Reimagining the customer experience with generative AI – part 2

In just the past few months we’ve seen a big shift in the generative artificial intelligence (AI) landscape. Today, business leaders want to dive deeper. They’re more interested in implementing these tools and seeing how it can drive the business forward. Executives in retail and consumer packaged goods (CPG) in particular are exploring how AI will impact their industry and change how they lead their organizations.

Amazon Web Services (AWS) is at the forefront of the generative AI revolution. Watch my recent video interview: The Impact of Generative AI, Part 2 with Jeffrey Woldt, of the Chain Drug Review, to learn more.

To be sure, changemakers in retail and consumer goods will always have their finger on the pulse of their companies’ core operations, like issuing quarterly reports and closing the books on time. It’s natural to be a bit cautious whenever a new technology, like generative AI, enters the fray. It’s also not uncommon to hear brand executives ask questions like, “How do we balance traditional data analytics with the new frontier of generative AI?”

It’s a topic that’s very close to the heart of business leaders today. Retail and CPG companies are used to working with huge sets of data that come to them at unprecedented speed. A lot of time goes into organizing that data and manipulating it in a way that offers business insights and competitive advantages.

What if companies were able to dedicate more time and energy to asking better questions about their data?

This is where generative AI can step in. It opens up the possibility for businesses of all sizes to be more creative with their time and gather better insights from consumers while also handling upfront data integration and cleansing. By diving into the generative AI space, brands are in a great position to focus their resources more intelligently and inquire deeper into their data.

Challenges on the horizon

Retail and CPG companies around the world have had their fair share of questions when it comes to adopting generative AI. People from the C-suite to the IT team, and everyone in between, want to know how to start testing its capabilities without disrupting business operations. Following are some of the most common challenges we’ve seen companies of all sizes grapple with:

• Privacy and security. Leaders want to know the risks associated with running generative AI models on their data. Given how many devices we have inside and outside the workplace, it’s vital to understand who can access and search your data, where, and when.
• Governance. Developing a responsible user framework for those who are feeding data into generative AI solutions is critical. Companies need to cover all their bases when thinking about the kind of data being collected, including identifying any biases inherent in a given model, and deployment and copyrighting concerns. They also need to educate stakeholders on the topic of generative AI in order to increase their exposure to its many uses.
• Scaling. Depending on the size of the company, the advantages of adopting generative AI can vary widely. Smaller businesses will likely already have cloud-enabled ERPs and point-of-sale systems in place that make it easier to plug their data into generative AI models. Large global retailers have other concerns, like avoiding data leaks and creating specific use cases that fit the needs of their brand identity.

Where generative AI is heading in the future

There’s no question that generative AI has changed the landscape of the retail and CPG industry. Since the start of the year, we’ve seen a surge of interest in this groundbreaking technology. Executives and IT pros have been deluged with information from all sides of the AI topic, both its upsides and its operational challenges. What remains is to see the big picture.

One thing is certain: generative AI isn’t just for industry giants.

This technology is for everyone. Already we’re seeing smaller companies disrupt markets using the many capabilities and support structures these tools provide. Every time we hear about a certain AI model that isn’t perfect, we see those same models improving rapidly week by week as they’re exposed to larger datasets and more complex supply chains.

Generative AI is also changing the culture of people working in retail and CPG—not unlike what happened in the cloud computing revolution. With AI it’s now possible for companies to access better data and spin up new capabilities in a fraction of the time required in the past. At the same time, the commitment to investing in revolutionary tech is growing at a rate we’ve never seen before.

As we forge ahead in the generative AI space, it can sometimes seem like we’re stepping out into the unknown. Yet the competitive advantages, cost savings, and revenue-driving power of this exciting new tool are sure to dominate the conversation for years to come.

Interested in staying up to date on generative AI on AWS and how it can help your company innovate faster and reinvent customer experiences and applications? Check out my video interview: Generative AI’s impact on retail and CPG, Part 1 with Jeffrey Woldt of the Chain Drug Review to learn more. Watch Generative AI’s impact on retail and CPG, Part 2 for further insights.

Contact an AWS Representative to know how we can help accelerate your business.