Thank you so much for joining us in this interview series. Before we dive into our discussion our readers would love to “get to know you” a bit better. Can you explain how AI is disrupting your industry? Is this disruption hurting or helping your bottom line?
In today’s turbulent supply chain landscape, leaders are facing unparalleled levels of pressure to deliver results in the midst of many external challenges outside their control. Ongoing geopolitical conflicts, sustainability concerns, labor shortages, and shipping lane challenges constitute an array of threats to supply chain continuity. AI-powered technology is supporting leaders by enabling faster, smarter, and more efficient decision-making in time-critical situations. According to Jabil’s 2024 Supply Chain Resilience Survey of nearly 200 supply chain and procurement decision-makers worldwide, 66% of companies are using predictive analytics and AI/machine learning models in their supply chain activities.
Transformational AI technology is actually creating major change in how organizations handle disruptions within the logistics domain. With AI tools, organizations can gain end-to-end visibility into supply chain operations, including the ability to see where and when disruptions occur or forecast where they are likely to occur. Using this intelligence, supply chains can optimize routes for cost and time savings to reduce the ripple effect of external global events that pose a risk to delivery (such as a natural disaster or port closure).
By harnessing the power of AI, organizations can improve demand forecasts, enabling them to adjust their inventory levels, lower costs, and improve customer satisfaction. Across the industry, AI also has huge potential in the sourcing arena. AI can complement and augment human expertise in supplier selection by providing data-driven insights, recommendations, and actions that can help organizations to identify, evaluate, select, and source from the best suppliers.
Generative AI is changing the way supply chains anticipate using and analyzing the huge amounts of data collected by their organizations. Users are seeking a more personalized experience, akin to the outputs they’ve come to know from tools like ChatGPT. Supply chain professionals will soon expect that they can view a report and generate actionable insights through conversation with an AI model leveraging natural language processing.
The disruptions caused by AI can both benefit and threaten the supply chain industry’s bottom line. On one hand, AI can help create competitive advantages and improve operational efficiency to generate greater revenue opportunities. However, AI can also pose data privacy and security concerns, create regulatory and legal uncertainties, and expose talent gaps that could potentially threaten growth opportunities if they are not carefully managed.
Which specific AI technology has had the most significant impact on your industry?
To this point, AI-powered advance planning technologies have had, and continue to have, a significant impact on supply chain operations. These tools help organizations more accurately forecast demand, which enables tighter inventory management and helps us keep inventory at optimal levels — positively improving free cash flow. At Jabil, we’ve implemented AI/ML algorithms into our advance planning toolsets as well as our safety stock and reorder point (ROP) recommendations. More accurate forecasts allow us to get ahead of potential swings in demand, technologies reaching the end of their lifecycle, and other disruptions.
Looking ahead, I anticipate that AI will have a significant impact on logistics processes, particularly around route optimization for sustainability. Does route A or route B have a larger carbon footprint? Is it more efficient to manufacture in a factory that is powered by 100% renewable energy but involves transporting components five hours by truck than it is to manufacture nearby using traditional fuel? These are the questions AI could help us answer in the years ahead as companies work to comply with increasing sustainability regulations.
When you look at supply chain industry sentiment around this issue, there’s certainly interest but not necessarily action yet; for example, 54% of respondents in Jabil’s supply chain resilience survey said they anticipate AI will offer greater insights into how sustainability efforts can be executed more responsibly and efficiently. However, only 23% said that contributing to the company’s sustainability goals is a main goal of their supply chain organization over the next two years.
Can you share a pivotal moment when you recognized the profound impact AI would have on your sector?
The near-constant pace of disruptions we’ve seen since the pandemic has helped me realize that supply chain organizations must be able to consume, analyze, and understand data much faster than we’re used to. Most recently, the disruptions in the Middle East made it clear that the complexity of what supply chain organizations handle daily has become tremendous; expecting individuals to understand all the data points we have coming at us and make decisions fast enough to keep up, all on their own, is unrealistic.
AI will have a massive impact on the ability of supply chain professionals to parse which data is relevant and then make agile, effective decisions. After all, data is the currency of AI. However, any technology implementation must start with an assessment of the data you have. Is the information you’re gathering accurate, insightful, and timely? How is it being stored? If you don’t have a uniform approach for data governance and management across your supply chain organization — or, ideally, your entire business — AI tools won’t be your saving grace.
How are you preparing your workforce for the integration of AI, and what skills do you believe will be most valuable in an AI-enhanced future?
Like in any industry, the most fundamental step of preparing the supply chain workforce for AI adoption is helping employees understand the technology’s potential and limitations — specifically that it is intended to complement human skillsets and capabilities, not replace them.
At Jabil, we have several initiatives underway to equip our team of more than 3,000 supply chain, procurement, and logistics professionals with AI fundamentals, such as hands-on experience with our supply chain AI pilot programs, webinars, and workshops with both internal and external experts. Another important step is to identify the skills gaps and needs of our current and future roles. We are conducting comprehensive skills assessments and mapping exercises to understand how AI will impact our business functions and processes and thus what competencies are required to leverage AI effectively.
