AI is already transforming how businesses operate, but what does that really mean for jobs, people, and skills? 

In partnership with KTSL and AstraZeneca, we’re hosting the “Will AI Replace Me?” webinar to cut through the hype and have an honest conversation about how AI is reshaping the workplace and how organisations can use it responsibly, fairly, and effectively. 

Drawing on hands-on AI experience, Aaron Perrott, CTO at KTSL, believes the real impact of AI isn’t about replacing people, it’s about removing “toil”. 

“AI is removing a lot of the jobs we don’t particularly want to do — the repetitive, labour-intensive tasks — so people can focus on where they add real value.” 

What jobs will AI replace? 

AI is strongest where work is repetitive, consistent, and language-based. This includes tasks such as: 

• ➡️ Writing and summarising documents 
• ➡️ Processing large volumes of data 
• ➡️ Responding to common customer or internal queries 
• ➡️ Reviewing legal, insurance, or compliance documentation 

As Aaron explains, AI can perform these tasks consistently, without fatigue, making it well suited to first-line or admin-heavy roles. As a result, some roles will change significantly, particularly at junior levels. 

But that doesn’t mean humans are being replaced. 

Jobs that AI can’t replace 

From our conversation with KTSL we discussed that the skills that matter most in an AI-driven world are deeply human. 

“AI can give you the data — but it’s your interpretation of that data that becomes critical.” 

Jobs that AI can’t replace are those requiring: 

• ➡️ Empathy, judgement, and relationship-building 
• ➡️ Contextual decision-making 
• ➡️ Creativity and imagination 
• ➡️ Adapting communication to different people and situations 
• 
  

These skills become more valuable as AI takes on routine work, making human capability the real differentiator. 

How can AI help my business? 

When used correctly, AI can help businesses: 

• ➡️ Save time on repetitive tasks and documentation 
• ➡️ Improve knowledge sharing and training 
• ➡️ Support diverse learning and communication styles 
• ➡️ Enable more inclusive and flexible ways of working 
• 
  

AI can also help break down traditional barriers by re-framing technical information for different audiences, making workplaces more accessible for non-technical teams and diverse talent. 

However, KTSL emphasises the importance of using the right AI for the right purpose, alongside strong governance and clear boundaries between public and workplace AI tools. 

Using the right AI, the right way 

KTSL is clear that one of the biggest risks with AI adoption isn’t the technology itself, it’s how and where it’s used. 

Not all AI tools are designed for the same purpose. Public AI platforms are trained on vast amounts of open data and are built to give general responses. While useful for learning or exploration, they are not appropriate for handling business-critical or sensitive information. 

“You have to use the right AI for the right job and understand how that model was designed to behave and what data it was trained on.” 

In contrast, workplace AI tools can be configured to operate within an organisation’s own data environment, ensuring responses are based only on approved, trusted information. This reduces the risk of misinformation, data leakage, and unintended bias, while also making AI far more relevant to the business context. 

Strong governance is essential. KTSL discussed having clear guidelines around: 

• ➡️ Which AI tools employees should use at work 
• ➡️ What data can and cannot be shared with AI systems 
• ➡️ How outputs are reviewed, validated, and challenged 
• ➡️ Who is responsible for overseeing AI use and impact 
• 
  

Without these guardrails, organisations risk exposing sensitive data, embedding bias at scale, or relying on outputs that haven’t been properly verified. 

Most importantly, AI should support human decision-making, not replace it. Governance ensures people remain accountable and that we are using AI to enhance judgement, not outsource it. 

Why equity and bias must be built into AI 

AI systems are shaped by the data they are trained on, which means bias can easily be scaled if equity isn’t considered from the start. 

“It becomes much easier to force bias into AI if you’re not careful about the data and the model you’re using.” 

This is why KTSL advocates for human oversight, diverse input, and ethical governance to ensure AI supports fair outcomes, not just efficient ones. 

Join the conversation 

The “Will AI Replace Me?” webinar will explore these themes in more depth, from the future of jobs to AI bias, inclusion, and essential human skills. 

📅 Tuesday 27th January 2026 | 12:00 PM (45 minutes) 
🎤 Hosted by Simone Roche MBE 
🤝 In partnership with KTSL and AstraZeneca 

Join us for a practical, people-focused discussion on how businesses can move forward with AI: responsibly, inclusively, and with confidence. 🚀 

Want to find out more please contact: hello@ktsl.com