USA
UK
Canada
France
Germany
Italy
Spain
When Joseph Weizenbaum designed the first generative AI model in 1966, no one could have predicted its impact. Fast forward, 60 or so years, and the technology has quickly been adopted by enterprises eager to increase efficiency.
And the retail sector is no exception as generative AI has massively impacted everything from supplier negotiations to the consumer shopping experience.
To understand how Fortune 500 retailers maximize the ROI of generative AI, we caught up with Brad Thompson, the Senior Vice President of Data Sciences at Target on the Data Humanized Podcast. Here are the key takeaways from his discussion with Data Humanized Host, Mark Palmer.
Takeaway #1: Retail is ripe for generative AI applications
The retail industry sits on vast amounts of data, which makes the use of generative AI and data science models particularly exciting.
Retail as a business vertical is a really fun place to be a data scientist, a data analyst, or anybody working with data because retailers sit on vast, vast amounts of data. Whether it's supply chain data, our operations data, or interactions with the customers and all the data that spawns transactions — we have lots of data. It's like being a kid in a candy store.”
With so many data points to analyze, from web search queries to customer support chats, generative AI:
- Improves workforce efficiency through process automation
- Accelerates the speed at which data-driven insights can be generated and actioned
- Makes workflow management easier at scale
- Has many retail use cases from regional reporting to supply chain management
Takeaway #2: Workforce generative AI use requires training
Generative AI integration at Target didn't just happen miraculously. During the initial adoption, many employees at Target didn't quite fully understand how to leverage generative AI in their role, so this workforce skills gap was addressed with training.
Like any new technology, you have to train and teach people. You have to understand that people are going to make some mistakes. But when it comes to using something like a ChatGPT or BARD or anything else, you do have to let people know, hey, here's the kind of information that it's okay to include, say, in your prompts, and here's absolutely information that you can't.”
Takeaway #3: Don’t presume skills proficiency — even from technical roles
Even though most of the Target employees Brad works with have a technical background, generative AI is still a relatively new concept. It’s a technology that has a learning curve and requires a mindset shift from even the most technical teams.
Initially, some of Target's engineers struggled to use generative AI because they treated it like a search engine. If an engineer had a question on how to perform a task, they might ask the generative AI tool to provide a step-by-step solution instead of asking it to accomplish the task itself.
You would think, OK, technologists, software developers, they're going to be super savvy on how to interact with [generative AI]. But one of the things that we discovered is that a lot of them were just sort of thinking about it as a super Google. A lot of people weren't thinking of it as an actual tool that you could ask to perform tasks for you, to help to actually write code for you that you could then troubleshoot and debug. So we had to teach them that it's not just a place to go ask questions, it is a companion that you can put to work.”
Brad’s experience at Target highlights why:
- Technical proficiency should never be assumed
- Generative AI training initiatives should span across your organization
Takeaway #4: Nurture a hub of generative AI experts through mentorship
To keep generative AI adoption and integration moving forward, it’s important to nurture generative AI early adopters and evangelists. An internal community of experts is beneficial as it helps:
- Accelerate innovation
- Retain AI talent
- Increase generative AI knowledge
- Drive widespread adoption of AI tools
Brad notes the emphasis that Target places on mentorship for its technical talent:
You'll find the more senior technical staff kind of giving advice, coaching feedback on code, architecture, or design, and all of that is part of the mentoring process. Sometimes we will have people be mentors if it is their aspiration to someday lead people and they are trying to get experience in order to qualify themselves for supervisor roles or leaders of people roles."
Takeaway #5: Foster innovation and engagement through learning and development
With workforce disengagement at an 11-year low, it’s unlikely that employees are proactively looking for innovative solutions to organizational challenges. However, that can change if you prompt the workforce.
Take Target's 50 days of learning for example. The initiative allows employees to spend up to 50 days a year investing in their learning and development. On the podcast, Brad elaborated on Target's 50 days of learning program by explaining:
It can take the form of participating in a hackathon. It could take the form of going to an industry conference. It can take the form of listening to podcasts, all in service to skills development, learning about trends that are happening in technology, learning about new languages that maybe they want to build in, new types of architecture, even business strategies, and problems to help the technologists better connect to what Target is trying to achieve as a company.”
Scaling AI in retail: Key lessons from Target
Generative AI has already reshaped retail operations, unlocking new efficiencies and innovation across the value chain. From supply chain management to supplier negotiations, the future of retail will be dominated by those who embrace generative AI.
As Brad Thompson shared, the key to maximizing generative AI’s ROI lies not just in adopting the tools but in equipping the workforce with the skills to leverage them effectively. With ongoing training, mentorship, and a culture of learning, you can increase your competitive advantage and stay ahead of other retailers.
Increase your AI readiness with the How to get started with generative AI toolkit.