Breaking Barriers: Women, AI, and the New Frontier of Creativity

In this episode of Women with AI, host Joanna Shilton chats with Emma Wharton-Love, co-founder of Spark, an AI consultancy empowering creative and marketing teams.

Emma shares her unconventional career journey—from leading hybrid working initiatives in Parliament to founding Spark alongside her husband, Jules, where together, they demystify AI’s role in streamlining creative processes, tackling misconceptions, and highlighting its potential to enhance, not replace, human creativity.

With actionable insights on AI tools, business transformation, and the importance of blending human ingenuity with cutting-edge technology, this conversation is a must-listen for anyone navigating the future of work and creativity.

Takeaways:

• Emma emphasises that AI can streamline repetitive tasks, allowing more time for creativity.
• Understanding AI tools is crucial for creative agencies to stay competitive in the evolving landscape.
• AI should be seen as an assistant that enhances human creativity rather than replacing it.
• The integration of AI into the creative process can lead to innovative and original ideas.
• Emma's journey reflects the importance of adaptability and continuous skill development in one's career.
• The collaborative potential between AI tools and human ingenuity will define future creative success.

Links relevant to this episode:

• Subscribe to Creative AI News — Spark — AI Partners for Creative Agencies - A newsletter designed to cut through the AI hype and give creatives the AI news that matters to them.
• Sign up for the the next edition of What's new in Creative AI
• AI for Creatives from Spark YouTube channel
• Nadio Granata
• We Are Spark AI | LinkedIn
• Emma Wharton-Love | LinkedIn
• Events — Spark — AI Partners for Creative Agencies
• Invisible Women | Caroline Criado Perez - The #1 Sunday Times best-seller, INVISIBLE WOMEN: Exposing Data Bias in a World Designed for Men (Chatto & Windus, Abrams, 2019), highlights the systematic biases behind the data and assumptions impacting our everyday lives.