Earlier this year, Bill Winters, the chief executive of Standard Chartered, hit the headlines when he discussed a planned 15% reduction in back-office roles over the next four years. It wasn’t the headcount reduction itself that sparked outrage; rather, it was his use of the phrase “lower-value human capital” to describe the roughly 8,000 employees facing replacement by automation.

The phrase fed directly into a growing modern anxiety: the Fear of Becoming Obsolete, or FOBO. From mainstream broadsheets to reactionary social media feeds, there is no shortage of commentary warning us about the end of work.

But should we really be worried? History suggests otherwise. We shouldn’t be fearing AI; we should be preparing for it.

The Evolution of the Labour Market

The internal combustion engine did not replace the horse overnight. As old roles vanished, new ones emerged: ostlers morphed into petrol station attendants, and carriage drivers became bus drivers.

So far, AI is following a similar script. Look at the United States—the most mature AI economy. While service jobs are considered highly exposed to generative AI, the number of white-collar positions has actually grown by 3 million in the three and a half years since ChatGPT arrived on the scene. Even in computer coding, an area lauded for massive AI-driven productivity gains, overall employment has risen.

As the technology integrates further, a wave of new roles is emerging to support it. Here are a few positions that are already active today, alongside a glimpse of what’s coming next:

Roles Existing Today

• Prompt Engineers: Professionals who design, test, and refine the inputs given to AI models to ensure they produce accurate and useful results.
• AI Trainers and Data Curators: Human experts who select, clean, and manage massive datasets, fact-checking AI outputs to ensure models learn from legitimate sources.
• Conversation & Personality Designers: UX professionals who specialise in making AI interactions natural and appropriate, effectively closing the gap between cold algorithms and empathetic human communication.
• AI Ethicists and Compliance Officers: Experts who monitor AI deployments for bias, privacy violations, and copyright issues, ensuring corporate usage aligns with evolving regulatory standards.

Speculative Future Roles

As the industry shifts from simple software chat apps toward autonomous agents and physical robotics, entirely new engineering and management categories will emerge:

• Infrastructure Innovators: The immense physical demands of AI data centres and processing power will drive radical infrastructure roles — from managing superconductors and practical quantum computers to building solar-powered data centres in space.
• Collaboration Managers: If the real value of AI lies in augmenting human effort rather than replacing it, companies will need specialists to manage the day-to-day collaboration between human teams and autonomous AI agents.
• And Beyond Speculation: As we look to a future where AI moves out of the computer screen and into the real world. Autonomous AI agents will move among us.
  • Will they have employment rights?
  • Will they need Trade Union and Legal representation?
  • Is it possible that a future CEO will be silicon-based rather than carbon?

How Do We Prepare?

Navigating this transition will require effort at every level. Governments must keep labour markets flexible through updated employment legislation, and our education system needs an overhaul to teach skills that complement, rather than mimic, AI.

For businesses, prosperity means finding, nurturing, and rewarding the best people to work alongside these tools. While some back-office disruption is inevitable, forward-thinking companies will focus on retraining workers who possess deep, irreplaceable institutional knowledge.

As individuals, the best strategy is to embrace the opportunity. By engaging with AI tools today, you can build a portfolio of adaptable skills that will make you indispensable in tomorrow’s marketplace. Disruption is a natural byproduct of progress, but we have the time to prepare—let’s make sure we use it wisely.

Published: 15 June 2026
© Copyright Just Recruitment Group Ltd 2026

…should we really be worried? History suggests otherwise. We shouldn’t be fearing AI; we should be preparing for it..

Navigating this transition will require effort at every level. Governments must keep labour markets flexible through updated employment legislation, and our education system needs an overhaul to teach skills that complement, rather than mimic, AI.

Long before Silicon Valley, there was “MENACE”—a machine with no wires or chips that could learn to beat you at Noughts and Crosses. Today, that same spirit of innovation is heading into space with SpaceX and Google.

By Connor Stephens

From Matchboxes and Coloured Beads to Data Centres Built in Space: AI has come a long way since 1963! In that year, Professor Donald Michie, of Edinburgh University, declared that

“…in the future, people will draw information from computers as they do water from a tap.”

Professor Michie had originally trained as a biologist at Baliol College, Oxford. In World War 2 he worked with Alan Turing at Bletchley Park, on the development of Colossus, the world’s first high-speed electronic computer. Together with Turing, he conceived the idea that machines could be trained, in a comparable way to people, so that their performance on a given task could be improved.

Initially, this wasn’t called Artificial Intelligence but Machine Learning. Michie’s obsession with the idea that machines could learn led him to build MENACE. The Machine Educable Noughts And Crosses Engine, a machine capable of learning to be a better player of Noughts and Crosses than its opponent.

The most amazing aspect of MENACE was that there wasn’t a single wire or chip in the machine. Computers were not freely available in the early 1960s, so Michie built MENACE from 304 matchboxes and glass beads. Each matchbox represents a single possible layout of the grid in play.

It may have been more Blue Peter than Silicon Valley, but with MENACE, Edinburgh can claim to be the birthplace of AI in Europe. If you are interested in finding out more about the early pioneering days of Edinburgh’s contribution to AI visit https://impact.ed.ac.uk/research/digital-data-ai/back-to-the-future-edinburgh-ai-legacy/ , a celebration of over 60 years of innovation.

Fast forward to 2026, and we are in the midst of a technology revolution, as AI is suddenly delivering against Michie’s prediction. Today, however, the data centres required need more than matchboxes and beads. They require space and power; both are at a premium.

