Seven tips to use AI safely at work 

While AI is transforming the workplace and opening new paths to productivity, additional safety considerations should be used when using AI at work.  

Research shows that while over 70% of companies globally use AI in the workplace, fewer than 40% report having clear organisational guidance on safe or responsible AI use.  

This guide outlines essential practices that will help you build a secure foundation for AI integration in your organisation. 

1. Understand data privacy policies 

What is data privacy in AI tools? 

One of the most significant risks associated with AI is how data is collected, stored, and reused. Many AI systems rely on large datasets to learn and improve, and publicly available tools often retain conversation history or use inputs for model training. 

This matters because studies show that over 40% of employees admit to sharing sensitive or work-related information with AI tools without employer approval, often without fully understanding where that data is stored or how it may be reused. When data is mishandled, it can expose organisations and individuals to security breaches, compliance violations, and reputational risk. 

How to implement this practice 

• Review the data retention and usage policies of any AI tool before using it 

• Check whether your organisation has approved specific AI platforms or issued AI usage guidelines 

• Never input confidential information, client data, credentials, or proprietary code into public AI tools

2. Implement verification protocols for AI-generated content 

AI has become a powerful tool for creating content, including text, images, and videos. While this can be incredibly useful, it also raises concerns about misinformation and deepfakes, which can spread rapidly across the internet.  

How to verify AI outputs: 

• Test all AI-generated code thoroughly; never use it without reviewing and testing  

• Verify statistics, studies, and data points through primary sources before including them in professional work  

• Implement a multi-stage review process that includes validation through human expertise  
   

3. Use AI to assist, not replace

Understanding AI’s limitations 

While AI tools can recognise patterns and automate tasks, they cannot assess nuance, intent, or ethical implications in the way humans can. 

Despite this, surveys show that nearly 64% of employees admit to putting less effort into their work, knowing they can rely on AI. This reliance has led to 57% making mistakes in their work 

Why human expertise is still important  

AI can help professionals with research, automating routine tasks, and offering alternative perspectives. It should not replace critical thinking, creativity, or responsibility. 

Over-reliance on AI can destroy core professional skills and introduce risk when AI systems are used to support high-stakes decisions without enough human oversight. 

How to maintain appropriate oversight 

• Treat AI outputs as inputs, not final answers 

• Maintain responsibility for decisions and outcomes in your work 

• Ensure you understand and can explain any AI-assisted work you deliver

4. Protect yourself from AI-enabled threats

What are AI-enabled threats?

AI has significantly increased the sophistication of cybercrime. Voice cloning, deepfake videos, and highly personalised phishing attacks now allow fraudsters to convincingly impersonate trusted individuals. 

AI-enabled fraud is projected to cost organisations $40 billion USD by 2027, and high-profile cases have shown how deepfake video calls have been used to authorise fraudulent transfers worth millions. 

How to protect yourself and your organisation 

• Apply verification checks to unusual requests involving payments, system access, or sensitive data 

• Remember that voices, videos, and caller IDs can all be convincingly disguised 

• Share threat intelligence and real-world examples within your teams to raise collective awareness

5. Foster transparency and accountability for AI-assisted work

Stakeholders need to understand when AI has been used, its limitations, and where human judgment applies. 

This is especially important given the number of employees concealing their AI usage at work, often due to unclear policies or fear of judgment. Lack of transparency increases risk. 

What AI transparency looks like in practice 

• Document when AI tools assist in code generation and ensure you can maintain the output 

• Clearly indicate when AI has been used to draft or structure content, with independent accuracy checks 

• Clarify AI usage expectations in project scopes, contracts, or internal documentation 

6. Encourage organisational AI literacy

What is AI literacy in professional contexts? 

AI literacy goes beyond knowing how to use tools. It includes understanding risks, limitations, ethical considerations, and appropriate use cases. 

Henry Duddy, FDM’s Senior Delivery Consultant, shares, “Successful AI adoption isn’t determined by the technology but by the people using it. Without a coordinated investment in graduate development and workforce upskilling, companies risk falling behind competitors who pair technology with human capability. Building a future‑ready workforce means acting now—upskilling, reskilling, and creating real hands‑on experience pathways that empower people to work confidently and responsibly with AI.”   

How to build AI literacy 

• Establish clear AI usage guidelines within projects 

• Share insights about AI capabilities and limitations with colleagues 

• Discuss both opportunities and risks openly to build critical evaluation skills 

• Use organisational AI policies as a foundation for ethical practice
   

7. Commit to continuous learning in AI governance

The AI landscape evolves rapidly. Tools that met security standards months ago may have changed their data policies. 

For tech professionals, committing to continuous learning in AI governance, security, and ethics creates a long-term career advantage. Organisations increasingly seek professionals who understand not just how to use AI, but how to deploy it responsibly. 

How to stay current 

• Attend webinars, workshops, or training on AI ethics and security 

• Engage with peers to share experiences, challenges, and emerging best practices
   

At FDM, we’re committed to developing AI-enabled talent who can confidently navigate this evolving tech landscape. FDM is uniquely positioned to meet this demand by developing consultants with hands-on AI capabilities through agile Pods (proof of concepts), real-world projects, and embedded AI coaching. 

Summary 

AI is transforming the tech industry, creating both opportunity and responsibility. The professionals who thrive in AI-augmented environments are those who understand its capabilities and limitations, while contributing to responsible AI practices within their organisations. 

The demand for professionals who are not just AI-aware but AI-native is growing rapidly. At FDM, we believe in humans and AI, together. We give businesses the creativity, skills, speed, and scale they need to stay ahead. 

AI solutions should be simple, useful, and designed around your business. While many consultancies focus on theoretical models, expensive architecture, and abstract transformation, FDM prioritisespractical delivery. 

Ready to build an AI-native workforce? Discover how FDM can equip your teams with the skills to turn AI potential into business results.