By Managing Partner Phillip Osborne
This year’s APAC Agri-Food Innovation Summit felt energising in a different way. Instead of the usual focus on funding cycles or high-level market hype, the conversations centred on practical innovation: addressing real-world challenges for smallholder farmers, exploring how CRISPR and AI can improve productivity, and thinking about how technology can make a tangible difference. It was a reminder that, as leaders, the most valuable innovation is the kind that can be applied and scaled effectively.
In past years, the sessions leaned heavily toward venture capital and alternative proteins. This time, the dialogue centred on the realities of Southeast Asia on how to improve productivity and livelihoods for smallholder farmers. As leaders, we often talk about transformation, but what resonated this year was a return to fundamentals: how agri-food innovation actually serves people, communities, and economies, not just investors.
CRISPR technology featured strongly again, but what stood out was how it’s now being paired with AI. The ability of AI to rapidly analyse data from CRISPR applications opens the door for faster, smarter progress, from developing disease-resistant crops to reducing fertiliser use. These technologies are no longer operating in isolation; their strength lies in how they work together. For senior agribusiness leaders, that convergence presents both opportunity and complexity. It’s one thing to invest in innovation; it’s another to lead teams capable of integrating it across scientific, commercial, and operational lines.
A session led by Bain & Company on AI adoption particularly struck a chord. Their view was that AI, at least for now, isn’t eliminating jobs, it’s changing how we work. The productivity gains are real, but they raise an important leadership question: how do we ensure those efficiencies lead to better outcomes, not just faster processes? For many businesses, the real benefit lies in freeing up time for customer engagement, strategic thinking, and problem-solving — the areas where human insight still makes the biggest difference.
Of course, the quality of AI-driven outcomes depends entirely on the quality of the data behind them. Whether you’re analysing large external datasets or your own business metrics, the old rule still applies: garbage in, garbage out. For leaders, the focus shouldn’t just be on adopting AI tools, but on ensuring the integrity and reliability of the data that fuels them.
What I took away from this year’s summit is that agri-food innovation is maturing, and the way we approach leadership in agribusiness is evolving with it. The excitement is still there, but it’s grounded in realism. We’re moving from speculative conversations to actionable progress, from vision statements to measurable value. For senior leaders, that shift calls for both curiosity and discipline: the curiosity to explore new technologies, and the discipline to apply them where they’ll make the most lasting impact.
If you’re navigating similar questions about leadership readiness, data capability, or innovation strategy in agribusiness, I’d welcome a conversation.
