This is where alliances become broader and transboundary: Kay Firth-Butterfield is a name that almost every person across the globe would recognize as a leader in ethical artificial intelligence and is perhaps the most prestigious voice in AI governance today. Formerly head of AI and Machine Learning at the World Economic Forum (WEF), she has made a lifelong career helping ensure that AI benefits the world rather than devastates it.

In this exclusive interview, we spoke with Kay regarding generative AI, the development of the Metaverse, and the ways in which organizations can overcome various challenges and opportunities within the scope of digital transformation.

Understanding Generative AI: Promise and Pitfalls

Generative AI took the world by storm, but there are still people who fail to fully grasp how it really works and why it is different. How would you explain it? 

Why such a game changer?

In your own words, say the following: Generative AI promises to be the next transformation in artificial intelligence. Unlike the classical AI, which has its own predefined rules, generative AI can create novel content-new text, image, or even code-according to the prompt a user provides. At the core of generative AI is predicting the next word in a sequence. This prediction is based on patterns learned from analyzing massive datasets, often containing everything publicly available over the internet. These are called large language models (LLMs).

However, there’s a catch: these models sometimes “hallucinate”, meaning they generate false or misleading information. This is a major concern because AI-generated errors can spread rapidly, polluting future datasets. Ensuring accuracy and trust in AI outputs remains one of the biggest challenges in the field.

Another issue is copyright and intellectual property. Many AI models are trained on protected material without explicit permission, leading to legal battles. We’re likely to see more regulation in this space soon.

The Societal and Business Impact of Generative AI

What are the biggest benefits of generative AI for businesses and society? And what risks must we address to ensure fairness?

Generative AI’s democratization is one of the most exciting aspects. Even small companies in the past that would not have been able to afford advanced AI tools could now use them for marketing, customer services, and even coding.

But there’s a problem: data bias. Most AI models are trained on Western-centric datasets, primarily from the U.S. and Europe. This creates a form of “digital colonization”, where AI outputs reflect a narrow cultural perspective. If we want AI to serve the global population fairly, we need more diverse training data.

Another challenge is job displacement. It is true that AI can automate a large number of tasks, but failing to come up with appropriate policies will definitely lead to unemployment everywhere. It is the responsibility of the government and business to provide reskilling programs for workers and ensure that AI complements human labor instead of totally replacing it.

The Metaverse: Hype vs. Reality

The Metaverse has seen cycles of excitement and skepticism. Where do you see it heading in the next five years?

We’re currently in a “Metaverse winter”—a period of lowered expectations after the initial hype. While early visions promised fully immersive digital worlds (think Ready Player One), the reality is more gradual.

That said, the Metaverse still holds huge potential for business:

• Virtual Retail: Imagine trying on clothes in a 3D store or feeling fabric textures through haptic feedback.
• Remote Work: Instead of flat video calls, teams could collaborate in virtual offices with spatial interactions.
• Training & Education: Medical students could practice surgeries in VR, and engineers could simulate complex machinery.

However, creating truly immersive experiences requires massive computing power and creative investment. We’re still years away from mainstream adoption, but the foundational work is happening now.

The Next Decade: AI, Quantum Computing, and Ethical Risks

Which emerging technologies will have the biggest global impact in the next 10 years?

1. Generative AI will continue evolving, enabling natural language programming—where people build software just by speaking or typing requests.
2. AI-powered Synthetic Biology could revolutionize medicine, agriculture, and materials science.
3. Quantum Computing + AI may unlock breakthroughs in drug discovery and climate modeling, but also pose security risks.
4. The Internet of Things (IoT) will expand, but with greater concerns around data privacy and cybersecurity.

One critical issue is AI-generated data pollution. As machines produce more content than humans, we risk a feedback loop where AI trains on its own flawed outputs. Ensuring data integrity will be crucial.

How Businesses Should Approach AI Adoption

What’s your advice for companies navigating digital transformation?

1. Don’t Ignore AI – Like Kodak missing the digital camera revolution, businesses that avoid AI risk obsolescence.
2. Move Strategically – Avoid rushing into poorly matched AI solutions. Every adoption should align with business goals.
3. Ask Tough Questions – Hold AI vendors accountable. If you lack in-house expertise, hire consultants to evaluate systems.
4. Plan for Ethics & Compliance – Ensure AI use aligns with regulations and ethical standards to avoid reputational damage.

Final Thoughts: A Balanced Approach to AI’s Future

AI is changing our world faster than anything that has come before it. The opportunities are endless, but so are the risks, from layoff situations to prejudiced algorithms. Solution: responsible innovation-Acknowledging AI’s promise while actively dealing with its problems. 

Kay Firth-Butterfield said, “We must ensure AI serves humanity, not the other way around.” The next 10 years will test our balance beam, but with utmost intention, an AI future can be created for the benefit of all.