There was no shortage of customers at Google Cloud Next 2025 as the company is hitting its enterprise stride with a focus on industries, use cases and integrating AI agents.

Here’s a look at customers at Google Cloud Next their takeaways and best practices picked up along the way.

Google Cloud Next coverage:

Volkswagen

Volkswagen's Steve Lancaster, Director of Connected Car Development, Operations and Connected AI for the America region, is responsible for apps, IoT platform and AI efforts. Volkswagen has been a Google Cloud customer for about 16 months.

Lancaster said the data streaming from cars and apps is valuable feedback. The problem was Volkswagen didn't have the visibility into the content and data to improve customer experiences.

"There's a lot of feedback and direct contact with the customer through this application, and we pay a lot of attention to what they're saying," said Lancaster. The requirements for Volkswagen revolved around search across multiple data types and documents and models that can learn and answer customer questions.

"We're using Gemini to really understand customer intent and Vertex AI to really break data down into its proper form and return answers. We know the most about these vehicles and we need to make that information readily available," explained Lancaster.

Best practices:

  • Follow the playbook and Google Cloud roadmap. Lancaster said it helps to learn the basics blocking and tackling on the platform to improve data and AI core competencies.
  • Focus on business results. Lancaster said he wouldn't talk about ROI savings, but said there are fewer calls to customer service. The feedback from the app provides signals as does sentiment on social media. "Customer satisfaction is measurable and tangible, and we're watching them closely. We get all kinds of feedback from the app, from the thumbs up, thumbs down to very specific comments about how it's interacting, or what they're thinking," said Lancaster. "At the end of the day we're selling cars. If we can impact the owner experience and brand loyalty that's a big measure."
  • Know your own user stories before you engage. You know your business better than anyone else and have the data before engaging.
  • Clean up your data so it's AI ready ahead of the AI project.
  • Beware of the "laptop AI guy" who shows what was possible with a model. Lancaster said AI is an IT project that needs security, compliance and everything you need in the enterprise.

Best Buy

Ashley Daniels, Vice President of Product Management at Best Buy, said the retailer is in a broader customer care transformation and moving beyond stitching together experiences beyond the call center.

Daniels said genAI is enabling agents to lead with empathy since AI can take the notes. "We're now in the IVR and chat bot transformation," said Daniels, who said Best Buy has been transforming its customer engagement and experience for the last 18 months.

Best practices:

  • If you have contact center use cases, there are plenty of ROI measures. Daniels said the previous IVR system would route to an agent when a customer tried to cancel a membership. The problem was an inconsistent experience. Now Best buy can pull data on savings and coverage for devices and increase the save rate. "The day it went live the contain rate went form 9% to 50%," she said.
  • Continually optimize. Daniels said Best Buy continuously changes the system to leverage AI and tweak the experience.
  • Create human experiences using AI. Don't lose track of the human element.
  • Best Buy using AI agents going forward will improve customer satisfaction and drive revenue, said Daniels.

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Geotab

Neil Cawse, CEO of Geotab, has a business that manages vehicle fleets. Geotab leverages Gemini in its products and in analytics as well as Workspace.

Cawse said Geotab is focused on data residency and where it resides. "We can't tolerate data being in the wrong places," said Cawse.

Best practices:

  • Focus on adoption. Cawse said the company is following the usage data. By tracking usage, Cawse was able to discover that HR didn't use Gemini nearly as much as marketing.
  • Notch small wins. Geotab uses town halls to highlight examples of good AI usage internally.
  • Find new ways of working. Processes and workflows change with LLMs.
  • "We have the opportunity to leverage AI to take away the laborious work and enable AI agents to automate tasks," he said. "Humans will still run the show, but you'll have agents running behind the scenes doing the work."

Gamuda Berhad

John Lim Ji Xiong, Chief Digital Officer at Gamuda Berhad, said his Malaysia-based construction firm is focusing on AI via Google Cloud and "trying to insert technology for all of our property and construction business."

Xiong said Gamuda Berhad has 164 agents in production. He said:

"We're at 164 across all sorts of different areas, whether it's contract analysis, whether it's looking at the design documents, whether it's looking at tender documents, being able to speed up our time to put in proposals, being able to also then get information across the organization, whether it's Australia to Malaysia. We're seeing a 20% increase in our funnel."

"These are customers that would not have necessarily come through our sales gallery, but they are interacting with us already."

Best practices:

  • Transform your industry. Gamuda Berhad is now starting a tech services unit to branch out from construction.
  • Gamuda Berhad has just completed the second phase of its transformation by consolidating data in BigQuery. Now the plan is to leverage data to "create a crystal ball for construction," said Xiong.
  • Upskill. Xiong said his company has created an AI academy to get people from all walks of life to learn AI. "We use a full-stack syllabus," he said. "We can get people up to speed in three months." The company has graduated two classes of 50 and is expanding the class to the rest of the country.
  • Build a talent base. Xiong said his company is hiring some of those graduates.

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WPP

Stephan Pretorius, CTO WPP, said the advertising firm started out with Google Cloud focused on workflows and when genAI landed the company started using it for content and ideation.

