Scope of the study
In February and March 2024, in collaboration with EYGS LLP (EY), HFS conducted research to better understand how organizations are utilizing GenAI throughout their supply chains. We surveyed 460 senior supply chain leaders with a significant role in their organizations’ AI initiatives in the supply chain. Responses were collected across 19 countries covering the Americas, Asia-Pacific (APAC), and Europe, the Middle East, India and Africa (EMEIA) in the consumer, health sciences and wellness, energy and resources, technology, telecommunications, and manufacturing industries. Respondents represented organizations with over US$1 billion in annual revenue that were at least in the planning stages of deploying GenAI in their supply chain. In addition, in-depth qualitative interviews were conducted with supply chain executives to better understand organizations’ approaches to adopting GenAI in the supply chain.
When conducting the research, the following definitions were provided:
- Artificial Intelligence: a broad term for a set of technologies that develop or simulate intelligence in machines, including by performing tasks that traditionally required human intelligence. AI can be broadly segmented into two categories:
- Traditional artificial intelligence: AI, that is rule-based and requires prepared data sets and predefined logic to solve business problems.
- Generative AI (GenAI): A type of AI that can create new content such as images, text, audio or video based on the data it has been trained on, using techniques such as large language models, transformer neural networks and generative adversarial networks.
Key findings
While GenAI’s promise to revolutionize supply chain management is widely recognized, significant challenges and risks impede its growth. The report aims to equip enterprise leaders with the necessary insights to navigate the complex landscape of GenAI adoption. It offers both strategic recommendations for implementation and critical evaluations of its operational implications.
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GenAI can be a game-changer in building the autonomous supply chains of the future
- Nearly 85% of enterprises believe GenAI will play a crucial role in their supply chain strategies by 2030. Moreover, 80% of respondents recognize GenAI as a transformative force capable of reinventing their supply chains, indicating a significant shift toward low-human-touch, autonomous supply networks.
- 73%* of supply chain executives are actively piloting or implementing GenAI projects, allocating substantial portions of their AI budgets toward these technologies.
- In the next 24 months, GenAI adoption in supply chains is expected to surpass the current adoption level of traditional AI.
Despite the high potential, most enterprises are plagued by challenges and risks
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- Develop a phased adoption roadmap with current and future use cases
Start by implementing GenAI in selective areas that promise a quick return on investment (ROI), such as leveraging GenAI in demand forecasting. Then, incorporate more diverse and long-term use cases, such as supplier management.
- Leverage cloud technologies for faster deployments and scalability
Being part of a commercial cloud platform will ensure that an enterprise can quickly begin its GenAI journey and scale it once it sees results. 84% of leading enterprises anticipate relying much more on cloud while planning their GenAI programs. Enterprises with strict data policies and cybersecurity concerns should consider beginning their cloud journey with a hybrid cloud setup. This will enable them to leverage the latest technology advancements in GenAI while addressing their data privacy concerns.
- Empower the workforce with the best GenAI platforms, tools, and cross-functional collaboration
Leading firms stress the development of in-house GenAI capabilities and equipping their workforce with the best-of-breed GenAI tooling. This is the best way to manage employee insecurity, maintain morale, and ensure productivity.
- Begin with cross-functional collaboration and move towards a collaborative ecosystem
78% say cross-functional collaboration is required to unlock the full value of GenAI. This needs to be followed by initiatives that go beyond the four walls of the organization, focusing on alignment with n-tier suppliers, distributors, and customers. Interestingly, enterprises are placing their bets on GenAI to achieve different goals, including improved innovation, enhanced agility, better product quality, superior services, and increased revenue.
- Customize KPIs for measuring success
Tailoring success metrics to specific supply chain functions can enable companies to assess the impact of GenAI technologies more effectively. While assessing GenAI’s impact in the warehouse, improvement in throughput is a key indicator of success. However, its effect must also be evaluated in relation to the long-term business goal of achieving supply chain agility.
- Develop a complementary tech ecosystem for success
In conjunction with GenAI, leading firms are leveraging traditional AI, 5G networks, speech recognition, and edge computing to achieve more pronounced results and higher success.
- Enforce a comprehensive governance and compliance action plan
Develop a comprehensive GenAI framework, conduct a risk assessment, formulate policies around GenAI use case selection and deployment practices, perform continuous training and education, and maintain stakeholder transparency.
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The bottom line: Through strategic use-case selection, targeted technology investments, tailored KPIs, and rigorous governance, enterprises can harness GenAI’s potential to progress toward autonomous supply chains.
Many enterprises’ long-term vision is to build an autonomous and networked supply chain driven by advanced GenAI applications capable of predictive and adaptive operations. While the path to integrating GenAI within supply chains is fraught with challenges, the potential benefits make it an indispensable strategic endeavor for future-ready enterprises.
* Please note: The remaining 27% of enterprises ‘Not making or planning any investments in GenAI’ were eliminated during the screening process and did not participate in the study.
To read the complete report, click the download button below.
