Unleashing the Power of AI in Supply Chains: Identifying and Developing Leaders for Success

Artificial intelligence (AI) has the potential to fundamentally transform supply chain management, from demand forecasting to inventory management, logistics optimization, and customer engagement.

While some organizations have been making investments for years, others are just starting their AI journey. The introduction of ChatGPT and subsequent surge in interest around large language models (LLMs) and generative AI has thrust this technology conversation into the spotlight.

From a leadership perspective, embracing AI-driven solutions can bring efficiency, agility, and strategic advantage. However, given the technology’s newness and rapid advancement, many leaders are wondering where to begin. To help leaders better understand how AI can transform supply chain management, Russell Reynolds Associates examined the technology, emphasizing the strategic considerations and leadership approaches necessary to harness its full potential.

AI in action: how three companies are leveraging it in supply chain management

According to 2023 Boston Consulting Group research, early adopters are rapidly adopting generative AI throughout the supply chain.¹ While AI isn't new to the supply chain management--a 2021 McKinsey study indicated that one-fifth of executives had implemented AI and machine learning for some type of supply chain activity--organizations are moving even faster to embrace generative AI (Figure 1).²

Figure 1: Supply chain adoption of AI

Leadership considerations when embedding AI into supply chain management

Integrating AI into supply chain management presents both opportunities and complex challenges for leaders. To successfully harness the power of AI in optimizing supply chain operations, leaders must consider a range of strategic, organizational, regulatory, and ethical factors. Here's an exploration of some of the leadership considerations involved when it comes to leadership, culture, organizational structure, and risk management:

1. Strategic alignment

This is crucial for the successful adoption of AI in supply chain management. When implementing AI technologies, organizations need to ensure that their AI initiatives are closely aligned with their broader business strategy. By doing this, they can maximize AI’s benefits and achieve their desired outcomes more effectively. AI has great value creation potential:

• A 2023 McKinsey survey found that 33% of respondents in supply chain management witnessed cost reductions as a result of adopting AI, while 56% reported an increase in revenue.⁸
• In a recent Gantner survey, 61% of respondents considered supply chain technologies, such as AI, a source of competitive advantage.⁹
  
  

2. Change management and cultural shifts

AI might supply a new framework, but human judgment, creativity, and strategic thinking are still necessary to lead and develop effectively. Leaders should aim to meet their people with passion, authenticity, rigor, and humility. That’s something they’ll never get from a bot.

Leaders should communicate the benefits of AI, foster a learning mindset, and lead by example. Additionally, predictions on AI’s potential impact on workforce size in supply chain management (Figure 2) may reinforce resistance to change. When addressing these concerns, leaders must communicate transparently, educate employees on the tool’s additive benefits, and address employee concerns in an open and supportive environment.

Figure 2: Effect of generative AI adoption on number of employees by function over the next 3 years

% of respondents

^{Source: McKinsey, The state of AI in 2023: Generative AI’s breakout year, August 1, 2023. N = 1,684. Data collected between April 11-21, 2023. | Note: McKinsey Global Survey to 1,684 participants at all levels of the organization. Respondents were asked about only the business functions in which they said their organizations have adopted AI.}

3. Continuous learning and adaptation

AI technologies evolve rapidly, so leaders need to stay updated on AI trends, encourage innovation, and embrace agility.

The new nature of competition is really not about technology; AI technology moves too fast for that. It’s about the value you deliver to customers. And whatever value you deliver, it can be augmented through partnerships.”

- Philippe Rambach, Chief AI Officer at Schneider Electric¹¹

4. Cross-functional collaboration and organizational structure decisions

Effective AI implementation requires collaboration across different departments. This effectiveness is highly influenced by the organization’s structure.

While dedicated R&D teams will continue to create new products, every function within the company can have its own R&D capability, leveraging AI tools to improve their respective workflows and processes. The best structures will facilitate collaboration between business and technology, breaking down organizational silos.

5. AI governance and data privacy

The success of AI-driven supply chain initiatives heavily relies on accurate and high-quality data. Leaders should establish data governance policies, ensure data security, and address ethical concerns alongside existing and emerging regulations.

Government regulations, such as the EU AI Act, will increasingly impact the deployment of AI, extending beyond ethical considerations.¹²

Embracing the AI revolution: Identifying and developing leaders for a future-ready supply chain

Supply chains have become a strategic priority for many organizations, shifting them from out of sight to front and center on C-suite and, increasingly, board agendas. With organizations racing to capture AI’s value, the significance of supply chains as a strategic issue at the board level is likely to be amplified.

