Oracle Cloud Success StrategiesThe Big Themes:Customer Success Services creation: Oracle established Customer Success Services to provide comprehensive support for customers using its cloud tools. This integration of various service organizations — such as education, consulting, and customer success management — aims to create a unified approach, ensuring customers receive consistent and effective assistance while adopting the cloud.Introduction of Navigator tool: The Oracle Cloud Navigator is designed to assist customers in navigating their cloud transformation more efficiently. This digital platform streamlines the onboarding process, providing best practices and facilitating quick configurations, ultimately helping clients achieve value faster and more effectively.Concierge services enhancement: Oracle is introducing new concierge services to address the complexities of multi-cloud environments. These services aim to provide tailored support for troubleshooting and integration challenges, reinforcing Oracle's commitment to customer success and ensuring that users can efficiently resolve issues, regardless of where they originate.The Big Quote: “What's unique about Oracle is our enterprise-grade embedded AI. In the application space, we say, let's bring AI to your end users . . . but it's not easy for customers. 'Okay, which one should I use? How do I use them?' So we put a whole program together, which explains the new innovations."

Episode 44 | Workday Rising AI InsightsThe Big Themes:The evolution of AI tools: AI tools have moved from basic task automation to more sophisticated systems like copilots and autonomous agents. Bonnie introduces the concept of "orchestrators," which monitor and optimize workflows based on real-time feedback. This evolution signifies a shift toward more dynamic and intelligent systems that can adapt to changing business environments and user needs.Strategic partnership: Bonnie talks about the significance of partnerships, particularly between Workday and Salesforce, in creating a more powerful toolset for users. By leveraging both organizations' strengths, customers can access integrated solutions that enhance operational efficiency. This partnership exemplifies how collaboration in the tech industry can lead to greater innovation and more comprehensive service offerings.Illuminate, the AI branding strategy: Workday's branding of its AI initiatives as "Illuminate" represents a strategic approach to making AI accessible and user-friendly. Bonnie explains that this branding aims to demystify AI for end-users, transforming it from a complex developer tool into a consumer-grade experience. This initiative reflects a broader trend of making advanced technologies more approachable for everyday users.The Big Quote: “The power of the partnership between [Workday and Salesforce], leveraging both of their agencies together, is a real win for customers."

AI Transformation at NetSuiteThe Big Themes:AI integration and customization: NetSuite focused on integrating AI into its platform. Evan points out the importance of large language models and traditional AI working together to identify data patterns and enhance productivity. Features like Text Enhance and the new “Ask Oracle” tool enable businesses to tailor AI applications to their specific needs without needing extensive IT resources.AI adoption across industries: NetSuite is seeing a surge in AI adoption, especially among its customers in software and internet industries. However, the company’s strategy is to make AI valuable and user-friendly for all sectors. By integrating AI tools directly into everyday workflows, like using the search box to ask complex business questions, NetSuite aims to make non-technical users comfortable with these advanced tools.Meeting business needs with tailored offerings: NetSuite is committed to providing businesses with tools that are both powerful and easy to customize, catering especially to small and midsize businesses that may lack extensive IT resources. The company's philosophy has always been to offer robust out-of-the-box capabilities while also allowing customers to tailor these features to their specific needs. Recent AI-driven enhancements demonstrate this commitment.The Big Quote: “You should be able to ask the question in plain language and get an answer back in plain language, and that's the ultimate business user experience.”

Efficient AI Model EconomicsThe Big Themes:GenAI and its practical application: GenAI has emerged as a major focus in enterprise settings, with organizations exploring its potential to enhance core business processes. While many have successfully integrated generative AI into their workflows, others face challenges moving beyond continuous prototyping to actual production deployment. Key to overcoming these hurdles is understanding the limitations and capabilities of AI models.Economic advantages of smaller AI models: Smaller AI models, such as the 35 billion parameter models from Cohere, represent a significant economic shift in the AI landscape. These models, which can be run on a single GPU, offer a more cost-effective alternative to larger models, reducing the financial burden associated with AI deployment. These mid-sized models are not only cheaper but also capable of covering the majority of use cases effectively.AI integration into Oracle's software-as-a-service (SaaS) portfolio: Oracle has integrated generative AI into its software-as-a-service (SaaS) portfolio, enhancing various business functions without additional charges. This integration includes features like automated job postings and Salesforce optimization. Greg notes that this approach adds significant value to Oracle's offerings.The Big Quote: “People try to chase the latest and be on the frontier but never really commit to making something work for production."

Oracle's Industry Cloud InnovationsThe Big Themes:AI integration in Industry Applications: AI, especially GenAI is playing a significant role in transforming industry applications. Mike explains how AI technologies are enhancing customer experiences, such as in healthcare, where they automate routine tasks and improve patient interactions. This integration is expected to continue growing.Shift towards Industry Suites: There is a clear shift toward adopting Industry Suites rather than piecemeal cloud solutions. Mike explains that Industry Suites, which integrate various technologies and services, are becoming more popular as they offer a cohesive solution and reduce the need for extensive regression testing and complex integrations. They help organizations maintain cloud benefits, such as innovation and security, without the drawbacks of fragmented systems.Business transformation through technology: Technology has a huge impact on broader business transformation. Mike notes that what starts as an IT project can evolve into a comprehensive business transformation initiative. For instance, AI-driven offerings in healthcare are not only improving operational efficiency but also transforming business models and patient care.The Big Quote: “Everybody's here to serve their customers. Patients are customers, people who check into hotels and customers, people who eat at restaurants or customers. Every CEO that I engage with says, 'This transformation helps me serve my customers better, and that's why I want to engage in it.'"

