Inclusive AI in Transformation: Ensuring Equity and Diversity in Digital Change

Imagine this: You’re having a heart attack and rushed to the hospital. Your treatment will depend on decisions made by AI systems designed to assess urgency, predict outcomes, and allocate resources. But what if that AI system is biased? What if the algorithm is more likely to prioritize patients from certain demographics over others because of flawed data or systemic biases embedded in the system?

This scenario isn’t just hypothetical. It’s a real risk we face today as AI systems increasingly shape how businesses operate, innovate, and interact with the world. And while AI offers incredible potential to improve lives, it also carries significant risks if we fail to address the issue of bias. The question we must ask is: Are we building AI systems that work for everyone, or are we unknowingly embedding biases that could harm millions?

With AI adoption accelerating at a staggering pace, it’s clear that AI is here to stay. But here’s the catch: AI is only as unbiased as the data and processes that shape it. When left unchecked, AI systems can perpetuate harmful biases, leading to unfair outcomes that damage reputations, undermine employee engagement, and even result in legal challenges.

Why Diversity in AI Matters

AI systems are increasingly making decisions that impact various aspects of our lives ; from hiring and medical treatment to financial services and social welfare. The risks of biased AI are real and alarming. In fact, AI-driven decision-making has already shown how easily inequity can be perpetuated on a massive scale.

Consider this: An AI-powered recruitment tool that systematically discriminates against qualified candidates from underrepresented groups because it was trained on biased historical data. This situation isn’t just hypothetical. In 2015, Amazon built an AI-based recruitment tool that was biased against female applicants. Engineers tried to fix the bias but there was no way to guarantee it was eliminated so Amazon abandoned the tool.

Ignoring these biases doesn’t just create unfair outcomes. It undermines your organization’s ability to innovate, damages your reputation, and exposes you to significant legal and compliance risks. Given these substantial risks, understanding the importance of DEI in AI systems is more important than ever.

The Cost of Ignoring DEI in AI

Organizations that overlook Diversity, Equity, and Inclusion (DEI) in their AI systems are taking a massive risk. Biased AI systems can lead to:

• Legal challenges and compliance failures.
• Loss of trust from customers, employees, and stakeholders.
• Reduced innovation and competitive edge.
• Poor customer experiences and market exclusion.
• Workplace inequality and skills gaps.

The implications are clear: If you’re not actively working to make your AI systems inclusive, you’re not just missing an opportunity; you’re creating a risk.

Building a Better Future

The conversation about AI and DEI is not just about avoiding risk; it’s about unlocking the true potential of technology to serve everyone fairly. Organizations that actively work to identify and eliminate biases are paving the way for more innovative, ethical, and effective AI systems.

Building inclusive AI is about ensuring that technology reflects a diverse range of experiences and perspectives. It’s about creating systems that are fair, ethical, and aligned with the values of equity and belonging. The future of AI depends on our ability to recognize its potential pitfalls and proactively address them.

Learn More

I will be diving into these topics further at the Business Change and Transformation 2025 conference in London this June, where I will present “Inclusive AI in Transformation: Ensuring Equity and Diversity in Digital Change.” This session will provide valuable insights for business leaders, technologists, change managers, and DEI advocates looking to create AI systems that are both effective and ethical.

If you care about responsible AI, equity, and creating real change, this is a session you won’t want to miss. Let’s work together to transform AI for the better because the decisions we make now will shape the future.

During my session, I will cover:

• Why addressing diversity and inclusion in AI is a business imperative.
• Examples of AI bias and what we can learn from them (with some surprising case studies!).
• The practical steps organizations can take to identify and mitigate AI bias.
• How to cultivate an inclusive leadership mindset and build a feedback culture that drives better outcomes.

Kelly Brogdon Geyer, a People and Culture Transformation Leader with a passion for Diversity, Equity, Inclusion and Belonging (DEIB). She has extensive experience leading global change initiatives and has successfully managed culture change, mergers & acquisitions, IT implementations, HR transformations, and standardization efforts across multiple industries.

Her thought leadership is featured in prominent publications such as Change Management Review, where she has written about cultural agility and navigating cross-cultural challenges.  She will also be featured in the Wired for Change podcast in the spring.

With a passion for bridging DEIB principles with technological advancement, Kelly’s work emphasizes creating equitable, innovative solutions that align with the future of business transformation.

Connect with her on LinkedIn: Kelly Brogdon Geyer