Generative artificial intelligence has struck like a bolt of lightning, rapidly moving from an industry buzzword to a robust business opportunity.

A report by Gartner indicates that chief supply chain officers are investing in growth through new technology investments, with many anticipating allocating an average of 73% of their supply chain information technology budgets to areas such as actionable AI, smart operations and digital twins, among others. Now, every business and technology leader are searching for ways to integrate AI-powered solutions into their business plans.

Within procurement and supply chain management, generative AI can be a difference-maker — analyzing large amounts of data to provide insights that can help optimize supply chain planning, forecasting and decision-making. By embracing AI and leveraging its ability to predict and plan for disruption, organizations can improve operations and create new business opportunities.

Moving forward, generative AI will deliver trillions of dollars in economic benefits and help companies realize greater top-line growth, be more productive and safeguard supply chains.

Predictive, preventive resilience

Supply chain disruptions are here to stay. Whether they’re the result of geopolitical conflicts, effects of inflation, products of climate change or other issues yet to emerge, investing in the right technology will be critical to predict, prevent and pivot in the face of disruption.

The biggest obstacle in achieving this mission: the reliance on legacy systems that are not equipped to handle the speed of today’s digital economy. In a survey from Tata, two-thirds of respondents are still using mainframe or legacy applications for core business operations.

By prioritizing technologies such as generative AI and cloud-based platforms, companies can identify looming supply chain issues and stop them before they happen. Generative and predictive AI will not only help forecast disruptions, but also recommend alternate sources of raw materials, detect errors in invoices and predict shipment and delivery times.

When trained properly on a company’s procurement process, these AI tools can also spot opportunities for efficiency that a human might miss or not see — or even identify clunky processes and suggest how to improve them. A KPMG Global report highlights that in the event of a disruption or a surge in demand, the nimblest companies will have a significant competitive advantage, responding proactively to market changes and sourcing new suppliers quickly. Generative AI can assist in evaluating and selecting suppliers based on various parameters, including reliability, performance history and financial stability — potentially minimizing disruptions.

All these capabilities come together to create a stronger, more resilient supply chain operation. And in 2024, you can almost guarantee that AI will be at the center of most companies’ processes.

Data-driven decision-making

Today’s companies need end-to-end visibility and collaboration throughout their supply chain. However, this level of transparency cannot happen without data and technology to drive it.

This is not just a matter of business success, it’s a matter of business survival. The pandemic made companies painfully aware of the lack of visibility they had into their supply chain. Despite decades of globalization, companies around the world were thrown into chaos, and many of them were not able to adapt fast enough to keep up with consumer demands.

Companies that modernize their supply chain through data lakes and control tower layer technology, as well as digital twins will be a step ahead when it comes to supply chain resilience and flexibility. By centralizing data in a data lake, AI and machine learning algorithms can go to work extracting and analyzing any data type that could pave the way for new business opportunities.

Data lakes pair well with the use of digital twins, which are virtual models of real-world objects, systems and processes, that can apply current operational data to run digital simulations that help mitigate real-world volatility. By fueling digital twins with real-time data, supply chain managers can gain insight into the current state of their operations, while forecasting various short- and long-term scenarios that will help inform better decision-making.

There is a clear trend toward increased utilization of data-driven technologies, greater flexibility and adaptability in supply chain management practices. Businesses that haven’t embraced these tools are falling behind the competition — and missing out on ways they can become more flexible, proactive and sustainable that they may not be able to identify on their own.

How other industries are leveraging AI

It’s easy to recount all the potential benefits and applications of AI on paper. But applying these solutions in the real world is another story. In any industry, the first step is recognizing AI technology as an enabler rather than a threat, or even a complicated new tool.

Within a business network made up of suppliers, distributors, third-party developers and others, AI can be especially helpful — helping businesses anticipate the need to replenish inventory based inferring information drawn from activities elsewhere in the value chain, without manual intervention. A recent IDC study, sponsored by SAP shows that companies that use business networks have higher levels of digital maturity, supplier collaboration and supply chain performance.

These applications could start small, such as embedding AI to automate repetitive tasks like spend applications or invoice tracking to build more efficient processes. In the world of operations and recruitment, generative AI can help draft more effective job descriptions, create more detailed statements of work, or translate postings into multiple languages.

As an industry, retail has established a formidable e-commerce presence and has been a champion of using data to better understand their customer preferences. Now, retail companies are using AI to inform their production runs and inventory management to ensure items are delivered on schedule.

Finance companies are incorporating AI in ways that help reduce costs and improve efficiency as well. With AI tools visually verifying information for mobile check deposits, and robo-advisers or chatbots answering questions that spare time spent on hold with customer service, the banking experience is now more convenient and personalized.

In manufacturing, the AI revolution is powered by the internet of things and robotic automation to optimize supply chain operations.

As we look at the current state of digital transformation in trade and supply chains, it’s clear that there is still significant room for growth. 2024 and beyond will be about seizing these opportunities to build a foundation for long-term success.

Muhammad Alam is president and chief product officer for SAP Intelligent Spend and Business Network, and general manager for SAP Business Network. He wrote this article for SiliconANGLE.

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