"As the models have become more capable, the latest unlocks for us have been video and we saw an explosion of video usage inside the business," he said. "Going in we saw a new pattern of behavior."

WPP also has 2,800 agents in production for contract review, CRM automation and other use cases.

Best practices:

  • Pretorius said enterprises need to focus on adoption, change processes and the way they think. "Adoption is a huge metric. We track, time spent and tasks," he said.
  • AI can drive new ideas quickly and you pretest concepts for media campaigns as well as returns for customers. But unit economics are a challenge. WPP used to charge for creative by new sizes and markets. Now that revenue stream is gone.
  • "For most of our clients, AI is enabling them to keep their spend and get same reward or spend more to get more," he said.
  • Embrace the business changes and adapt. WPP's business model has changed dramatically.
  • Focus on ecosystems. Pretorius said it makes sense to pick vendors that work across systems and data stores. Open ecosystems matter so you don't get boxed in architecturally.

Palo Alto Networks

Palo Alto Networks' Rajesh Bhagwat, Vice President of Engineering at Palo Alto Networks, is responsible for data platform and AI. Palo Alto Networks has been a Google Cloud customer since 2020.

He said Palo Alto Networks cloud transformation aligned with the overall product strategy, which now revolves around its Cortex platform today. Bhagwat said Google Cloud was able to offer real time data analysis via BigQuery.

Best practices:

  • Focus on tangible business returns. Bhagwat said uptime and customer satisfaction. Palo Alto Networks was able to reduce its mean time to resolution for customer issues. "When a case comes in, the support personnel is using AI assist for a quick respond back. The AI assistant knows the customer context, knows all the data is using the underlying models bring out all the reasoning, all the analysis," he said.
  • Know whether you should build or buy. Bhagwat said enterprises need to know their core competencies. It was clear that Palo Alto Networks wouldn't train its own models and run massive data centers at scale.
  • Prepare for scale. Bhagwat said scale matters. Plan ahead for it. Palo Alto Networks manages 5.5 petabytes of data each day.
  • Address skill gaps via learning but balance between broad and deep knowledge of AI. Look at new hires through the lens of AI readiness.

AI21

Pankaj Dugar, Senior Vice President and GM at AI21 Labs, said the company which develops models is using Google Cloud for infrastructure.

"As a company we do two main things. We build highly optimized foundation models. And we recently launched an AI planning and orchestration system," said Dugar.

Best practices:

  • Leverage hackathons to find talent and upskill as new technologies emerge. Dugar said AI21 connects his engineers to Google Cloud experts to learn how to use new features and services.
  • Be an early adopter. By adopting Google Cloud services early, AI21 creates a feedback loop to improve products on both sides.

Citigroup

Citigroup CTO David Griffiths said the banking giant is leveraging Google Cloud as part of its multi-year transformation. "Anywhere we work with digital transformation, AI can help. We are embracing AI as a universal enabler," said Griffiths.

Griffiths outlined the strategy and best practices:

  • "We've been guided by a couple of simple principles, with taking a very deliberate approach. We build a simple, scalable, secure, multi-model platform that has centralized controls and observability, so we can keep everyone safe, and we can learn and observe across the breadth of all of our AI interactions."
  • "We think about the impact of AI in two dimensions: General, horizontal, assistive AI tools that have very wide applicability. These may only give you 1% to 3% of productivity back, but you scale that across the company, this really adds up. And you have to complement that with deeper AI verticals, specialized capabilities for the specialists within your workforce."
  • "A scale footprint allows us to maximize the impact as this technology advances. Google is at the frontier of AI development, and we want to have a mini lag between AI innovation and AI impact."

Griffiths added that Citigroup had about 1,000 use cases in 2024 at various stages. Those use cases were horizontal and could benefit the entire organization. In 2025, Citigroup is focused on scale and depth and "industrializing our AI verticals" for customer servicing, fraud detection, finance and sales and marketing.

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Citigroup’s journey

Pearson

Pearson CTO Dave Treat said the education and learning company is transforming to "use AI to help educators and students transform learning across all stages of life." And the company is betting on agentic AI.

"We've realized it's time for us to think outside the book, and we're really just at the beginning now of creating super effective, personalized learning experiences using agents," said Treat. "We're envisioning a team of agents working together on behalf of educators and students using natural language interfaces integrating all of the tools and resources that they need guided and shaped by our learning science and trusted content."

Treat noted that agentic AI will change its engineering and software development lifecycle. Pearson is using specialized agents for code, documentations, and testing scripts.

According to Treat, Agentspace will be the control plane for multiple agents including ones from Salesforce and ServiceNow. Treat's take highlights how hyperscalers may be best suited to orchestrate AI agents across systems. "Just like humans, there's going to be the right agent for the right job," said Treat.

 

 

Business Research Themes

Data to Decisions, Future of Work, Innovation and Product-led Growth, Next-Generation Customer Experience

Roles

Chief Information Officer

Tags

@googlecloud, #AI #artificialintelligence #machinelearning #ML #generativeAI, agentic AI