The Slow Progress of Artificial Intelligence Adoption in Supply Chain Management

Introduction

While businesses are increasingly interested in incorporating artificial intelligence (AI) into their supply chain management, the majority are stuck in the pilot stage, according to research firm Zero100. This article delves into the transformative potential of AI in supply chain management, the slow progress companies have made in implementing AI beyond pilots, and the need for a clear path forward to capitalize on this technology.

The Impact of AI on Supply Chain Management

AI is revolutionizing supply chain management at a faster rate than any technology since the internet, emphasizes Kevin O’Marah, Chief Research Officer and Co-founder of Zero100. The rise of generative AI is pushing digitization to the forefront, and boards are beginning to recognize that embracing AI will be crucial for long-term prosperity. However, Zero100’s analysis of public earnings calls reveals that only 11% of companies have successfully deployed AI beyond the pilot stage.

The Payback of Technology Investments

Investments in supply chain technology, in general, have had a significant payback in a relatively short time frame. Cleo’s 2024 Ecosystem Integration Global Market Report found that within 24 months of implementing supply chain technologies, 97% of surveyed companies experienced benefits, with 81% witnessing business improvements. However, investment in AI has been comparatively slower.

Zero100’s Recommended AI Fast Track Plan

To accelerate the adoption of AI, Zero100 advises companies to follow a “90-day AI fast track” plan consisting of three separate 90-day attack plans:

1. Define & challenge goals (PRFAQ approach):
• Craft a press release outlining the ideal future state and work backward to develop a focused, customer-centric strategy.
• Create frequently asked questions (FAQs) to challenge goals, considering external factors and how AI can help achieve them.
2. Balance & speed (Star Model):
• Foster collaboration and rapid experimentation through the Star model while maintaining core processes.
• Implement lean workflows that integrate business and technical teams for AI, data, and process reinvention to break silos and increase speed.
3. Close collaboration & shared innovation (MLOps):
• Establish tight integration between supply chain, technology, and data science teams to break down silos.
• Promote seamless collaboration and information sharing across departments for continuous improvement.

Leading the Market with AI

Research from Gartner shows that top-performing supply chains invest in AI and machine learning at twice the rate of their lower-performing counterparts. These companies leverage their size to focus on enhancing productivity and optimizing supply chain data with AI/ML applications to unlock value and drive future success. On the other hand, lower-performing companies tend to prioritize efficiency or cost savings.

Conclusion

While AI has the potential to transform supply chain management, the majority of companies are still in the early stages of adoption. To maximize the benefits of AI, companies need to embrace a clear roadmap and follow a systematic approach tailored to their specific goals. By doing so, businesses can position themselves for success in the rapidly evolving digital landscape of supply chain management.

Questions and Answers

1. What percentage of companies have moved beyond the pilot stage in implementing AI in supply chain management according to Zero100’s research?

   Only 11% of companies have deployed AI beyond the pilot stage.

2. What benefits have companies seen within 24 months of implementing supply chain technologies, as found by Cleo’s report?

   Within 24 months, 97% of companies experienced benefits, with 81% witnessing business improvements.

3. What is Zero100’s recommended approach to accelerate AI adoption?

   Zero100 advises companies to follow a “90-day AI fast track” plan, which includes three separate 90-day attack plans: Define & challenge goals (PRFAQ approach), Balance & speed (Star Model), and Close collaboration & shared innovation (MLOps).

4. According to Gartner’s research, how are top-performing supply chains investing in AI compared to lower-performing ones?

   Top-performing supply chains invest in AI and machine learning at twice the rate of lower-performing supply chains.

5. What is the key factor that will drive future success in supply chain management, according to Ken Chadwick from Gartner?

   Enhancing productivity is the key factor that will drive future success in supply chain management.