Wine growers everywhere fear spring frosts. New vine buds emerge in the spring and are highly susceptible to freezing temperatures which can kill them and result in significant crop loss for the year. If the primary buds are destroyed by frost, secondary buds may grow, but they typically produce lower yields and lesser-quality grapes. 

Severe frosts can lead to substantial economic losses for vineyards due to reduced grape production and potential long-term damage to the vines. To mitigate this risk, wine growers employ various strategies, such as deploying heaters or frost pots throughout the vineyard, using wind machines to mix warmer air from above with the colder air at ground level, applying water via sprinklers to the vines, and covering vines with special materials. Others plan proactively and plant vineyards on slopes or in locations less prone to frost accumulation, or they delay pruning to postpone bud break until after the risk of frost has decreased. 

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At the Kit’s Coty vineyard in Kent, England, owned by wine producer Chapel Down, the winemakers are less concerned than most in the industry about the frost — for a surprising reason. And that is the passing by, every hour or two, of the Eurostar train on its journey between London and Paris. 

The effect of the train, moving at high speed and whooshing in and out of the North Downs Tunnel just the other side of the A229 road from the vineyard, is to mix up the air in the local environment just as wind machines do, creating a movement of warmer air that acts against the settling and accumulation of frost. This effect has a direct and clear benefit for the winemakers who have a safeguard against the risk of frost on their vines and the financial viability of their entire enterprise. 

This unexpected benefit is a prime example of what economists call an externality; a byproduct of a company’s operations that has an indirect cost or benefit to an entirely separate entity. Many externalities are negative, the most common being the costs to communities and ecosystems of industrial pollution, costs not borne by the polluting entities themselves. But this particular case is a happy example of a positive externality. Chapel Down and the Eurostar are entirely separate entities, but the winemaker benefits indirectly from the activities of the train operator, rather than incurring costs from them. 

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Of course, this externality is unplanned. This interaction is not an example of industrial or commercial symbiosis. And yet it can inspire company leaders, strategists, and designers as we think about the impact of our products, services, and operations. This relationship should remind us our organizations are never really separate entities. We are all connected in one way or another and impact each other in one way or another. So how can we ensure we design for the greatest good and least possible harm while designing for our financial success? 

The most important thing is to develop a mindset attuned to the impact that we can have on the world, unintended as well as intended, and to become familiar with design principles that can help put that mindset into practice. Mindset, principles, and action are all as important as each other. One well-recognized model is the Circular Economy. 

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Another model that my colleague Vala Afshar and I have developed is the Boundless model, a mindset and set of principles for having the greatest possible awareness, both situational and horizontal, of one’s impact and designing that impact to be overwhelmingly positive. We can design for synergy and symbiosis and do our best to ensure our externalities are mutually successful. 

Once you have chosen your model and have deeply assimilated it into your daily decisions and actions, some tools can help you minimize the risk of negative externalities and increase the possibility of positive ones. As seen below, artificial intelligence (AI) can be a useful tool for both.

Identifying and mitigating negative externalities

• Predictive analytics for environmental impact: AI can analyze data from various sources, such as satellite imagery and weather patterns, to predict how a company’s operations might affect the environment. For example, AI models can predict the impact of emissions on local air quality and help companies take preemptive measures to reduce their carbon footprint. 
• Supply chain optimization: AI can optimize supply chains by analyzing data to find the most sustainable and efficient routes and methods for transporting goods. This effort can reduce fuel consumption and emissions, minimizing the environmental impact. 
• Social media sentiment analysis: By using AI to analyze social media and other online platforms, companies can gauge public sentiment and identify potential negative reactions to their products or services. This effort helps them address issues proactively before they escalate. 
• Risk management and compliance: AI can help companies comply with environmental and social regulations by continuously monitoring their operations and flagging potential violations. This work reduces the risk of legal penalties and reputational damage. 
• Water usage and waste management: AI can optimize water usage in manufacturing processes and manage waste more effectively by predicting waste generation patterns and suggesting more efficient waste disposal methods.

Designing for positive externalities

• Product life cycle assessment: AI can evaluate the entire life cycle of a product from raw material extraction to disposal, and suggest design changes that minimize environmental impact and maximize positive contributions to communities and ecosystems. 
• Energy management systems: AI can optimize energy usage in buildings and industrial processes, reducing costs and environmental impact. For example, smart grids and energy management systems use AI to balance energy loads and integrate renewable energy sources. 
• Community impact analysis: AI can analyze demographic and economic data to predict how a new business or product will affect local communities. This effort can help companies design initiatives that support local development, such as job creation or community services. 
• Customer behavior prediction: AI can predict customer behavior and preferences, allowing companies to design products and services that meet societal needs more effectively. This work can lead to positive social outcomes, such as improved health or education. 
• Agricultural optimization: AI can be used in precision agriculture to optimize water use, fertilizers, and pesticides, reducing environmental impact while increasing crop yields. This effort benefits both farmers and the broader ecosystem. 

Examples in practice

• Salesforce Trailhead and its AI-focused curriculum: The demand for AI-skilled employees has skyrocketed. Salesforce’s Trailhead program can supercharge your career and help you learn the latest AI skills. With over 21 million active learners on the platform, analyst IDC forecasts the Salesforce community will create 11.6 million new jobs and $2 trillion in incremental business revenues by 2028. 
• IBM’s Environmental Intelligence Suite: This suite uses AI to predict and mitigate the impact of climate events on supply chains, helping companies reduce their environmental footprint. 
• Google’s DeepMind for Energy Efficiency: Google has used its AI subsidiary, DeepMind, to reduce the energy used for cooling its data centers by 40%, demonstrating significant operational efficiency and environmental benefits. 
• Microsoft’s AI for Earth: This initiative provides AI tools to organizations working on sustainability challenges, such as biodiversity conservation and climate change, enabling them to have a greater positive impact. 
• Unilever’s Sustainable Living Plan: Unilever uses AI to analyze and improve its supply chain, ensuring sustainable sourcing of raw materials and reducing the overall environmental impact. 
• Patagonia’s Use of AI for Environmental Monitoring: Patagonia employs AI to monitor and mitigate the environmental impact of its production processes, aiming for sustainability and positive community impact.

In summary, AI has the potential to significantly enhance a company’s ability to design for positive externalities and mitigate negative ones. By leveraging AI’s predictive and analytical capabilities, companies can make more informed decisions that benefit their bottom line and the environment. 

We may not be able to replicate the happy accident of Eurostar’s impact on frost mitigation and Kit’s Coty’s efforts to make some of the best sparkling wines in the world but we can be inspired by it and set out to design intentionally for positive impact and shared success. 

This article was co-authored by Henry King, business innovation and transformation strategy leader and co-author of Boundless: A New Mindset for Unlimited Business Success.