One week after showcasing a family of six GenAI agents spanning key functional areas and personae, Google Cloud has released a list detailing how 101 customers across a vast range of industries are using those GenAI agents to drive innovation, growth, productivity, and customer engagement.
In a blog post headlined “101 real-life genAI use cases from the world’s leading organizations,” VP of product marketing Brian Hall said customers are “increasingly focused on improving productivity, automating processes and modernizing the customer experience.” Aided by Google Cloud’s broad range of AI and GenAI models, those customers are developing agents to help boost performance and outcomes in six key areas:
- Customer service
- Employee empowerment
- Creative ideation and production
- Data analysis
- Code creation
- Security
At the Google Cloud Next event last week, various company executives as well as customers described how these agents are able to engage with people as well as with other agents to achieve the outcomes listed above. And they are being deployed with increasing frequency and increasing effectiveness in industry-specific applications, some of those customers said during Next.
One big factor in those high-value deployements, Hall wrote in his blog post, is the ability of these GenAI agents to “handle tasks across a range of communications modes, including text, voice, video, audio, code, and more. With human support, agents can converse, reason, learn, and make decisions.”
In that post, Hall does indeed list 101 use cases with some details on each, and those examples are organized into six groups based on the type of agent being deployed. As business leaders race to get GenAI projects into production, I would encourage anyone interested in this type of innovation to read Hall’s post. And of the 101 examples Hall offers, here are my 10 favorites, grouped by the type of agent the customers have created.
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Customer Agents
1. “Samsung is deploying Gemini Pro and Imagen 2 to their Galaxy S24 smartphones so users can take advantage of amazing features like text summarization, organization, and magical image editing.”
Employee Agents
2. “Bayer is building a radiology platform that will assist radiologists with data analysis and intelligent search to create documents that meet healthcare requirements needed for regulatory approval. The bioscience company is also harnessing BigQuery and Vertex AI to develop additional digital medical solutions and drugs more efficiently.”
3. “The Home Depot has built an application called Sidekick, which helps store associates manage inventory and keep shelves stocked; notably, vision models help associates prioritize which actions to take.”
4. “McDonald’s will leverage data, AI, and edge technologies across its thousands of restaurants to implement innovation faster and to enhance employee and customer experiences.”
Creative Agents
5. “Carrefour used Vertex AI to deploy Carrefour Marketing Studio in just five weeks — an innovative solution to streamline the creation of dynamic campaigns across various social networks.”
6. “Procter & Gamble used Imagen to develop an internal gen AI platform to accelerate the creation of photo-realistic images and creative assets, giving marketing teams more time to focus on high-level planning and delivering superior experiences for its consumers.”
Data Agents
7. “Kakao Brain, part of Korean technology company Kakao Group, has built a large-scale AI language model that is the largest Korean language-specific LLM [large language model] in the market, with 66 billion parameters.”
8. “Mercado Libre is testing BigQuery and Looker to optimize capacity planning and reservations with delivery carriers and airlines to fulfill shipments faster.”
Code Agents
9. “Wayfair piloted Code Assist, and those developers with the code agent were able to set up their environments 55% faster than before, there was a 48% increase in code performance during unit testing, and 60% of developers reported that they were able to focus on more satisfying work.”
Security Agents
10. “BBVA uses AI in Google SecOps to detect, investigate, and respond to security threats with more accuracy, speed, and scale. The platform now surfaces critical security data in seconds, when it previously took minutes or even hours, and delivers highly automated responses.”
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