Adapting the Latest Innovations in Artificial Intelligence During COVID-19

Companies often explore ways to find new operational efficiencies using emerging technologies, including the latest innovations in artificial intelligence, or AI. During times of economic uncertainty, this pursuit can become even more crucial. While AI and machine learning for business may still be a developing field, these technologies are already starting to generate results and drive revenue for companies.

Before COVID-19 emerged, businesses were already beginning to discover how AI and predictive analytics could drive efficiency and improve operational resilience to changing dynamics in supply chains, labor shortages and other challenges. Still, the pandemic brought massive uncertainty to every level of life, including the economy. Businesses began to grapple with the challenges across all areas of operations, including:

• Managing on-site workforces within vulnerable populations
• Managing remote employees in hot zones for infection
• Meeting volatile customer demand
• Maintaining supply chain visibility
• Navigating their dependency networks

The crisis emerged as an abrupt systemic shock that required rethinking business models and strategies within days, not weeks or months. This reality opened a window for companies to experiment with advanced AI and machine learning for business decision-making if they hadn't already adopted these technologies.

The role of AI during COVID-19

Using technology and innovation to navigate uncertainty may seem like an obvious path in the 21st century. Still, a key challenge is finding reliable solutions quickly while maximizing the technologies and business processes already in place. When the pandemic began, popular machine learning approaches relied on massive quantities of historical data for success. The last global pandemic was 100 years ago, so there was little reliable data available to drive predictive analytics. As COVID-19 surged, data often changed by the hour, rendering previous data patterns unreliable and widely popular AI implementations unhelpful.

In response, companies began pivoting to model-based AI solutions, which better leverages currently available data instead of relying on historical data. Several months into the pandemic, hybrid implementations of data-rich approaches and model-free solutions became increasingly more useful. Businesses can now use AI for more effective scenario planning during evolving situations. This is an incredibly valuable advantage in a turbulent economy experiencing major changes to finances, workforces and supply chains.

For example, manufacturers have used adapted hybrid solutions to build salient workforce models that deliver insights into employee absenteeism trends alongside infection and fatality rates in the local area. Other manufacturing uses include scaling production to meet changes in demand while minimizing risk to essential workers. Chatbots and other forms of AI-driven customer service automation can minimize the risk of workforce exposure, keeping customers and employees safer. Data analytics, robotics and other important AI-based tools can help wholesalers and retailers maintain sufficient—but not too large—inventories, minimizing risks to the customer experience and the bottom line.

Adaptability in times of crisis

Agility in the face of changing market dynamics remains a core feature of resilience and competitiveness. To gain optimal advantages from AI and acquire high-quality training data, consider:

• Refining your implementation strategies
• Working to understand your strategic objectives and potential use cases
• Harnessing resources from across the organization
• Tapping into external partner networks that will work with you and provide data

Investments in AI can provide tools for companies to stay successful during times of disruption. Talk to your banking partner about a plan to reap the rewards from the latest innovations in AI.