These are only select examples; every pollinator dependent crop faces similar problems.
Traditionally, farmers have placed beehives in orchards and hoped for the best, but bees don’t always visit the right flowers at the right time - this creates a major pollination gap.
AI powered pollinator management can make a difference to these gaps. By using technology to monitor bee activity and pollination patterns in real time (like our Polly™ device), growers can gain a clear picture of what's working, what isn’t, and when exactly to intervene. It’s a smarter, more precise way to manage pollination and ensure better yields in an increasingly uncertain climate.
AI is rapidly transforming the way pollination is managed in agriculture. As natural pollinators continue to decline, AI-powered solutions are emerging as a critical tool to protect crop yields and prevent food security challenges. Technologies such as drone-assisted pollination, predictive analytics, and digital twins are already improving pollination efficiency and resilience.
In 2023, researchers at Monash University published a study using recordings of activity to track pollinators like honeybees and hoverflies, creating a database of over 2,000 insect flight paths on a commercial strawberry farm. The Hebrew University of Jerusalem also unveiled an AI-based bee tracking system, in 2024, designed to optimise pollination in complex crops like dates and avocados.
These innovations help maintain consistent yields, whilst offering more sustainable and precise farming methods, by reducing pesticide use and optimising pollinator activity.
Companies and research institutions globally are actively exploring AI-driven systems to future-proof their operations. As the market for AI in agriculture grows, more agribusinesses are recognising the value of adopting these technologies to stay competitive, increase productivity, and contribute to a more resilient food system.
Whilst improving pollination practices is critical, our industry must be careful not to disrupt the natural balance by chasing only short-term solutions. The goal should be to create the right conditions and timing for natural (or managed) pollinator activity, to allow pollinators like honeybees, bumblebees, and wild insects to do their job effectively.
We can use data-driven decisions to improve hive placement, timing, and overall pollinator management. These steps can offer quick wins, especially when weather conditions are unpredictable. But we shouldn’t shift our focus entirely toward artificial solutions such as drones or mechanical blowers; these tools should be sought as a short term, emergency solution for example during poor weather spells.
Nature has already given us the best pollinators and while replacing them may seem productive for farms, pollinators also play a critical role in supporting wild plants and ecosystems. If we remove them from the equation, we risk damaging not only crop yields, but biodiversity too.
At AgriSound, we believe in using AI responsibly, not as a replacement for nature. We encourage the use of AI to understand and support pollinators; it can help us to study bee behaviour, monitor activity, and identify the best conditions for pollination. With this knowledge, we can create environments where bees thrive and continue to do what they do best: pollinate. This way, we improve yields and protect the natural biodiverse systems which sustain us.
We support food growers and organisations worldwide to manage their pollination practices using the power of AI technology, through our Polly™ device. Having real-time data can be critical in establishing sustainable farming practices rapidly, to manage their biodiverse landscapes efficiently. Learn more by getting in touch today.