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Digital Transformation
05 July 2026 - 4 min read
One of the biggest talking points in recent years has been the rise of AI in our workplaces and daily lives. AI is fast becoming a force to be reckoned with, with over 44% of individuals having spent time using AI tools during work hours in August 2025 alone.
However, there has also been significant discourse around the potential risks and ethical implications of using a technology that is still poorly regulated and, at times, unpredictable.
In this blog we’ll explore some of the risks and ethical challenges of AI, as well as covering some tips on how to overcome these issues and promote responsible use.
AI carries with it some inherent risks and dangers, and the question of whether or not we should embrace it or resist it remains controversial and complex.
Some of the most prominent risks of AI include the following:
A significant and worrying threat of AI is the impact it may have on our livelihoods.
Jobs such as translating, coding and writing are at a particularly high risk, with AI being able to carry out these tasks with remarkable accuracy and efficiency, potentially one day making human workers redundant in these roles.
AI is also starting to impact entry-level roles in various sectors, with a scarcity of available jobs creating fierce competition among university graduates and other career starters. Some American gen-Z workers have even resorted to creating their own jobs in a marketplace where more traditional corporate roles have dried up.
However, the reality is that no one is quite sure how exactly AI will affect the future labour market. While people like Jeff Bezos have repeatedly claimed that AI will create more new jobs than it’ll replace, others are less hopeful and speak of significant upheavals to the economy and the global workforce.
Others, meanwhile, claim that AI will simply reshape the way that many people work, streamlining productivity much in the same way that the internet and digital communications transformed the workforce back in the 2000s and 2010s.
There’s no denying that the looming threat of AI is already taking a mental toll on employees though. A startling 52% of US workers now fear job displacement due to AI, with reports of anxiety, paranoia and insomnia as a result of perceived job insecurity. There’s even a new proposed clinical term for this phenomenon: AI replacement dysfunction.
Whatever the future holds for AI, there’s no doubt that it does represent a worrying existential threat to many, with the full scale of effects yet to be seen.
AI is still a burgeoning technology and its potential role in professional development is still yet to be clearly established.
However, there have been a slew of studies warning against the risks of cognitive atrophy or skill decay associated with AI use in schools and workplaces; in other words, a decline in skills and cognitive thinking due to overreliance on AI for critical tasks.
The resultant stagnation of skills and abilities may lead to an overall decline in professional development, as the need for agile, adaptable thinking may well be replaced by AI models who can instead solve difficult problems in the workplace on our behalf.
We’re still unsure of what the future relationship between AI and professional development might look like on a global scale. But it’s well worth being mindful of the potential risks of AI removing our need to continually hone our thinking and problem-solving skills in the workplace.
The technology used to power AI is accelerating at a startling rate. As progress marches on, it becomes increasingly important to monitor bad-faith uses of AI and the threats it can pose to global cybersecurity.
For instance, although AI can be used as a tool to strengthen digital infrastructure from cyberattacks, it can just as easily be used to accelerate the force of such attacks, exposing vulnerabilities in systems and crafting unprecedented new threats.
Deepfake tools can also be used to create highly realistic audio or video content, adding additional layers of sophistication for phishing or social engineering scams.
AI systems themselves may even pose threats to cybersecurity. Inadequate security measures in AI models can lead to exploitation, unauthorised access, data breaches or even malicious, poisonous code being planted within their systems, introducing a new layer of risk for those who use AI tools. These risks are further amplified when AI is used to handle or process sensitive data, such as personal information pertaining to employees or vulnerable groups.
Using AI to process employee data or to automate HR systems is especially risky due to one of the biggest inherent risks of the technology: bias and misinformation.
AI is not a neutral agent by any means, and the information it provides is far from impartial.
Rather, AI is highly susceptible to bias, misinformation and prejudices, given that the data it’s trained on is initially implemented by humans, who naturally contain typical biases and misinformation found in society at large.
This can create a feedback loop where biases are amplified in AI outputs and absorbed by users, who may go on to adopt and reinforce them.
We’re already witnessing real-life examples of AI bias in action. AI has been shown to unfairly discriminate against certain groups when used in hiring and recruitment processes, such as in the case of Amazon’s systems unfairly discriminating against female applicants due to the AI’s awareness of tech as a historically male-dominated industry.
As such, it wouldn’t be a far reach to assume that AI is also inferring data about race, sexual orientation or age from candidates’ profiles and harnessing that data to perpetuate discriminatory attitudes and practices in recruitment.
For HR teams and organisations, this poses a very real problem. AI can certainly be used to streamline processes and remove some of the administrative strain from the recruitment process. But monitoring instances of unconscious bias can be difficult when there’s little transparency on how large language models (LLMs) produce the results they do, or exactly what kinds of data they’ve been trained on.
Without careful regulations and monitoring in place, AI could potentially undermine efforts to build a fairer and more equitable workplace, instead reinforcing existing prejudices in society.
The final risk factor and ethical hurdle of widespread AI use is its staggering impact on the environment.
By 2030, reports estimate that AI data centres could consume 945 terawatt-hours of electricity every year. That’s almost triple the combined electricity use of Pakistan, Bangladesh and Nigeria.
Data centres also use significant quantities of water and require large land footprints in order to operate, putting considerable strain on local resources and supply chains.
According to the UN, the main reason why AI is so resource-intensive isn’t solely due to building and training AI models; in fact, 80 to 90% of the total energy demand for AI comes down to day-to-day use accounts, like asking chatbots questions or generating images. With increased energy requirements comes increased reliance on fossil fuels, thus accelerating greenhouse emissions and climate change.
On top of all this is a worrying lack of transparency from AI developers, with one study finding that only 14.9% of developers have directly or indirectly released environment impact data, with the vast majority (84.1%) choosing not to disclose any data relating to their impact on the environment at all.
This lack of transparency makes it incredibly difficult to gauge the true impact of AI on the environment and presents a challenge for future regulation. However, there have been urgent calls for global reform to make AI models more efficient, responsible and sustainable to minimise negative impacts on the environment.
Despite the many risks, AI – when used correctly – can still be a force for good.
AI is already helping to deliver breakthroughs in various industries, including:
We’re then left with the key question: is it ethical to use AI? The realistic answer is that it depends.
Though it may be a bit of a cliché at this point, it still holds true that AI is just a tool. Tools can be used for a variety of applications, whether good or bad, and how they can assist or hamper our development is dependent on how we choose to harness them.
However, AI use is also becoming ubiquitous in modern life. For example, many organisations and universities now publishing official guidelines on how to use AI ethically and responsibly, acknowledging the fact that people can, and will, use it to aid their work. As a result, there’s an argument to be made that rather than trying to resist AI implementation, it’s best to embrace it and adapt to it within our means.
Fundamentally though, we can – and should – remember to put the human first, and place principles such as risk prevention, safety, fairness, responsibility and sustainability at the core of how we utilise AI in our daily lives, ensuring that AI is used to aid human achievement rather than diminish it.
AI offers many benefits, but it also comes with some caveats – which is why it’s essential to use it responsibly and to minimise negative consequences.
Some steps you can take to use AI more responsibly include the following:
While the threat of AI over jobs, the environment, and society remains significant, ethical AI use is still very much a possibility.
Keeping human creativity and judgement at the centre of what we do is absolutely critical. We shouldn’t lose sight of our abilities as a society to achieve amazing things; AI is simply another tool to help us achieve them, but only when we use it correctly.
Whatever the future of AI holds, there’s certainly no doubt that it’s here to stay and the onus is on us to harness it as thoughtfully and responsibly as possible.
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