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- Generative AI is unlike any technology that has come before. It’s swiftly disrupting business and society, forcing leaders to rethink their assumptions, plans, and strategies in real time.
- To help CEOs stay on top of the fast-shifting changes, the IBM Institute for Business Value (IBM IBV) is releasing a series of targeted, research-backed guides to generative AI, on topics from data cybersecurity to tech investment strategy to customer experience.
- This is part nine: Supply chain.
Generative AI is unlike any technology that has come before. It’s swiftly disrupting business and society, forcing leaders to rethink their assumptions, plans, and strategies in real time.
To help CEOs stay on top of the fast-shifting changes, the IBM Institute for Business Value (IBM IBV) is releasing a series of targeted, research-backed guides to generative AI, on topics from data cybersecurity to tech investment strategy to customer experience.
This is part nine: Supply chain.
Generative AI is unlike any technology that has come before. It’s swiftly disrupting business and society, forcing leaders to rethink their assumptions, plans, and strategies in real time.
To help CEOs stay on top of the fast-shifting changes, the IBM Institute for Business Value (IBM IBV) is releasing a series of targeted, research-backed guides to generative AI, on topics from data cybersecurity to tech investment strategy to customer experience.
This is part nine: Supply chain.
Supply chain automation just got an upgrade
If you could see the future, would you run your business differently? This is the question CEOs face in the era of generative AI—and supply chain automation has taken it out of the abstract. As real-time data fuels faster simulation and more accurate predictive analysis, it’s become easier for businesses to plan for tomorrow.
That’s why CEOs are rapidly investing in generative AI to automate and streamline their supply chains. In fact, 89% of executives report that key investments in automation will include generative AI capabilities—and 19% say generative AI will be critically important to their supply chain automation futures.
For six out of 10 executives, the business case for investing in automation centers around boosting workforce productivity and agility—and generative AI amplifies these effects for both human employees and AI assistants. Clean and trusted data will be central to getting the intended value from these investments.
Organizations are seizing the generative AI moment to capture opportunities to increase responsiveness, build deeper human-tech partnerships, and innovate at clock speed. Those that don’t will be stuck in the control tower wondering why they’ve fallen behind.
The IBM Institute for Business Value has identified three things every leader needs to know:
1. Real-time data is finally for real.
2. Seamless collaboration sparks productivity gains.
3. Generative AI is a mirror that lets you see around corners.
And three things every leader needs to do right now:
1. Stop fighting fires and start rethinking your supply chain.
2. Feed generative AI data that supports supply chain productivity.
3. Supercharge supply chain operating models with generative AI platforms.
An updated version of this chapter with 2024 data is now available in the latest edition of the IBM Institute for Business Value's book, The CEO's Guide to Generative AI.
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Originally published 07 November 2023
1. Data
+ Generative AI
What you need to know
Real-time data is finally for real
As disruption continues to rock the global supply chain, executives are hungry for a single source of truth. In fact, being able to respond to real-time demand volatility is a top operational priority (51%) over the next three years.
With generative AI, they’ll finally be able to feast. It can help leaders collect data from across the supply chain in real time and avoid the confusion that comes from competing views. Rather than debating whose numbers are right, teams can look through the same pane of glass to make faster decisions—and elevate their ability to innovate.
Nearly two-thirds (62%) of executives expect generative AI to accelerate the pace of discovery, leading to new sources of product and service innovation. And companies that get it right can gain a crucial advantage: Generative AI leaders outperform in innovation 53% more frequently than their peers.
Of course, real-time data won’t just appear on the dashboard overnight. To tap into this invaluable asset, CEOs need to address a host of practical and pragmatic data issues, from segmenting and cleaning data to determining how structured and unstructured data should be used across the organization.
What you need to do
Stop fighting fires and start rethinking your supply chain
Enable innovation with real-time, data-driven insights. Pair these findings with business know-how to deliver differentiated outcomes. Determine which data should be centralized and what should be left at the edge or with third parties to add the most value.
- Modernize your supply chain with advanced modeling. Take advantage of generative AI’s uniqueness to modernize your supply chain applications and architecture. Engage with quantum computing tools and methods to capitalize on expanded modeling and optimization capabilities.
- Identify hidden pain points that are candidates for targeted innovation. Encourage end-to-end experimentation in demand volatility, sourcing, production, and distribution. Sponsor the integration of supply chain communities that rely on predictive and prospective analysis fueled by generative AI and huge amounts of data.
- Deploy your AI assistants into your supply chain ecosystem. Insert your digital technology capabilities into your massive ecosystem of supply chain partners. Bring a new level of synergy and efficiency by exchanging those capabilities with your ecosystem partners. This enables quicker access to data that complies with your standards and accelerators.