Google Cloud AI Security InsightsThe Big Themes:Google’s ecosystem-driven security approach: Google Cloud's partner ecosystem, consisting of entities such as managed security service providers (MSSPs) and global systems integrators, helps deliver top-notch security services. While Google maintains a small in-house service capability, partners are key to scaling and extending innovations to customers. Google provides AI tools to partners, who enhance their product offerings to better serve end customers. This model ensures that the latest security advancements, such as AI integration, are accessible.Transitioning from assisted to autonomous security: Google Cloud envisions a future where AI will evolve from assistive to fully autonomous security workflows. Currently, AI plays an assistive role by providing actionable insights to security teams, helping them prioritize threats and respond more effectively. However, the goal is to transition these capabilities into semi-autonomous workflows, with the potential for fully autonomous security systems in the future.Enhancing CISOs’ efficiency with AI: One of the key problems CISOs face today is the overwhelming number of security alerts, which makes it challenging to identify and act on the most critical threats. Google Cloud addresses this issue by leveraging AI to sift through thousands of alerts, helping CISOs quickly identify the most significant risks. AI can provide real-time insights, suggesting actions to mitigate potential threats and reduce the noise from less pressing alerts.The Big Quote: “AI is only as good as the data that the model is trained on and, in the world of security, we happen to have probably the world's most high quality and quantitative data set in threat intelligence."

Episode 43 | Oracle's AI and Security InnovationsThe Big Themes:Completeness of suite: Oracle has an integrated approach across industries, offering a full suite of applications and services. Its multi-cloud offerings and the inclusion of infrastructure and vertical-specific applications set it apart. This completeness was emphasized with customer stories from DHL, MGM, and others.Embedded AI: Oracle’s AI tools are built directly into its applications, providing contextual insights based on user roles, history, and security levels. This integration allows for seamless decision-making across different business functions like HR, sales, and supply chain management, offering customers greater functionality without adding to their tech stack.Security: Larry Ellison discussed Oracle's commitment to eliminating passwords and enhancing security through biometrics. Oracle’s security offerings operate at the data, application, user ID, and network levels. The approach involves building strong networks first and then deploying security "agents" to detect and neutralize threats.The Big Quote: “ . . . Embedded AI means that clients just have to turn it on. It's not like they have to add something new to the tech stack. It is there as an option, whether they turn it on or off."

Scaling Generative AIThe Big Themes:Prioritizing cost and impact: Businesses are focused on the dual priorities of cost efficiency and impactful results when implementing generative AI. With numerous potential applications for generative AI, organizations need to evaluate which projects will deliver the highest value. This approach involves collaborating with partners to identify the opportunities that offer the most substantial benefits.Open ecosystem advantage: Google Cloud’s emphasis on openness and flexibility is a key differentiator in the AI landscape. Its commitment to open systems and platforms allows for various models and technologies, including first-party and open-source offerings. This open ecosystem approach enables businesses to leverage various AI models and infrastructure options, enhancing scalability and adaptability.End-to-end offerings: Google Cloud offers a comprehensive AI stack that supports a wide range of applications, from foundational models to advanced infrastructure. This end-to-end tool facilitates the development and scaling of sophisticated AI applications. The integration of various layers, including model capabilities, hardware options, and platform services, enables partners to deliver efficient and effective AI offerings.The Big Quote: “Having great models is one thing, but having differentiated infrastructure and a platform — all those three things come together, and I think we are unique in that sense."

 Creating Value with TeradataThe Big Themes:Open Table Formats: Datasets are one of the most common ways that organizations use open table formats, as it enables them to combine several types of data and access that data. Open table formats are improving performance which will help drive a more flexible, low-cost storage option for enterprises. Having this level of customer choice will drive greater adoption and outcomes for customers deploying open table formats over time.Trusted AI: Trusted systems require access to data, but it must be properly managed data. Open table formats can help with trusted data progression, such as reducing data duplication by consolidation and providing a single place of oversight. As open table formats match agility and flexibility with the appropriate levels of governance, it can deliver trusted outcomes that overflow into providing trusted AI.Driving Customer Value and Success: Providing customers with opportunities for success is the ultimate driver. For example, Teradata supported a call center that wanted to improve customer satisfaction and outcomes based on the call center data. Teradata provided the organization with text analytics, large language models, and more being driven through a Teradata analytic model engine that provides real-time advice to agents.The Big Quote: “We’ve always said, ‘Whoever has access to the most data can win in the analytics space.’ So, open table formats are a key component of really helping companies create an environment of trust around the data because without trusted data, you can’t have trusted AI.”

Google Cloud Data InnovationsThe Big Themes:Integration of unstructured data with AI: Google Cloud is shifting how enterprises leverage their data by integrating unstructured data (which makes up 85-90% of all data) with structured data through its BigQuery multimodal data foundation. This integration allows for a more comprehensive data landscape where AI models can seamlessly access and analyze both types of data. This approach addresses the limitations of traditional data systems and unlocks new potential for AI-driven analytics.The role of partners in maximizing AI and data value: Google Cloud’s service partners implement solutions and bring industry best practices to customer environments, while independent software vendors (ISVs) build applications that leverage Google Cloud’s data and AI tools. Programs like the Google Cloud Ready (GCR) initiative streamline integrations.Integration challenge: The challenge for organizations lies in connecting disparate data sources, such as operational data from systems like SAP and CRM data from Salesforce, with analytics tools to enable real-time decision-making. Google Cloud addresses this by developing connectors, such as Cortex.The Big Quote: “We are coming to the Third Age in data, which is going to divide data systems. It’s not just about having lots of one data type… it’s having the broadest possible set of data signals you can bring together. That idea of wide data systems means combining all of your data signals, structured and unstructured, into one unified system."