2M revenue SME running on:

  • Spreadsheets nobody updates
  • Customer data scattered across email, CRM, and Gary’s notebook
  • Processes that live entirely in people’s heads
  • Systems that don’t talk to each other

You’re going to plug ChatGPT into that mess and expect magic?

Bollocks to that.

The Data Security Nightmare You’re Ignoring

Abstract geometric illustration of a black silhouette with blue and red shapes spilling from it, pop art style, with the text 'Perforated Silhouette Spill' visible.

While everyone’s excited about productivity gains, here’s what’s actually happening:

  • 4% of employees have already put sensitive information into ChatGPT
  • Data leak incidents jumped 60.4% between February and April 2023
  • Most common leaks? Internal data, source code, client records

Samsung found out the hard way when engineers pasted confidential code into ChatGPT. Company-wide ban. Done.

For SMEs, this is even more dangerous. You probably don’t even know what your team’s putting into AI tools. Your 24-year-old marketing assistant might be feeding your entire customer database into ChatGPT right now.

And you’d never know until something goes tits up.

What You Actually Need to Do First

Geometric pop art illustration with yellow, blue, and pink shapes, arrows ascending steps labeled 'ORGANIZING', 'DOCUMENTING', and 'INTEGRATING' in bold text.

Before you get excited about becoming an “AI-enabled generalist” operation, sort these three things:

  1. Get Your Data Sorted

Where does your customer information actually live? Email? Spreadsheets? Your CRM that nobody updates? Gary’s brain?

AI can only work with data it can access. If your data’s scattered, inconsistent, or incomplete, AI will just amplify that mess.

  1. Document Your Bloody Processes

Can a new employee understand how your business works by reading documentation? Or is everything tribal knowledge?

If you can’t document it, you can’t automate it. Full stop.

  1. Make Your Systems Talk to Each Other

Does information flow from your website to your CRM to your email platform without manual intervention?

Or is someone copying and pasting data between systems like it’s 1995?

The “AI-enabled generalist” assumes integrated systems. Most SMEs are running disconnected tools held together with manual data entry and hope.

The Right Way to Do This

Here’s what actually works:

Start with your most repetitive, time-consuming manual tasks. The stuff that makes you want to throw your laptop out the window.

Make sure those tasks have clear documentation. Write down exactly how they work. Every step.

Implement automation in phases. Test it. Refine it. Make sure it actually works before moving on.

Only then expand to more complex applications.

The businesses winning with AI right now aren’t the ones with the fanciest tools. They’re the ones who did the unglamorous work first: cleaned their data, documented their processes, integrated their systems.

Then AI becomes a force multiplier.

The Bottom Line

The “AI-enabled generalist” is real. I’ve seen it work. I’ve built systems that do exactly this.

But it’s not a shortcut. It’s the result of proper preparation.

Rushing to adopt AI without fixing your foundation doesn’t make you innovative – it makes you vulnerable. You risk data breaches, wasted money on tools that don’t integrate, and frustrated employees who can’t make the technology work.

Do the boring work first. Clean your data. Document your processes. Integrate your systems.

Then – and only then – does AI become the game-changer everyone’s talking about.

Without that foundation? It’s just expensive chaos.

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AI Disclaimer: Because Apparently We Need One Now

Right, let’s get this out of the way before someone has a proper meltdown…

Yes, I use AI. Shocking, I know. An AI automation specialist using AI – it’s almost like a chef using knives or a plumber using spanners. Mental, isn’t it?

Here’s the thing – I’ve never pretended to be Picasso. I can barely draw a decent stick figure, and my artistic education peaked at colouring inside the lines (which I was rubbish at). So when it comes to creating visuals or researching content, AI is bloody brilliant at doing the heavy lifting.

But here’s what AI can’t do – it can’t replicate 30+ years of getting my hands dirty in real businesses. It can’t copy the scars from watching “simple integrations” turn into six-month nightmares. And it definitely can’t swear like a proper Brit who’s spent decades dealing with systems that mysteriously decide important data fields mean something completely different.

The EU’s Having a Field Day (Naturally)

Speaking of overreactions, the EU’s now mandating AI content labels because apparently they’d regulate the opening of a crisp packet if they could. Their new AI Act requires everything to be marked, watermarked, and probably stamped in triplicate.

Meanwhile, the UK’s taking a more sensible approach – “use your judgement, don’t be a pillock about it.” Refreshing, really.

But here’s the kicker: research shows that slapping “AI MADE THIS” labels on everything actually makes people trust it less – even when the content is identical quality. It’s like putting a “CONTAINS CHEMICALS” sticker on water. Technically true, completely mental.

Remember When Social Media Was “Just a Fad”?

This whole AI panic reminds me of those highly respected business experts who dismissed social media as a passing trend back in 2006. You know the ones – sitting in boardrooms saying “Facebook is just for university kids” while their junior staff begged them to pay attention.

Those same companies spent years trying to catch up after realizing they’d missed the boat entirely. By the time they finally joined Facebook in 2011, their competitors had built communities, refined strategies, and owned the conversation.

Here’s the scary bit: AI adoption is happening three times faster than social media did. We’re already seeing the same pattern – 5% of companies are crushing it with AI while 95% are still “evaluating options” and “waiting to see how it develops.”

Guess which group my clients want to be in?

My Process is Simple:

  1. AI helps me research and draft the boring bits.
  2. I add the personality, experience, and occasional profanity.
  3. I make sure it actually makes sense for real businesses.
  4. I take full responsibility for everything published.

The Reality Check

To those clutching their pearls about AI assistance: get over it. We’re not going back to typewriters and encyclopaedias. The future belongs to people who embrace tools that make them more effective, not those hiding behind “authentic struggle.”

Besides, if you think AI came up with my stories about early automation systems going mental and mixing up data fields… well, you’ve clearly never worked with AI long enough to know it’s nowhere near that creative (or sweary).

TLDR: AI helps, humans create, everyone wins. Now can we get back to actually helping businesses instead of arguing about tools?

P.S. – If you’re still bothered by this, you’re probably not my target audience anyway. My clients care about results, not whether I used a calculator or did the maths by hand. And they definitely don’t need the EU telling them how to label their content like it’s a tin of beans.

P.P.S. – Those “experts” who missed social media? They’re probably the same ones telling you to “wait and see” with AI. How’d that work out last time?

All insights are based on publicly available information and my 30+ years of business technology experience, including building AI systems since 2021. This content is for informational purposes only and is not intended to be professional or legal advice.

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