Written by: Vinay Kapoor, Expana Chief Product Officer
What if I told you that you could save 20% of your costs and improve your margins? Would it warrant your attention? What if I told you that the solution that offers these breakthrough savings is one of the most popular trends in tech and simultaneously the most poorly implemented solution. You probably know by now that we are talking about AI.
From autonomous tractors delivering 20% savings to savings via developer productivity, we are at an inflection point with AI where the cost of experimentation and technical bar of using AI to improve productivity is helping early movers widen margins, while laggards face shrinking share. In a sector where a few basis points decide profitability, “good enough” data, and intuition are no longer enough.
Yet, according to a recent study in Canada, only 12.2% of businesses reported using AI in producing goods or delivery services. Everyone’s racing to deploy AI, but few are crossing the finish line with anything that actually works.
Developing an effective AI business strategy
The biggest traps that most businesses fall into when trying to introduce AI are the failure to do the groundwork, and a failure to develop an effective strategy.
The work should start with the development of an effective AI business strategy – a company-wide, forward-looking plan that aligns AI capabilities and projects with your core goals. It is important that the strategy includes the following key components:
- A clear vision, prioritize high-impact use cases (that match your data maturity and risk appetite)
- Identified investments in enabling foundations (data assets, talent, governance and ethics)
- An adoption plan with ROI metrics
Our vision at Expana is to be “Your Market Intelligence Partner, Guiding the Decisions that Feed Our World”. This spans beyond just providing you cutting edge data and analytics. Our aim is to truly help you transform your organization to be in the top 10th percentile performers, by effectively using data and AI to develop effective supply chain strategy.
AI is deeply embedded in most of our business operations and our customers have had the benefit of being able to leverage AI for their decision making for many years. From our cutting-edge forecasting, that uses sophisticated AI models tuned to each specific commodity, to our cost modeling functionality, we have helped thousands of customers make the right commercial decision at the right time.
Our AI strategy recognizes that the most effective outcomes are achieved when people and machines work together, the principle of Augmented Intelligence. Steve Jobs once famously said “What a computer is to me is… the equivalent of a bicycle for our minds.” How can AI be used to further improve abilities of the experts, as opposed to falling into the trap of replacing your experts. We follow the same strategy in our forecasting product, where our core forecasts are developed through a collaboration between our experts and AI models. The AI models suggest several scenarios and outcomes and then the human and AI work together to produce the right recommendation, with the human as a supervisor and the AI as the collaborative worker.
Implementing an AI Roadmap
An AI strategy is a great start and should be followed with a clear AI roadmap for the organization with initiatives that are tied to ROI and clear business outcomes. A key area to pay attention to is identifying which use cases are ripe for GenAI and which ones benefit from more traditional AI models.
At Expana, our forecasting uses several traditional AI models that work with our experts collaboratively. This is a great use case for using models trained on specific commodities as you need to hyper-tune the model to individual nuances. We are also working on some cutting-edge insight capabilities that rely on generative AI models. The latest wave of GenAI models are particularly well suited to summarization and insight generation use cases. Since accuracy and trust worthiness is crucial in our industry, we at Expana can point GenAI models to our abundant proprietary data and build guardrails to ensure that users are able to take away real, actionable insights. We are also developing tools that will dramatically lower the bar of entry for new professionals entering the AgriFood workforce, helping to address a critical skills gap in this industry.
The Expana platform also uses AI for recommendation of related news, time series and forecasts, so you have an experience very similar to an online shopping experience, where a recommendation engine suggests similar or complementary products based on your search. These are all great tools to help you transform your business into a cutting-edge operation that uses all available innovation to drive better outcomes.
Key takeaways
So where should you start? I leave you with specific takeaways that you can implement starting today:
- Develop an AI Strategy for your business by identifying quick-win use cases tied to specific ROI
- Based on your AI strategy, implement an AI Roadmap
- Within agrifood, use the new Expana platform and its ready-built AI tools
- Pilot with a mixed team (category managers, data analysts and senior stakeholders)
- Measure, then scale
The agrifood supply chain is rewriting its playbook in real time. Either you drive that change, or you’re priced out by those who do. Schedule a 30-minute executive demo to see how Expana’s AI roadmap can supercharge your decision-making. We’ll benchmark one of your key commodities live and show the margin impact.
The time is now: turn intelligence into advantage.
Written by Vinay Kapoor
