Augmenting compliance workflows: AI integration at Avery Dennison

Abstract

Avery Dennison is a leading manufacturer of self-adhesive labels. The company relies on its Product Compliance team to ensure that every product meets the latest health, safety, and environmental standards. These regulations continue to evolve in complexity, placing significant demands on a group already tasked with managing a large volume of customer requests and databases.

This report explores which compliance tasks act as bottlenecks in the Product Compliance team’s workflow and how AI could be integrated to assist in these tasks to improve overall work efficiency. The approach included reviewing existing studies on AI and interviewing several team members and technical sales specialists within the company.

Findings from these interviews indicate that the compliance team's main pain points are the repetitive nature of some of their tasks (e.g. compliance requests from customers) and the difficulty of managing fragmented data across emails, spreadsheets, and databases. For example, the compliance team often needs to copy and paste compliance statements, update spreadsheets, and answer similar questions over and over again. These everyday tasks can take up an entire day, leaving less time for more strategic or complex work. The interviewees also shared that they often spend too much time looking for information scattered in different places, which slows their workflow down. Moreover, the report highlights a few concerns about using AI for compliance data. One worry is about accuracy: since compliance work requires precise information, even a small mistake by an AI system could lead to serious issues. There is also the risk of exposing confidential information, so any AI tool used must be secure and protect sensitive data.

Based on these findings, the report makes several recommendations for Avery Dennison and how AI could overcome some of these bottlenecks. For a more detailed discussion and accompanying figures, please refer to Chapter “Recommendations and Conclusion.” First, the company should create a clear strategy for the adoption of AI within the compliance team. This begins with executive discussions on its feasibility, followed by small-scale pilot projects targeting repetitive ‘’bottleneck’’ tasks, and gradually expanding as AI tools demonstrate value. For instance, AI could for help with extracting data from large unstructured documents, draft emails, and eventually help with responding to simple compliance requests from customers. In light of this, it would be helpful to build a single, centralized database where all compliance-related data is stored. With all the information in one place, AI systems can work more accurately, and team members would find it easier to get the information they need, also without an AI tool. Lastly, the report emphasizes that AI should be seen as an augmentation rather than a replacement for employees. While AI can handle many routine tasks, employees are still needed to check its work and make sure everything is accurate.

In conclusion, integrating AI into Avery Dennison’s Product Compliance workflow can significantly ease repetitive ‘’bottleneck’’ workloads and allow the team to concentrate on more complex, and strategic work. The company can augment workflow efficiency within the compliance team by implementing a well-defined, department-specific AI adoption strategy, centralizing data, and enforcing strict data security measures to leverage AI’s benefits.