As part of our culture of continuous learning, this information will also be used to build tailored learning pathways and training for current and future employees. As data is the building block of any successful AI solution, we recently established a data literacy campaign to equip all supply chain employees with a basic knowledge of data’s role in AI.
Jabil employees are empowered to embrace AI and experiment with conceptual ideas. We have established an internal data and AI council, to whom our employees can introduce AI projects and use cases to be considered for enterprise use and who is responsible for creating enterprise-wide policies and procedures. Striking this balance between encouraging employees to innovate but having internal gatekeepers who ensure AI deployments are made strategically is critical for organizations trying to get their workforce up to speed on new technologies.
What are the biggest challenges in upskilling your workforce for an AI-centric future?
A major challenge in upskilling employees for AI adoption is overcoming a fear of change. Employees might feel threatened or intimidated by AI and worry that it will “take their jobs.” While it may be true that AI can automate specific tasks, those are opportunities for people to be upskilled to more creative or thought-intensive roles. As leaders, it’s our duty to be transparent about the opportunities AI presents and clearly communicate the scope in which it will be deployed.
The “human in the loop” concept is critical for the success of AI adoption; the workforce will play a vital part in the validation of AI outputs. AI will merely augment the role of an individual, providing efficiency gains but not replacing the human skillset and expertise required for making final decisions.
AI can carry an air of mystery, so the deployment of new tools must include transparency about how they work. AI can’t be a black box where employees put something in and get something out with no understanding of what happens in the middle. Without that knowledge, employees may not trust the output of AI and thus not use it as part of their decision-making — wasting the organization’s investment.
What ethical considerations does AI introduce into your industry, and how are you tackling these concerns?
While data security has been an everlasting priority for supply chain organizations, governance of data for AI adoption remains as challenging as it is critical. It is paramount that organizations establish guardrails as part of their technology deployment to ensure they are compliant with internal data protection policies and external regulations. They must also remain transparent with employees, customers, and suppliers about which data their AI tools have access to. This is of particular concern for the protection of customer and supplier intellectual property.
Investments must be made in data protection from unauthorized access, misuse, or theft by implementing robust encryption and authentication measures. Teams using AI tools — in supply chain and beyond — need to work closely with legal and compliance teams to ensure these policies and guardrails are sufficient for every use case and region in which the tool will be deployed.
What are your “Five Things You Need To Do, If AI Is Disrupting Your Industry”?
- Leaders must take responsibility to ensure their organizations are AI-prepared by establishing a well-governed, interconnected, and scalable data platform. Data is a foundational element in the makeup of artificial intelligence. Without a solid data management framework that guarantees governance of compliant, secured, and accurate data assets, the outputs of AI models are less insightful and valuable in decision-making.
- Supply chain leaders who embrace AI, keep abreast of its innovations, and apply their AI expertise to their specific business requirements can better position their businesses to win. By staying updated on the latest AI trends, following the best practices in the industry, and establishing a clear AI strategy, leaders will have the fundamental knowledge to invest in and adopt AI technologies.
- It is imperative that outputs driven from AI applications are trusted by employees across the organization. Ensuring that subject matter experts are involved from the outset and partaking in AI model training and human in the loop decision-making gives you a fighting chance at building that trust. Once your organization is at a high level of AI maturity and widescale adoption, it is pivotal to deliver explainability to garner trust in AI-driven insights.
- Investing in AI infrastructure and talent, developing the understanding of AI building blocks, and optimally leveraging data are essential steps for leaders who want to succeed in the AI domain. Leaders must empower employees to conceptualize practical AI use cases that add value, deliver efficiencies, and create potential cost savings in supply chain processes. AI implementation must be meticulously thought out and aligned with strategic needs of the business.
- Foster a learning culture across your organization by offering a variety of training opportunities on AI technologies. Moreover, it is important for leaders to broadcast the AI strategy and roadmap across the organization, promote AI success stories, and report AI solution adoption rates to gather interest and sustain momentum.
What are the most common misconceptions about AI within your industry, and how do you address them?
Thanks to the accessibility and user-friendliness of tools like ChatGPT, there is a misconception that all AI solutions for any industry are fast and easy to implement. Within supply chain, there’s a misbelief that AI can overcome all the challenges organizations face with gaining visibility and creating predictability. While it can certainly offer new efficiencies, I believe we’re still in the early hype cycle. We all have some learning to do to fully embrace the reality of AI. We are seeing more use cases every day that demonstrate the potential for AI to help organizations create new efficiencies and navigate the near-daily disruptions in the global supply chain.
Still, organizations need to be thoughtful on where we invest in AI to deliver the most value for their business and their customers. It doesn’t make sense and it is not cost-effective to try and solve everything with AI. Companies need to choose the right use cases based on their particular needs and challenges.
Thank you for the time you spent sharing these fantastic insights. We wish you only continued success in your great work!