I recently hosted an artificial intelligence summit at this year’s eTail West conference in Palm Springs, Calif., featuring additional presentations from large retailers, mid-market ecommerce brands, startups and AI software providers. The excitement among attendees about the power of AI tools was palpable.
One presenter shared an intriguing story about fostering a culture of experimentation within retail organizations, which is vital for adoption and understanding of new tools, like AI solutions.
This company created a weekly contest for employees to submit AI-generated content, ranging from jokes to cooking recipes. This foundation of experimentation allowed the team to rapidly identify and implement AI use cases to improve productivity.
A necessity for efficiency
Key areas included marketing, product creation and website optimization. AI advancements in photography, promotional video production, search engine optimization and product descriptions demonstrated clear improvements in content creation time and cost reduction.
One presentation discussed a company’s ability to generate product photography in hours compared to weeks or months to plan, shoot and process. This cut down significantly on costs and the time required to launch new projects.
AI’s impact on productivity is becoming evident across industries. According to the Federal Reserve Bank of St. Louis, workers are 33% more productive during the hours they use generative AI. Additionally, employees using AI reported saving an average of 5.4% of their work hours per week, translating to a 1.1% increase in overall productivity. These gains suggest that AI integration is not just a competitive advantage but a necessity for efficiency.
A significant disruptive topic was the emergence of AI agents for shopping. For decades, search engines have driven ecommerce demand and purchase needs, creating entire businesses with search engine optimization expertise to address and promote product visibility.
Now, generative AI agents are poised to disrupt the ecosystem by curating personalized shopping experiences. By using large language models to generate copy and data, along with additional logic, AI agents can now do the work faster and more efficiently. This shift requires companies to understand and optimize their content for these agents, like descriptive text that defines products.
Additionally, companies should focus on third-party review sites like Reddit, which are prominent in agent data sources. Frequent testing by teams is also necessary to understand how agents are recommending their products.
Implementing AI
Companies are developing frameworks to manage AI tools effectively. Common implementation themes discussed at the summit included:
- Developing use cases—Leveraging a culture of experimentation, companies relied on subject matter experts to identify use cases that enhance daily workflows, improve customer experience, and increase employee satisfaction.
- Data strategy—Effective AI solutions require robust data. Companies focused on their systems and available data to build these solutions.
- Data governance—Ensuring efficient operation without negative bias, mitigating data security risks, and compliance with policies were crucial.
- Measurement of ROI—Companies developed methods to measure the value of AI solutions to prioritize time and investment effectively.
The takeaway
AI adoption in retail is rapidly accelerating. According to Nvidia’s State of AI in Retail and CPG report, 42% of retailers are already using AI, while another 34% are piloting AI initiatives. Furthermore, the World Economic Forum’s 2023 Future of Jobs report found that 77% of companies (including retailers) globally plan to retrain or upskill workers for AI, while 41% plan to reduce roles that become redundant.
It’s clear. AI is enhancing productivity. Retailers that foster a culture of experimentation and innovation, and harness the power of AI will lead in growth, productivity and market share in the coming years.
