Shashi Raghunandan, CEO of Oaken, is not only a successful businessman but also a hobby painter, a dedicated husband, and a dog lover. In addition to his role at Oaken, he sits on the board of MIFOS. With a diverse set of interests, Shashi brings a unique perspective to the business world, emphasizing the importance of work-life balance and giving back to the community.
The application of AI in agriculture has been a topic of great interest and excitement in recent years. The combination of increased data generation at the farm level, advancements in computing power, and improvements in technology has created new opportunities to produce more food more efficiently. AI technologies such as image recognition are already being used in industries like food processing, and there are many potential applications at the field level, from weed management to soil health.
Large enterprises with significant resources have been leading the way in implementing AI in agriculture. Companies like John Deere are working to bring autonomy to all stages of crop production, using technologies like auto-driving and image recognition to improve efficiency and productivity. However, SMBs in the agricultural industry face challenges in implementing AI due to limited resources and expertise, making it crucial for them to prioritize where to invest their dollars for the most immediate returns.
McKinsey has identified three key areas where AI can deliver significant returns for agribusinesses: R&D, Sales and Marketing, and Operational Excellence. SMBs, in particular, have the opportunity to benefit from implementing AI in operational excellence, which includes areas such as procurement, back office, and accounting. By streamlining repetitive tasks and workflows with AI, businesses can save time and resources and improve overall efficiency.
SMBs in the agricultural sector often struggle with inefficiencies in their operations, particularly when it comes to managing documents, contracts, and leases. AI can help in areas such as procurement by improving responses to RFPs, synthesizing contract terms, and identifying opportunities for value creation. By leveraging OCR technologies to automate tasks like reading legacy legal contracts, businesses can save time and reduce errors, leading to more efficient operations and potentially greater ROI.
To successfully implement AI, SMBs in the agricultural industry must prioritize organizing their data, identifying the right use cases for AI, and finding the right technology partners. By focusing on operational excellence, businesses can unlock the benefits of AI in their day-to-day operations, setting themselves up for long-term success. By taking these steps, organizations can not only improve efficiency and productivity but also empower their employees to use technology to their advantage and stay competitive in the evolving agricultural landscape.
