4 ways EMEA organisations can prioritise responsible AI

AI is rapidly becoming a staple in business operations. As its use grows, so do considerations around deploying it responsibly and ethically. According to recent research by Stanford University, over half of European organisations worry about AI's impact on privacy and data governance. Another 45% question the reliability of AI, and 49% have doubts about AI's transparency.

It’s easy to understand the rush to implement new technologies that promise to automate routine tasks and surface new insights, but the dilemma is finding a balance between driving innovation and safeguarding against potential risks. Biased, opaque, or poorly governed AI systems can quickly erode trust among customers and employees.

Organisations across Europe, the Middle East, and Africa (EMEA) wanting to put AI to work ethically need to establish a bedrock of sound principles. The following four considerations provide a foundation for putting responsible AI into practice.

1. Put people first

A core principle is keeping human needs at the centre of AI development. Rather than implementing technology for innovation’s sake, AI needs to solve real user problems and frictions. A human-centred approach means establishing ethical standards throughout the entire lifecycle: from the initial design phase to deployment and continuous improvement.

With this in mind, UNESCO’s ethical AI framework provides a useful starting point for organisations to follow. This includes fairness and non-discrimination, transparency, accountability, and human oversight.

2. Make AI inclusive

Unlike other technologies, AI learns from the data it’s trained on and the people who develop it. If data and teams lack diversity, the resulting AI will likely show biases that lead to unfair treatment of underrepresented groups. As AI is increasingly deployed in high-stakes domains like customer service and job hiring, getting it right is vital to avoid compounding social inequities.

Diversity and representation must be top of mind to create AI that truly serves everyone. Development teams and data need to encompass individuals across cultures, genders, ages, and areas of expertise to bring together a multitude of perspectives that surface and mitigate unconscious biases.

By prioritising diversity and representation at every stage—from team composition to user testing—organisations can create AI systems that work better for all. The goal should be to democratise access to AI's benefits, ensuring the technology is accessible to and inclusive of every customer, employee, and stakeholder that businesses serve.

3. Build trust with transparency

For AI to earn trust at scale, there needs to be an understanding of how it works. Documentation on how models operate, their intended use cases, and limitations will be key to ensuring transparency around the technology. Over-communicating any uncertainties and limitations is also critical for employees and customers to have realistic expectations of what AI can and cannot do.

Hand-in-hand with transparency is robust accountability and governance. This includes oversight bodies and avenues for reporting issues. With this in mind, ServiceNow has set up internal bodies to oversee initiatives and help ensure they align with ethical standards in the AI community, enabling organisations to use its AI solutions with confidence.

4. Balance humans and machines

As advanced as they get, AI systems must collaborate with humans—not replace them. Organisations need visibility into where and how AI is being used, the ability to interpret its outputs, and power to adjust or override AI decisions when warranted.

Maintaining human judgment is especially important for AI use cases that can significantly impact lives. For example, a financial services company relying on AI to assess loan applications and make approvals may unfairly deny loans to qualified applicants. This lack of human judgment in the decision-making process could leave customers in a position of financial hardship, damage business reputation, and erode public trust.

Conducting ethical impact assessments and having mitigation plans in place can help ensure AI benefits humans—without harmful consequences. In practice, impact assessments mean taking stock of the potential risks both before and after an AI system is put into action. This is essential to ensure the technology stays in line with ethical standards throughout design, development, and deployment.

Bringing these principles together

Upholding responsible AI principles is an ongoing commitment. Organisations must set clear guidelines around human-centricity, inclusivity, accountability, and transparency to guide all AI initiatives going forward.

By taking these four considerations into account, EMEA businesses can begin to unlock AI's potential to create better experiences for all. The ethical path is the only route to building AI solutions that are widely trusted, valued, and future-proof.

Discover how ServiceNow can help put responsible AI to work for your organisation.