Are humans doing enough to support the great AI workplace takeover?
"A fear born from a lack of knowledge and support means many employees are wary of AI and fear it could replace their role."
AI may be more under the microscope than ever before. But do we, as humans, really advocate for its success? It's a fairly common understanding that terminating the employment of a newly hired assistant after one or two small mistakes would seem unnecessarily harsh.
Yet, when it comes to AI, there is a much lower tolerance for error, and this isn’t just theoretical. Recent research found that the average tolerance rate for AI is 6.8%, whereas the average for human employees sits much higher at 11.8%.
This double standard raises a question: Are we subconsciously against AI success?
On the surface, the AI sector in the UK seems to be on a rapid, upward trajectory; attracting an average investment of around £200 million daily. Many jobs are being created as a result. However, beneath the high-level enthusiasm, there is scepticism, with data indicating less than half of the UK population trusts AI. It’s clear that there needs to be a mindset shift if we’re to truly reap the full benefits of AI.
AI dreams are distracting us from reality
AI headlines are often sensationalist, ranging from bold promises of fully self-driving cars to alarming reports of hallucinations appearing in court documents. These dramatic headlines are often defined by overpromise and therefore, feed negative perceptions that AI is underdelivering, or that the risks far outweigh the benefits.
Across many sectors, including healthcare, logistics and retail, AI is already delivering impressive, measurable results on a day-to-day basis, but these less publicised yet more meaningful, applications of AI are being overlooked.
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Take, for example, the Central and North-West London NHS Foundation Trust. By deploying AI agents, the Trust has automated a range of time-consuming manual processes, such as patient data entry, scheduling and administrative tasks. The results? Around £370,000 in manual effort saved a year and 56 hours a day freed up for healthcare professionals.
It’s imperative that the focus shifts from non-representative use cases that are creating a damaging narrative around the measurable impact of AI, to practical examples, recognising the true power of AI often lies in incremental, day-to-day operational improvements.
AI needs pilots to reach its full height
Immediately rushing into large-scale deployments, whether it be with LLMs or agentic systems, is one of the biggest mistakes a business can make with AI. Investing in AI comes with a high cost and cannot be done hastily. There needs to be careful integration within existing workflows, data systems and business processes to deliver ROI.
Short pilot phases with a clear roadmap to production are, therefore, essential for successful, long-term implementation. Running a focused pilot project serves to create a controlled environment for businesses to trial a new AI tool. This is a crucial step to de-risk integration as it provides an opportunity to troubleshoot issues and pivot strategy ahead of wider, scaled deployment of the technology.
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Employee confidence and buy-in will benefit from pilot phases, in conjunction with investment in thorough training initiatives. A fear born from a lack of knowledge and support in using AI technology means that many employees are wary of AI and default to the mindset that it could replace their role or devalue their expertise.
This isn’t a loose assumption– a staggering 73% of the UK public recently stated they haven’t received any AI education or training. By involving employees in pilot phases, businesses can measure their feedback on the new tool and provide training in the early stages of deployment so workers can confidently harness the technology to its full advantage.
Pilot phases aren’t just a key practical step in AI adoption, but a necessary cultural one. These fixed term experiments serve to build the confidence of teams, stakeholders and customers, remedying uncertainty ahead of widespread deployment.
Governance and transparency are imperative
When it comes to successful AI adoption, strong governance is non-negotiable. Measures must be embedded from the outset, not added on as an afterthought. The consequences of a lack of oversight are not to be underestimated – it can pose operational risks, inflict reputational harm, and even lead to legal consequences, as AI tools are frequently granted access to sensitive business and customer information.
Although AI tools, specifically agents, are increasingly autonomous, it is still necessary to have the presence of both a strong governance framework and human touch to ensure safe usage and to mitigate issues in real time.
Transparency and accountability also lay the groundwork for trust. Employees and customers need to understand exactly how AI is being used to trust it.
Businesses must be transparent about how they are using AI, how systems are monitored and what checks and balances are in place to ensure fairness and accountability. Innovation requires a transparent environment to thrive, as fear will be converted into confidence.
Future-proof AI implementation
Whilst challenges are inevitable as AI isn’t perfect and will make mistakes, especially in its early stages of deployment, the challenges can be managed. So long as AI is given the same grace period that would be offered to a new employee, taking this approach will help to establish strong foundations for long-term success and ROI.
AI shouldn’t be viewed as a direct replacement for human intelligence, and businesses must address this when deploying the technology. Instead, it should be recognised as a supportive tool that takes on time-consuming, administrative work, therefore allowing employees to focus on higher-value tasks such as orchestrating workflows and determining outcome-based KPIs.
Ultimately, ensuring AI’s long-term success in the workplace requires a thoughtful rollout and the right mindset from the teams using it.
Chris Ashley is VP Strategy & Business Development at Peak AI
