Q: How should business leaders approach the use of AI in their organizations?

When considering any new technology, business leaders must first identify and prioritize the problems they want to solve. Blindly applying AI without a clear objective is unlikely to yield positive results.

With the problems identified, business leaders should develop a clear strategy for AI implementation, including identifying required resources, setting objectives, and creating a timeline for the plan. The global nature of teams today means people are more spread out, however leveraging digital ideation sessions can be a collaborative way to explore how different types of AI can solve a particular challenge and generate new, innovative ideas.

During this phase, it’s also important to consider the ethical concerns of AI, such as bias and privacy, and develop the right policies and procedures to ensure responsible and ethical use.

With the problem and potential solution in place, business leaders should ensure that their organization has the necessary infrastructure and capabilities to implement and maintain AI solutions. AI relies on large amounts of high-quality data to function effectively. It also needs a level of expertise to implement and maintain. Roles including data scientists, software engineers, and other technical experts may be required. By taking these actions, business leaders can determine how AI may benefit their organization and develop a plan for successful implementation.

Q: What are some of the challenges businesses face when using AI technologies, and how can they overcome them?

 I mentioned a few challenges in my last response, but I’ll expand on those thoughts. One of the biggest hurdles is the need for more expertise in AI. Finding people with the necessary skills and knowledge to develop and implement AI systems takes work. Organizations must either invest in employee training programs or work with external partners with AI expertise to ensure their investment isn’t wasted. 

Data presents another challenge since AI technologies require high-quality data to produce accurate results.  Businesses may need access to more data, or improve the quality or organization of their existing data to be used by AI. Investments in master data management systems and data quality programs can solve these challenges and provide data in a format that can be used to develop and train a learning model.

AI can also raise ethical concerns, as I mentioned at our most recent Global town hall, and may be subject to regulations. Privacy, surveillance, bias, and discrimination are pressing issues related to AI. Businesses must develop the appropriate ethical guidelines for AI use and follow relevant regulations and standards, otherwise they expose themselves to compliance, financial, or reputational risk.

Lastly, developing and implementing AI systems can be costly. To overcome this challenge, companies can start small and focus on use cases in a specific area of their operations before gradually scaling up as they achieve the desired outcomes.

Q: What is the most important factor that will enable Avery Dennison to succeed with AI?

The most important factor that will contribute to our success in achieving value with AI is creating a culture of curiosity. Curiosity is the desire to learn something new and unfamiliar. Innovation is one of our company values, and to be innovative, one must be curious and use their imagination and intellect to create new possibilities. And, the possibilities with AI are endless.