Elon Musk believes that the answer is to build data centres in space where there is access to unlimited solar power and where planning approval doesn’t pose a problem. SpaceX’s Starlink Constellation already has around 10,000 satellites in orbit; the idea is to create a specialist network of satellites communicating with each other and with ground stations by laser beams. Musk’s vision is being taken seriously by a large number of players, such as OpenAI and Google, and could go live in as little as two years.

In the 1960s, the British PM, Harold Wilson, spoke about forging a new economy in the white heat of technology. Perhaps both his and Michie’s visions are about to become a reality.

Published: 16 March 2026
© Copyright Just Recruitment Group Ltd 2026

…in the future, people will draw information from computers as they do water from a tap.

Elon Musk believes that the answer is to build data centres in space where there is access to unlimited solar power and where planning approval doesn’t pose a problem.

Come the final apocalypse only two things will survive: cockroaches and Spreadsheets! Given that the computer-based spreadsheet only came into existence in the late 1970s their spread has been truly phenomenal. A quick chat to Copilot or Google will give you an estimate of between 1.1 and 1.5 billion Excel users in the world. Obviously other Spreadsheets are available. Spreadsheets have revolutionised how individuals and organisations analyse data, manage finances, and make decisions.

From Tiny Acorn to Mighty Oak

The ubiquity of the Spreadsheet is one of the marvels of the modern commercial world. This came about because the advent of Spreadsheets coincided with the phenomenal growth in the power of PCs, as predicted by Moore’s law, and the corresponding reduction in the price of PCs. Since 1979 the performance of a standard PC has increased ten thousand-fold while the price, in real terms, has fallen by 82%.

Year	Price_USD_Adjusted	Performance_Index
1979	5527	1
1984	6042	2
1990	3840	8
2000	2000	100
2010	800	1000
2024	1000	10000

PC Price vs Performance

The concept of the spreadsheet predates computers. For centuries, accountants used paper ledgers arranged in rows and columns to record financial information. This layout directly inspired the digital spreadsheet.

The first electronic spreadsheet, VisiCalc, was released in 1979 for the Apple II. Created by Dan Bricklin and Bob Frankston, VisiCalc allowed users to perform automatic calculations and instantly see results update when data changed. It is widely credited as the first “killer app” for personal computers, driving business adoption of PCs. I first started to use VisiCalc in 1984, and I have been working with Spreadsheets ever since.

In the 1980s, spreadsheet software evolved rapidly. Lotus 1-2-3, launched in 1983, became the dominant spreadsheet on IBM PCs by combining calculations, charting, and basic database features. 1-2-3 became the benchmark for any aspiring Spreadsheet. With the inclusion of Manuscript and Freelance it became the first PC based offering that included, Spreadsheet, Database, Graphing, Document and Presentation functionality. A pre-cursor to today’s Microsoft Office. It set performance and usability standards that shaped the industry.

The rise of graphical user interfaces in the late 1980s and early 1990s paved the way for Microsoft Excel, first released for the Macintosh in 1985 and later for Windows. Excel’s visual interface, powerful formulas, and extensibility helped it overtake competitors and become the world’s most widely used spreadsheet application.

In the 2000s, spreadsheets moved to the web. Tools such as Google Sheets introduced real-time collaboration, cloud storage, and version history, allowing multiple users to work on the same data simultaneously from various locations.

Spreadsheets transformed business decision‑making, democratised data analysis, and remain essential across finance, science, education, and personal productivity.

A Sting in the Tail

But with success came a problem.

Traditionally, applications that could process substantial amounts of data required the engagement of Software Developers or the acquisition of specialist Programs. The democratisation, mentioned above, coupled with the Spreadsheets’ rich functionality empowered users. End User Computing (EUC) was born. If a user could gain access to the data, they were now free from the time and cost constraints that came with traditional IT Development.

Why EUC Grew So Fast

Professionals like accountants, actuaries, and underwriters face constant pressure to move quickly. Spreadsheets let them:

• Build models without waiting for IT
• Prototype ideas instantly
• Automate repetitive tasks
• Adapt tools to their exact workflow

While their spreadsheets often drive decisions involving millions of pounds there is a potential problem; a single mis‑typed formula can cascade silently.

A 2012 academic paper on government austerity, called the Rheinhart-Rogoff paper after its authors, used a spreadsheet with a range‑selection error that excluded key data. The mistake influenced global economic policy debates; indeed, the paper was cited by George Osborne in his defence of his austerity programme.

Other examples of spreadsheets leading to serious embarrassment are:

1. Merchant Bank Loss

Impact: ~$6 billion loss
What went wrong:
A spreadsheet used to assess risk contained:

• Manual data entry errors
• A faulty formula (dividing instead of summing risk values)

Real-world consequence:
The bank vastly underestimated risk exposure, contributing to one of the largest trading losses in banking history.

2. Energy Trading Loss

Impact: $24 million loss
What went wrong:

• A trader accidentally copied and pasted the wrong row in an Excel spreadsheet
• Electricity prices were misread by a factor of 1000

Real-world consequence:
The company executed trades at wildly incorrect prices. The trader was fired!

3. Fund Manager Typo

Impact: $2.6 billion valuation error
What went wrong:

• A missing minus sign in a spreadsheet

Real-world consequence:
The fund temporarily overstated its value, misleading investors until the error was caught.

If your business relies on spreadsheets maybe you ought to consider hiring an expert.

Published: 1 May 2026
© Copyright Just Recruitment Group Ltd 2026

Spreadsheets have revolutionised how individuals and organisations analyse data, manage finances, and make decisions.