By Joanna Julie Dragsdal Nielsen

On a sunny Monday afternoon in May, Female Leadership Academy gathered curious minds at Accenture’s headquarters in Copenhagen for honest reflections and valuable insights. The event -aptly titled AI Needs Her – explored the intersection of AI, leadership, and inclusion. And it delivered.

AI is no longer just a technological breakthrough. It’s a leadership challenge – one with massive potential if handled with care, collaboration, and foresight. That was one of the clearest insights from the powerful session, which brought together leading voices in tech to explore why women’s involvement in AI isn’t optional – it’s essential.

Throughout the event, one truth kept surfacing: AI is shaping our future. But who is shaping AI?

 

A panel of pioneers

The afternoon’s main event was a panel conversation moderated by Nina Victoria Bergsten, featuring:

• Mette Kaagaard – CEO, Microsoft Denmark and Iceland
• Kate Zeberg-Clausen – Senior Manager, Data & AI at Accenture Nordics
• Ditte Fenger – Independent Consultant and Advisor
• Kasper Tjørntved Davidsen – CIO, Topdanmark

Together, they offered a broad spectrum of insights – from corporate leadership and strategy to agile transformation and public-sector digitalization. Rather than delivering isolated views, the panel leaned into dialogue: building on each other’s perspectives, supporting key points, and co-creating an open and layered conversation.

The core message was clear: AI will touch every corner of our society. And if we want those systems to be fair, inclusive, and future-ready, women must help shape them.

 

Technology with a human touch

Kasper Tjørntved Davidsen brought a grounded perspective from the insurance sector, where he led the implementation of Denmark’s first generative AI chatbot in financial services. But his focus wasn’t technical. It was human.

Kasper spoke about the responsibility that comes with launching something new – especially when it requires trust from both organizations and customers. To Kasper, the risk was worth it. Because at its core, AI isn’t just technical. It’s a tool – and a democratic one. Its real value lies in how it empowers people.

Kasper emphasized the importance of making AI accessible to everyone — not just to developers or data teams, but to individuals across roles, sectors, and backgrounds. But with accessibility comes responsibility: AI is trained on data, and data reflects society. Without conscious oversight, it can easily reproduce and amplify inequality. He highlighted gender and racial biases embedded in large language models (LLMs), reminding us that if we don’t challenge what’s built in, we’ll scale what we’ve inherited.

 

Bias isn’t just a bug – it’s a design flaw

This call to awareness was echoed by the entire panel. Mette Kaagaard – who leads Microsoft in Denmark and Iceland – underlined that representation in AI development is about far more than equity. It’s about shaping systems that influence who gets hired, who gets healthcare, and who gets heard. Without inclusion from the start, we risk coding discrimination into everyday life.

Kate Zeberg-Clausen added nuance to the conversation by raising an often-overlooked point: AI’s environmental impact. As we build larger and more powerful models, sustainability must be part of the strategy. She also recommended Invisible Women by Caroline Criado Perez – a reminder that biased data isn’t a technical problem; it’s a cultural inheritance that needs deliberate redirection.

Ditte Fenger built on this by drawing attention to early influences. Gender bias in AI is linked to a broader pattern of social conditioning – from family dynamics to education. She highlighted how women’s underrepresentation in tech is less about ability and more about the structural factors that shape confidence and access. For AI to serve society well, we need to encourage experimentation and foster psychological safety – especially for those entering the field from non-technical backgrounds.

 

A field that’s still forming

Despite the complexity of these themes, the panel carried a tone of optimism. Mette noted that AI is still so new that it offers an equal playing field. No one has all the answers, and that makes it the perfect time to get involved – not despite your inexperience, but because of it.

Kate encouraged attendees to start simply: reach out to someone who’s experimenting with AI, ask questions, and try things. Ditte added that learning how to prompt – how to communicate effectively with AI – is a skill in itself, and an ideal first step for anyone looking to grow in this space. And yes, even seasoned leaders are still figuring it out. Mette shared that she still types please when using ChatGPT – a small sign of the humility and humanity that ran through the entire discussion.

 

Start with education — and start early

Building inclusive AI starts long before product development. Several panelists stressed the need for AI literacy and gender-aware STEM education – not just in universities, but in primary schools. Ditte emphasized the need to better support educators so they can introduce AI in ways that speak to a broader range of learners.

Kasper echoed this with urgency, pointing to international trends where AI is becoming embedded in early education. If we want to prepare future generations not just to use AI, but to shape it, we must act now – because falling behind isn’t just a tech risk, it’s a democratic one.

 

A shared responsibility – and a shared opportunity

As the panel wrapped up, the mood shifted from curiosity to commitment. No single organization or individual can guarantee that AI is inclusive, sustainable, or fair. But together – across sectors, genders, and skill sets – we can build systems that reflect the best of what technology can be. What’s needed is not perfection, but participation. From encouraging women to take small steps into the AI space to raising awareness of bias and embedding AI into education, the conversation offered practical starting points – and an open invitation.

The final lightning round brought lightness and clarity: tools the speakers couldn’t live without (ChatGPT, Copilot, Perplexity), lessons learned (confidence over competence), and hopes for the future (unpredictable, unlimited, for everyone).

 

And that’s where the event left us: not with final answers, but with a spark – a call to explore, to ask, and to lead.

Because AI doesn’t just need engineers.
It needs curiosity, ethics, leadership, and courage.
It needs her.

And she’s already here – learning, challenging, building, and shaping what comes next.