The Power of AI Done Well: Emerging trends to feel excited about
In our previous post, we explored how values-driven leadership is reshaping the AI landscape not through spectacle or scale, but through steady, principled innovation. Now, we look ahead.
Amid the noise of hype cycles and industry buzzwords, it can be hard to know which AI trends truly matter. But our Top 33 see beyond the headlines. They’re not only tracking where the field is headed, they’re shaping it. And they’re most excited about trends that are inclusive, impactful, and grounded in real-world possibility.
This post shines a light on the emerging developments that are energising responsible AI practitioners worldwide and the values driving them forward.
AI for Planet and People
Across the board, our nominees highlighted climate action, sustainability, and healthcare as the most promising frontiers of AI. These are areas where the stakes are high—but so is the potential for progress. From optimising energy use to enabling predictive modelling for disaster management, AI is already helping turn climate ambition into measurable action.
The shift toward sustainable AI, including powering AI with renewable energy, is also gaining momentum, as governments and companies respond to growing public demand for accountability in emissions-heavy tech sectors.
Generative AI as a Catalyst for Creativity and Access
Generative AI was described by our community not just as a productivity tool, but as a catalyst of human creativity. From transforming how we diagnose and treat illness to unlocking new approaches in design, science, and storytelling, these technologies are reshaping the boundaries of human potential.
Critically, our nominees emphasise that the true promise of generative AI lies in its ability to democratise innovation offering smaller organisations, grassroots movements, and underrepresented creators access to capabilities that were once out of reach.
Automation as an Enhancer Not a Replacement
Contrary to predictions about job losses, our community sees AI-driven automation as an opportunity to enhance not replace human capacity. By handling repetitive or low-value tasks, automation has the potential to free people up to focus on higher-impact, human-centred work.
Large Language Models (LLMs), when deployed responsibly, have the power to evolve labour markets, create demand for new skills, and even reframe how we think about work and leisure in the long term.
Building the Ecosystem, Not Just the Tool
Perhaps the most powerful shift our community noted is a growing recognition that AI is not a plug-and-play solution. Responsible, effective AI takes time, training, and investment not just in the tool, but in the ecosystem around it.
That includes:
Rigorous testing and bias audits
Clear governance and accountability structures
Ongoing staff training and change management
Embedding responsibility, ethical design, equity and inclusivity from the start
As fine-tuning and training AI models becomes more affordable, more organisations will be able to build context-specific, values-aligned tools expanding the reach and relevance of AI systems around the world.
What’s Next
As these trends unfold, the stakes remain high: innovation without integrity can cause harm just as quickly as it can create good. That’s why the next part of our series focuses on a question our nominees return to again and again: how do we balance innovation with ethics?
Join us for Part 6: Balancing Innovation with Ethics, where we dive into how our Top 33 keep responsibility at the centre even in fast-moving, high-stakes environments.
Because doing AI well isn’t about slowing down progress, it’s about making it work for all.
