AI Tackles Data in Retail and Banking: Insights from Google Cloud Next ’24




It wasn’t long ago that the tech industry was just beginning to imagine how generative AI could transform businesses. Fast forward to today and generative AI is enabling business growth, enhancing client experience, improving developer productivity and increasing operating efficiency. We can use search technology to find and purchase a jacket that our favorite artist is wearing in a music video, we can produce live images to supplement a traveling camera crew, and we can empower our workforce to better and more quickly serve customers. 

“We’ve seen rapid innovation and we’re now at a stage where practical application of [generative AI] is showing the potential to yield real value for the business…We want to be thoughtful in how we approach and harness this technology, both as a mechanism to drive efficiency and as an enabler of disruption and differentiation for our clients.”

– David Solomon, Chairman and CEO at Goldman Sachs

The Fletcher Group joined 30,000 digital AI leaders at Alphabet’s annual Google Cloud Next conference in Las Vegas last month to hear how global brands are solving for tomorrow’s AI challenges today. With no shortage of Google announcements – all 218 summarized here, including Google Vids coming to Google Workspace – it is clear enterprise AI products are driving value and transforming daily tasks into smart, automated processes. 

With our team’s keen focus on the banking and retail industries, here are a few of our favorite takeaways. 

AI for Banking 

We can appreciate the introduction of AI isn’t new, but as the financial services industry relies on data, how executives use AI to manage, analyze and leverage data is ever evolving.  

A discussion with banking executives from Scotiabank, Discover, IntesaSanpaolo and Macquarie Bank, highlighted how generative AI and cloud functionality help streamline core banking services and personalize customer experiences. To optimize a shift to the cloud, banks must take a rational approach to security to accept a manageable level of risk, use personal identifiable information (PII) to increase personalization and maintain a digital-first mindset in all facets of the business. From a product standpoint, being digital-first means a customer must be able to use a mobile app, online portal, chatbot, call center and branch seamlessly and interchangeably. This omnichannel flexibility is an important step in efficiency.  

AI and cloud services have also benefited other banking areas such as: 

  • New features: Producing monthly statements of transactions without context is no longer the standard. Banks can move faster to develop and implement new features to delight the customer. For example, AI can produce cash flow predictions and real-time variable mortgage rate reviews to better inform purchase decisions. Customers can also add hashtags to their transactions (ie. #tax) for faster online sorting and reporting, saving time and stress. Adding context to our spending patterns drives value for the everyday consumer. 
  • Talent focus: As the industry normalizes the use of AI products, there will always be a human in the loop to manage risk and build trust with customers, however the goal is to continue finding efficiencies to move at the pace of AI development. With more data in the cloud, a team can spend less time chasing down and analyzing data to better deliver on the promise of personalized services. For example, call center agents can search and summarize hundreds of documents faster to reduce wait times.  
  • Business ownership of data: It’s not only that AI is getting smarter, but internal teams are getting more adept at collecting, managing and sorting data to make products better and improve internal operations. This is a great example of how AI can be used to elevate the role of data teams to use customer data in more efficient and impactful ways. At the show we saw a lot of excitement around the potential here.

AI for Retail 

It’s getting tougher to win in the world of retail. Customer expectations are increasing – 70% expect personalization, 75% want a seamless omni channel experience and 90% will continue to switch brands (as shared by Google Paul Tephenhart). As marketers, we must help drive value for retailers across digital commerce, marketing, store operations and supply chain. Recognizing the importance of personalization, generative AI can help retailers focus on what really matters to their customers. 

“As we think about the journey, there’s not a piece of the customer journey that won’t have AI included in some degree in the next 18-24 months. The companies that are going to win are going to be the ones that are stitching that experience together end-to-end, and not delivering different point solutions.”

– Ashley Daniels, Vice President, Product Management at Best Buy

When discussing AI innovations in retail, a few business areas stood out: 

  • Customer support: The contact center is a key channel for retailers and an important component in cementing customer loyalty. For decades, agents have been required to multitask – answering calls, note-taking, analyzing, sourcing a solution, etc. – in record time. Chatbots are evolving into intelligent digital assistants (IDAs) which will continue to reduce the cognitive load for these employees, by summarizing calls through AI, for example, or filtering through documents. This reduces distractions and allows employees to focus on listening to customers.
  • Staffing: The hiring profile has traditionally been focused on institutional knowledge (who knows the product, technology, and industry best in a group of applicants), but AI has helped create a world where companies can remove that barrier. Hiring teams can focus on evaluating who can show strong empathy and offer a truly personalized experience across the customer journey. 
  • Operations: With the rapid pace of innovation, it can be tempting for retailers to quickly launch an AI tool or functionality. We must remember that teams are building AI as these builders are trying to adopt it themselves. This rare technological crossroads can put a strain on developers. But successful companies will ground how they use AI in the customer experience and in actual friction points. We mustn’t lose ourselves in the rush.

Looking Ahead 

Personalization is a powerful cornerstone and generative AI will allow us to meet customer expectations across banking, retail and other industries more quickly and more consistently. For companies looking to be at the forefront of change, they must be nimble and open to it. This may include re-thinking your skills base and proactively discussing AI priorities to better implement and leverage enterprise AI tools. With AI ever-present, we can agree one thing remains constant: the art of possibility today will be different tomorrow.