Google VP for Applied AI for Google Cloud Duncan Lennox took to the stage for the Wednesday, March 19 Enterprise Connect keynote “5 Ways AI Will Transform Customer Experience and Collaboration,” and promptly laid out the five expected changes: transforming customer experiences, streamlining knowledge searches, fostering creativity, fostering collaboration, and automating coding and development processes.
Lennox says that, because of the introduction of AI agents and new developments in data infrastructure and cloud, there’s been a big from using AI for experimentation to using it to reinvent business processes. IDC has predicted that $152 billion will be spent on implementing AI capabilities into enterprise business operations in 2025.
“For the last decade or so, people have been standing on stage at Enterprise Connect, talking about how things like omnichannel personalization and proactive engagement are going to help us move support organizations from being a cost center to being a revenue driver,” said Lennox.
“But the reality is, for the last decade, the industry has struggled at adopting technologies, people, and processes to really ensure they can realize this kind of transformation. It’s no secret that AI holds enormous potential for both improving customer experience and driving operational and cost efficiencies.”
Customer Experience
According to a McKinsey study from 2023, Gen AI is capable of improving productivity in customer service by 30-45% and reducing the need for human service contact by 50%.
Lennox went on to say that of all enterprise functions, Gen AI has the highest impact on customer service productivity, and that AI can help organizations that are primarily focused on customer engagement and experience with deeper personalization, plus omnichannel and multimodal experiences. He then showed a demo for Google’s Customer Engagement Suite, which partners with Google DeepMind – a research laboratory – for real-time assistance with in-the-moment personalization to ensure the use of safe AI practices. The suite can provide real-time coaching through AI Coach, and also gives managers the ability to manufacture scenarios through AI Trainer for new and existing agents to learn or build on their skills through AI-generated chat and voice interactions.
Streamlining Knowledge Searches
According to McKinnsey, 89% of employees search across an average of 6 sources for information, with 45% of that information being irrelevant. Google’s Vertex AI creates a centralized hub for knowledge within the enterprise, allowing for keyword searches in multiple languages and modalities that is augmented by AI to understand context, allowing for more accurate results. AI can also help summarize, synthesize, and analyze data across multiple sources and provide insights. Vertex AI also has the ability to learn user preferences and provide relevant context and content based on their roles and projects.
“AI agents can streamline processes, manage repetitive tasks, answer employee questions, as well as edit and translate critical communications,” said Lennox.
Fostering Creativity
The keynote presentation cited a McKinsey report finding that 75% of the value created by Gen AI in expected to be in sales, marketing, customer operations, software engineering, and research and development, with AI being able to increase productivity by 5-15% in marketing organizations.
To that end, Google’s Vertex AI can now also be used to generate social media content and ads.
“Imagine crafting thousands of personalized social media ads, each optimized for maximum impact, all generated automatically,” said Lennox. These ads include original AI-generated images and copy, which are free of licensing fees – so the productivity gains also reduce both headcount and expenses.
Fostering Collaboration
According to Forrester’s Total Economic Impact study from 2024, there is a 30% improvement in collaboration for users of AI-enabled apps and a 40% improvement in the speed of finding and sharing information within teams.
Lennox says Google Workspace, is the AI-powered collaboration hub via meeting summaries and post-meeting action items, as well as real-time voice and chat translation. Users can also share research and data and create the first drafts of documents, emails, or slides. As Lennox said, “I’m sure I’m not the only one that’s stared at a blank screen trying to figure out how to get started.”
Google Workspace also has Notebook LM, where users can upload links to sources or documents and then ask AI questions about their content. It can also create an 8-10 minute podcast with two AI voices recapping the sources or documents.
Automating Coding and Development
Lennox says at Google, 25% of all new code is generated by Gemini Code Assist before being reviewed and accepted by engineers. “Code agents are helping developers and product teams to design and build new applications faster and better, and to ramp up on new languages and code bases. For employees, this means they can generate code or complete code as they write, convert natural language to code, and improve code quality and fix bugs.”
Code Assist not only helps developers write, debug, and optimize code, but it can also understand existing code bases and explain it to users, allowing for more efficient training for new engineers and developers.
Google’s Tips and Tricks on AI Adoption
At the end of the keynote, Lennox provided the audience with some insight on how companies can go about adopting AI effectively and responsibly. His first note was that companies should create an AI council to take charge of establishing guidelines, policies, and processes to ensure responsible AI use. They would also evaluate AI tools and establish measures to ensure that the company’s intellectual property was protected.
The second suggestion Lennox made was to monitor AI adoption and look for adoption gaps. “Different parts of your company will move at different paces, and that’s okay. You want to be able to provide the right information to them based on where they are in their production and help them move along with it.”
Lastly, he says that companies should identify and embrace Gen AI champions across all levels of the organization, then invest in upskilling and training the workforce to use AI more effectively and responsibly.