Kearney and AWS Present Up to 22% Improvement Benefits with Manufacturing AI [A.T. Kearney]

A.T. Kearney K.K. (Minato-ku, Tokyo; Japan Representative: Takefumi Harigaya) has published "How the Kearney-AWS Partnership Helps Manufacturers Accelerate an AI Transformation." This paper, based on the partnership between Kearney and Amazon Web Services (AWS) to accelerate AI adoption in manufacturing, examines the use of AI and generative AI in manufacturing, implementation challenges, and the transformative support offered by the Kearney-AWS alliance.

The paper indicates that through the collaboration of Kearney and AWS, manufacturers can more quickly realize benefits such as 10-20% improvement in throughput, 8-12% reduction in unit costs, 16% improvement in overall equipment effectiveness, and 22% improvement in new product time-to-market. However, it identifies two main challenges in advancing AI transformation: difficulty in technology selection (tech paralysis) and lack of a clear vision and implementation roadmap. Additionally, five misconceptions about AI-driven transformation are hindering widespread adoption.

Kearney and AWS support manufacturing AI transformation in three stages: "Envisioning the factory of the future," "Developing a roadmap of initiatives," and "Deploying and implementing." Defining the ambition for AI utilization over the next 5-10 years, clarifying priorities, value cases, investment needs, ROI, deployment sequence, and required capabilities, then proceeding with technology implementation, capability building, and transformation management are crucial for capturing value from AI transformation.

Four metrics show up to 22% improvement benefits as expected effects of AI transformation

The paper presents four metrics for the benefits manufacturers can gain by accelerating AI transformation through the Kearney-AWS collaboration: 10-20% throughput improvement, 8-12% unit cost reduction, 16% OEE improvement, and 22% faster time-to-market for new products.

GenAI is positioned as an addition to the digital technologies manufacturers have adopted, integrating disparate technologies and enabling companies to restructure their operations. The paper emphasizes that AI transformation is not solely about automation but focuses on human-machine collaboration for better decision-making and efficiency.

Two key challenges and five misconceptions hinder comprehensive transformation

The paper highlights two main challenges manufacturers face in digitizing operations. First, "tech paralysis" due to numerous systems and platforms with undifferentiated functions, making it difficult to make informed decisions on which technology to adopt. Second, the lack of a clear vision and implementation roadmap for how AI-driven transformation fits into the overall enterprise and generates sustainable value.

Furthermore, the paper organizes five misconceptions about AI-driven transformation: it is purely a technology issue, it is automation-centric, it is costly and time-consuming with poor ROI, it requires a complete overhaul of existing systems, and its applications are limited to high-tech industries. Under these challenges and misconceptions, point solutions addressing individual pain points accumulate without leading to comprehensive transformation.

Three stages x 5-10 year perspective, connecting vision to implementation

The Kearney-AWS partnership outlines a three-stage approach for manufacturing AI transformation. Stage 1 defines the ambition for manufacturing enabled by AI over the next 5-10 years. Stage 2 designs an execution roadmap with clear priorities and value cases, clarifying investment needs, ROI, deployment sequence, required capabilities, and enabling requirements. Stage 3 implements technology, builds capabilities, and manages transformation to capture value.

Kearney leverages insights from its 30+ year annual Factory of the Year competition and best-in-class operations from surveys of thousands of factories worldwide to support manufacturing operations assessment, identification of pain points and potential solutions, and ambition setting. AWS plays a key role in solution scaling through pre-built industry solutions and industrial services, custom solution options, guidance on technology deployment and investment requirements, proof-of-concept construction, and technical implementation support.

The paper concludes that by combining forces, manufacturers gain what they need to embrace AI transformation and build capabilities to enhance productivity, resilience, sustainability, and profitability. Connecting vision, roadmap, and implementation—rather than treating AI transformation as a single tool deployment—is a critical point for value capture.

- About the paper

· Title: "How the Kearney-AWS Partnership Helps Manufacturers Accelerate an AI Transformation" · URL: https://www.jp.kearney.com/issue-papers-perspectives/how-the-kearney-aws-partnership-helps-manufacturers-accelerate-an-ai-transformation

- Supervisors

Takashi Oshio, Senior Partner Graduated from Waseda University School of Science and Engineering. After NTT Data and a US-based strategic consulting firm, joined A.T. Kearney. Focuses on scenario planning, new business building, go-to-market, portfolio restructuring, mid- to long-term management planning, M&A strategy, profit improvement, and operational reform for high-tech, telecom/ICT, electronics, and trading companies.

Shoichi Osanai, Partner Core member of the Strategy and Operations Practice at the office. Supports transformation projects for ICT companies, financial institutions, and manufacturing clients.

- About A.T. Kearney

A.T. Kearney (global brand name KEARNEY) was founded in Chicago, USA in 1926 and expanded to Japan in 1972. Its strengths lie in high expertise, tangible results, and close collaboration with clients. Today, it has offices in over 40 countries and about 5,900 staff worldwide, serving global 1000 companies and major corporations/government agencies across all major industries with consistent high-quality services from strategy to operations and IT. For more details, please visit www.jp.kearney.com