The conversation around Artificial Intelligence (AI) is at the centre of considerable discussion. From boardroom strategies to daily news, speculation is widespread, with many narratives forecasting a future where human roles become obsolete.
However, a closer look at history and the technology itself suggests a different outcome. AI is not the end of human work; it is the next powerful wave of automation. Like the disruptive technologies before it, AI will undoubtedly cause disruption, but it is unlikely to make people obsolete. It is a tool that will change how we work, not if we work.
History Repeats Itself
This is not the first time a new technology has been met with widespread fear of mass unemployment. Nearly every significant invention that increased productivity was initially seen as a threat to livelihoods.
The Dawn of the Machine
During the Industrial Revolution, the invention of mechanical looms and knitting frames sparked panic. Skilled artisans, known as Luddites, famously broke into factories to destroy the new machinery that they feared would devalue their craft. It is said that in the 16th century, Queen Elizabeth I refused to grant a patent for a new knitting machine, stating it would “bring to them ruin by depriving them of employment, thus making them beggars.”
The Twentieth-Century Shift
This pattern continued through the following centuries:
- Farming Machinery: Revolutionised agriculture, reducing the need for manual labour in fields, but creating new industries in equipment manufacturing, food processing, and logistics.
- The Calculator: When electronic calculators became common, some educators and parents sparked concerns that students’ basic mathematical skills would atrophy and that accountants would be made redundant. Instead, calculators freed accountants from simple arithmetic to focus on more complex financial analysis and strategy.
- The Computer: As computers entered the workplace, there was widespread concern for administrative and secretarial roles. Many feared that the “sorting, filing, and checking” skills of human workers would be rendered useless.
- Email: A more recent example is the rise of email, which contributed to the decline of physical mail services but created an entire ecosystem of digital communication and marketing.
In all these cases, the technology did not end work. It automated specific tasks, which in turn changed existing jobs and created entirely new roles that were previously unimaginable.
The Paradox of Efficiency (The “Coal Example”)
There is a common assumption that efficiency—doing more with less—will lead to a net reduction in work. History often shows the opposite.
In the 19th century, the economist William Stanley Jevons observed a phenomenon with the steam engine. As James Watt’s innovations made steam engines far more efficient at using coal, the total consumption of coal did not decrease. It dramatically increased.
This became known as the Jevons Paradox. The increased efficiency made coal a cheaper and more effective power source. This spurred innovation, leading to the creation of more engines for new industries like railways and factories, all of which demanded more coal.
This paradox suggests that as AI makes certain tasks more efficient, it may not lead to a net reduction in work. Instead, it could spur innovation, making it cheaper and faster to start new businesses and write new code. This activity will likely create new demand for human skills to manage, direct, and secure these new ventures.
The Perils of Prediction
With the benefit of hindsight, the fears of the past—of a world filled with beggars created by knitting machines or a society of unemployed accountants—can appear misplaced.
This highlights a simple truth: humans are generally not very effective at predicting the complex, long-term impact of new technologies. The interconnectedness of an economy means that a change in one area creates countless ripple effects in others. Therefore, any person who claims to know exactly what the future holds is merely providing a prediction, and predictions are often wrong.
What is Artificial Intelligence, Really?
To understand its impact, we must be clear about what AI is and what it is not.
At its core, AI is a powerful tool for automation. It excels at processing enormous volumes of information to identify patterns and automate repetitive tasks.
- What AI excels at: It can hold, process, and retrieve huge amounts of information very quickly and cheaply, providing responses based on known information and past answers.
- What AI does not do: In its current form, AI does not perform true logic or abstract reasoning. It does not solve novel problems for which it has no pre-existing data or known answer. It cannot, for example, devise a creative solution to a brand-new business challenge it has never seen before.
The Real-World Impact on Jobs
Because AI is a tool for automating repetitive tasks, its impact will be felt differently across various industries and roles.
Which Roles May Change First?
The initial impact of AI is most likely to be felt in roles that are:
- Highly repetitive
- Highly simple
- Low-risk
- High-cost
This includes many customer-facing roles, such as receptionists and call centres, where AI can be trained on a known set of common questions. Marketing, which relies on analysing large data sets, is also likely to see significant change.
The Enduring Need for Human Experts
Conversely, tasks that are complicated, rapidly evolving, and adversarial are not a good fit for complete automation. These roles require logic, creativity, and the ability to adapt to new information—all areas where human experts remain essential.
Why Cybersecurity Experts Are Not Going Away
Cybersecurity is a prime example of an adversarial and rapidly evolving field. It is not a repetitive, static problem. Cyber attackers constantly change their tactics, techniques, and procedures to find new vulnerabilities. Defending against these threats requires human logic, creativity, and an adaptive strategy.
AI will undoubtedly provide specific tools and uses that can help defenders identify threats faster. However, cybersecurity experts are not going away.
If anything, the need for skilled cybersecurity professionals may increase. As AI helps create more code and more new businesses, our collective digital footprint expands. This creates a larger attack surface, which in turn requires more human experts to defend it.
Vertex: Prepared for the Future
Navigating this new technological landscape requires a partner who understands both the potential of automation and the critical importance of security.
At Vertex Cyber Security, we are already leaders in implementing sophisticated automation platforms. We understand how to leverage these tools effectively and are fully prepared for the future of AI, including defending our clients against sophisticated AI-powered cyber-attacks.
How Vertex Can Help
Understanding how AI will impact your specific business, from its operational efficiencies to its new security risks, can be a complex task.
If you would like to discuss tailored solutions or learn more about how to prepare your business for the next wave of technological change, please contact the team at Vertex or visit our website for more information.