To gain an AI advantage, organizations need to embed it throughout their supply chains. While companies will continue to have dedicated central teams, embedding data science teams within functional departments—such as supply chain—promise more success by connecting analytics projects closely with specific needs, providing dedicated resources, and focusing expertise.¹³ These efforts and teams require supply chain leaders with technology acumen who are forward thinking and create a culture of continuous innovation. The best ones understand that technology is an enterprise-wide responsibility, and know how to harness technology for strategic advantage.

At Russell Reynolds, our teams of industry experts and industrial organizational psychologists help find and develop those leaders. We assess candidates across three horizons, evaluating their experience, skills, competencies, and versatility. The goal is to identify individuals who have the capabilities needed to address both current and future technology change needs (Figure 3).

Figure 3: RRA process for finding tech-first leaders

Determining who will lead AI transformation is crucial to success. External advisors can offer valuable perspectives when it comes to finding and developing those individuals.

Authors

• Ben Shrewsbury leads Russell Reynolds Associates’ Operations & Supply Chain Officers capability globally. He is based in Dallas.
• Fawad Bajwa leads Russell Reynolds Associates’ Operations & Supply Chain Officers capability in the Americas. He is based in Toronto.
• Gregory Gerin leads Russell Reynolds Associates’ Operations & Supply Chain Officers capability in EMEA. He is based in Brussels.
• Vijuraj Eranazhath leads Russell Reynolds Associates’ Operations & Supply Chain Officers capability in Asia Pacific. He is based in Mumbai.
• Mika Nurminen leads Knowledge for Russell Reynolds Associates’ Operations & Supply Chain Officers capability. He is based in Toronto.

Footnotes

^{1. Boston Consulting Group. July 10, 2023. Building the Supply Chain of the Future. https://www.bcg.com/en-ca/publications/2023/building-the-supply-chain-of-the-future}

^{2. Marilú Destino, Julian Fischer, Daniel Müllerklein, & Vera Trautwein. February 9, 2022. To improve your supply chain, modernize your supply-chain IT. McKinsey. https://www.mckinsey.com/capabilities/operations/our-insights/to-improve-your-supply-chain-modernize-your-supply-chain-it}

^{3. Boston Consulting Group. July 10, 2023. Building the Supply Chain of the Future. https://www.bcg.com/en-ca/publications/2023/building-the-supply-chain-of-the-future}

^{4. Sharon Goldman. June 9, 2022. AI is embedded everywhere at Walmart. VentureBeat. https://venturebeat.com/ai/ai-is-embedded-everywhere-at-walmart/}

^{5. Timothy Inklebarger. August 17, 2023. Walmart CEO 'excited about what’s possible' with AI. Winsight. https://www.winsightgrocerybusiness.com/technology/walmart-ceo-excited-about-whats-possible-ai}

^{6. Brendan O'Callaghan. June 18, 2023. AI Goes Industrial. https://www.sanofi.com/en/magazine/our-science/ai-goes-industrial}

^{7. Lisa Lee. March 28, 2023. This Company Saved Millions with AI – Here’s How. Salesforce. https://www.salesforce.com/blog/ai-at-scale/}

^{8. McKinsey. August 1, 2023. The state of AI in 2023: Generative AI’s breakout year. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year}

^{9. Sarah Hippold. April 20, 2022. Emerging and maturing supply chain technology is a major source of competitive advantage. Gartner. https://www.gartner.com/smarterwithgartner/gartner-predicts-the-future-of-supply-chain-technology}

^{10. Neil Perry. August 25, 2023. Ivalua survey: Gen AI adoption gathers pace in procurement. Procurement Magazine. https://procurementmag.com/articles/ivalua-survey-gen-ai-adoption-gathers-pace-in-procurement}

^{11. Randy Bean & Allison Sagraves. June 20, 2023. Why Chief Data and AI Officers Are Set Up to Fail. Harvard Business Review. https://hbr.org/2023/06/why-chief-data-and-ai-officers-are-set-up-to-fail}

^{12. Saurine Doshi, Aman Sethi, Jay Motani, & Eric Rivera. August 23, 2023. What are the opportunities, realities, and obstacles for generative AI in supply chains? Kearney. https://www.kearney.com/service/analytics/article/what-are-the-opportunities-realities-and-obstacles-for-generative-ai-in-supply-chains}

^{13. Marta Stelmaszak & Kelsey Kline. April 27, 2023. Managing Embedded Data Science Teams for Success: How Managers Can Navigate the Advantages and Challenges of Distributed Data Science. Harvard Data Science Review, 5(2). https://doi.org/10.1162/99608f92.1f068331}