Analyst(s): Nick Patience
Publication Date: October 15, 2024
The recent Google Cloud Summit in London showcased Google’s confident and aggressive strategy aimed at establishing the company as the leading provider of AI platforms and tools for businesses. The event emphasized the breadth of Google’s AI offerings, spanning cutting-edge foundation models such as Gemini to robust infrastructure and data management solutions. Google’s messaging underscored its commitment to not just providing tools but also enabling businesses to integrate AI into their operations and realize tangible benefits.
What is Covered in this Article:
- The announcements from Google’s Cloud Summit held in London and the other insights gleaned from the event.
- Google’s position in the AI Landscape and how it differentiates from its main cloud competitors.
- The centrality of Gemini – a multifaceted family of models – to its strategy as well as developments and enhancements to the Vertex AI development platform and its early forays into agentic AI.
- Examples of real world AI use cases in financial services, insurance, retail, and other industries.
The News: The Google Cloud Summit in London showcased Google’s confident and aggressive strategy aimed at establishing the company as the leading provider of AI solutions for businesses. The event emphasized the breadth of Google’s AI offerings, spanning cutting-edge foundation models like Gemini to robust infrastructure and data management solutions.
Google Cloud’s AI-First Vision: Empowering Businesses for the Generative AI Era
Analyst Take: Google has legitimate claims to have invented generative AI. After all, it was Google researchers that came up with the first transformer language models in 2017, which considered all the words in a sentence at once, rather than in a sequential order. It followed this with its Bidirectional Encoder Representations From Transformers (BERT) model in 2018 and added it to its web search engine in 2019. But as is often the case, the company that invents something isn’t always the one that benefits the most from it. Google recognizes that and is determined to do something about it. The recent Google Cloud Summit in London showcased a lot of things that Google reckons makes it different from its competitors – AWS, Microsoft, and its tight partner, OpenAI.
Gemini and Vertex AI
Positioned as a key differentiator, Gemini powers a diverse array of applications, from code translation and threat intelligence to document summarization and data insights. Google repeatedly emphasized the cost-effectiveness of Gemini, particularly Gemini Flash 1.5, claiming it outperforms competitors in terms of both price – 50% below its nearest competitor – and performance. This aggressive pricing strategy suggests that Google is serious about gaining market share and making Gemini the go-to LLM for enterprises. One executive told us the pricing made it so cost efficient that Flash was effectively cheaper than using the open source Llama models from Meta. Google announced a UK-resident version of Flash so UK organizations can use it in compliance with their data residency requirement.
Vertex AI, Google’s machine learning platform, also took center stage as the foundation for building and deploying enterprise AI apps. Vertex AI provides a comprehensive suite of tools for developing, training, and managing AI models. The platform’s three layers – Agent Builder, Model Builder, and Model Garden – offer flexibility and cater to various levels of AI expertise. The Agent Builder, in particular, highlights Google’s focus on enabling businesses to create AI-driven agents that can enhance customer and employee experiences.
Industry Transformation
The summit was not short on real-world examples of how Google AI is transforming industries. HSBC’s implementation of AI for dynamic risk assessment in anti-money laundering demonstrated significant efficiency gains, including a 70% reduction in the number of cases that investigators need to work on, enabling the same investigator to see a case through from start to completion.
Admiral, a leading insurance company, showcased how AI is being used to improve customer experiences and streamline operations. Admiral built a car damage assessment app using Google, which told customers what their cash settlement would be. However, after rolling it out in Spain it was so fast in coming back with an amount that some customers thought it couldn’t have worked that fast, so Admiral chose to sit on the information for a day before informing customers.
In the retail sector, Kingfisher Plc and one of its subsidiaries, Screwfix demonstrated an image search function on its website, which was ideal for a lot of customers for whom English wasn’t their first language. Multimodality was a recurring theme among customer examples at the Summit. Google customer WPP demonstrated an impressive internal tool called Creative Studio built using Vertex AI, which has 25,000 active monthly users inside WPP, enabling users to accelerate creative tasks as well as build their own agents.
Data, Data, and More Data
Recognizing that there is no AI without good data AI, Google also addressed the challenges of managing and leveraging vast datasets. BigQuery, Google’s data analytics platform, was positioned as a critical component for bridging the gap between foundation models and real-world data. Google announced the general availability of Data Insights in BigQuery, aimed at data analysts, while AI-associated data preparation was launched in Preview to accelerate the work of building data pipelines. Also new in BigQuery is vector search using the same ScaNN algorithm used in Google search and YouTube, currently available in preview. The emphasis on multimodal data processing and real-time data ingestion indicates Google’s commitment to enabling businesses to extract insights from diverse data sources and respond to changing conditions in real time.
What to Watch:
- Competition: The AI landscape is fiercely competitive. Microsoft and OpenAI’s partnership presents a formidable challenge, while AWS remains a dominant player in cloud infrastructure. Google’s ability to differentiate itself and win over enterprise customers will be crucial.
- Customer Adoption: While Google showcased some compelling use cases, widespread adoption of Gemini and Vertex AI remains to be seen. Google needs to provide strong incentives and support to encourage businesses to embrace its AI platform and tools.
- Ethical Considerations: As AI becomes more pervasive, concerns about bias, fairness, and responsible AI development will intensify. Google’s commitment to ethical AI principles and its ability to address these concerns will be closely watched, as will those of its competitors.
- Talent Acquisition and Development: The success of Google’s AI strategy hinges on its ability to attract and retain top AI talent. Competition for skilled professionals is intense, and Google needs to maintain its position as an employer of choice in the AI field.
See the complete Google Cloud Summit London event blog post for more information.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
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Author Information
Nick Patience is VP and Practice Lead for AI Platforms at The Futurum Group. Nick is a thought leader on AI development, deployment, and adoption - an area he has researched for 25 years. Before Futurum, Nick was a Managing Analyst with S&P Global Market Intelligence, responsible for 451 Research’s coverage of Data, AI, Analytics, Information Security, and Risk. Nick became part of S&P Global through its 2019 acquisition of 451 Research, a pioneering analyst firm that Nick co-founded in 1999. He is a sought-after speaker and advisor, known for his expertise in the drivers of AI adoption, industry use cases, and the infrastructure behind its development and deployment. Nick also spent three years as a product marketing lead at Recommind (now part of OpenText), a machine learning-driven eDiscovery software company. Nick is based in London.