2. Productivity
+ Generative AI
What you need to know
Seamless collaboration sparks productivity gains
Identifying issues that foreshadow future disruption is essential to keep supply chains up and running. But that’s only the first step. Acting on that information fast enough to fill the gaps takes coordinated effort on a global scale.
That’s where generative AI comes in. It enables faster, more effective collaboration between people, AI assistants, and partners that can proactively identify supply chain anomalies and correct them in real time.
Executives report that generative AI will increase the volume of decision-making by digital assistants by 21% in the next two years. While this does introduce new opportunities for error, 82% of executives agree that the benefits they expect from generative AI exceed the potential risks.
Of course, human workers still have a critical role to play. The creativity, empathy, and critical thinking skills they bring to the table are needed to rethink operations and solve complex problems. How they apply those skills is evolving rapidly, however, with 71% of supply chain executives saying generative AI completely changes how their people do their jobs.
Nine in 10 executives now say their organization’s workflows will be digitized with intelligent automation and AI assistants by 2026. This expansive digitization promises to deliver benefits across the supply chain, with 80% of executives expecting generative AI to enable better management by analyzing all relevant supplier performance metrics.
Increased visibility and transparency help leaders respond to risks immediately, rather than waiting for partners to report problems at their own pace. Integrating clean and trusted data from across the supply chain also makes it possible to power an LLM that people across the industry can tap for accurate, real-time information.
What you need to do
Feed generative AI data that supports supply chain productivity
Map the full range of preemptive data initiatives needed to connect people and technology across the supply chain ecosystem. Upskill employees and train tools to speed decisions and actions. Progress an LLM specific to supply chain for your industry.
- Cultivate human-tech chemistry to uncover real-time insights. Make this chemistry a commodity that touches every point of the supply chain: planning, sourcing, manufacturing, and distribution and transportation. Increase productivity of both humans and AI assistants with generative AI.
- Crank up the dial on process improvement. Look for leaders in each key supply chain function to suggest and execute supply chain process improvements. Augment technology with people and people with technology to deliver superior process outcomes and transform the employee experience. Find ways to free supply chain professionals from transactional work so they can focus on solving real business problems.
- Replace traditional dashboards with real-time supply chain large language model (LLM) queries. Feed comprehensive supply chain metrics and transactional data into generative AI models. Take the latency out of decision-making with LLMs that enable immediate insights. Conceptualize new practices based on gap analysis and points of interrelation. Use the recommendations for predictive and preemptive decisions and actions.
3. Prediction
+ Generative AI
What you need to know
Generative AI is a mirror that lets you see around corners
Predicting the future isn’t just for fortune tellers. Generative AI serves as a counterweight to global complexity, letting leaders detect approaching threats and suggest evasive maneuvers based on more than premonition.
More than four in five (81%) executives agree predictive capabilities with generative AI detect problems earlier, and 77% say generative AI models successfully identify geopolitical and climate risks, enabling proactive mitigation. More tactically, 79% of executives say generative AI will optimize inventory management by predicting future demand patterns.
In response, 80% of executives say generative AI models with visualization and simulation, such as digital twins, will uncover supply chain bottlenecks in real time. But applications will be limited. By 2025, they say only 19% of supply chain use cases will incorporate generative AI, including simulation and modeling of complex systems, transportation optimization, product lifecycle management, and customer service and real-time response.
What you need to do
Supercharge supply chain operating models with generative AI platforms
Create self-learning simulations that let you identify, visualize, and proactively correct critical operating exceptions. Hyper-automate transactional work to create next-level operational efficiencies.
- Preempt the next shock. Predict and embrace disruptions. Deploy analytics, data visualization, and simulation models, along with generative AI capabilities for pattern recognition. Act calmly and resolutely to keep your supply chain afloat while the competition takes on water.
- Put mission-critical touchpoints front and center. Align the most crucial and differentiating supply chain workflows with your early predictive generative AI use cases. Involve key partners for improved collaborative foresight. Ensure generative AI-driven artifacts are clearly identifiable and auditable.
- Measure the positive impact of premodeling. Regularly assess the performance and ROI of generative AI-driven predictive analysis. Set clear goals to ensure these efforts are delivering the desired results and adjust as needed for continuous improvement.
The statistics informing the insights on this page are sourced from two proprietary surveys conducted by the IBM Institute for Business Value in collaboration with Oxford Economics. The first survey was asked to 200 US-based executives in September 2023 regarding generative AI and supply chain. The second was asked to 2,000 executives across 21 countries in April–July 2023 regarding automation and AI.
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An updated version of this chapter with 2024 data is now available in the latest edition of the IBM Institute for Business Value's book, The CEO's Guide to Generative AI.
Additional content
Download report translations
Originally published 07 November 2023
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