9次执行采访揭示了Oracle AI World的企业AI的前途。
将企业AI应用推向生产，需要的不仅仅是能力日益增强的模型。 企业需要安全获取商业数据、可靠的基础设施和对自主agents的更大控制，因为各组织希望将AI实验转化为可衡量的商业成果。
“大赦国际进展迅速。 “CUBE研究首席分析师称 Dave Vellante(图画，左侧), “Oracle AI World最大的对话之一是如何将企业AI从实验转移到生产，以及如何确保企业AI不受全新的AI驱动的威胁。”
Oracle AI World 2026于10月25日至28日在拉斯维加斯举行，他们的对话突出了Oracle对信任的代理AI，数据库现代化，网络安全和应用开发的方法，以及旨在帮助企业大规模部署AI的技术创新。
包括将OpenAI Codex与Oracle AI数据库合并的黑客交易。 CUBE将在10月28日扩大这些对话，现场报道Oracle AI World，重点介绍对企业AI战略的进一步深入了解以及决定采用这些战略的技术。 (* 下文披露。 )
以下是Oracle高管们在Oracle AI World 2026前的9个关键见解：
1. 企业AI信托要求整个技术库的安全。
根据Oracle数据库技术执行副总裁Juan Loaiza的说法，企业采用代理化AI取决于各组织能否信任系统，以作出涉及关键业务流程的决定和采取行动。 在与CUBE谈话时，Loaiza解释了为什么在AI应用需要一致的保护和可靠性时，在现有架构中添加安全护栏是不够的。 他即将到来的Oracle AI World Conference将探讨将AI，数据管理和应用开发整合到一个统一的架构中，如何在整个技术堆中提供安全和控制。 讨论确定了Oracle数据深潜编程的中心主题：必须把信任纳入基本架构，而不是下放给个别AI模型。
请不要错过CUBE的完整采访。
2. Oracle AI数据库以新的能力和更强的安全性推进企业AI.
根据Hasan Rizvi，产品和研究的EVP，数据库工程，在Oracle，要使AI对企业有用，就需要将智能应用与给出其反应意义的企业数据联系起来。 他即将到来的会话将涵盖Oracle AI数据库的推进，旨在简化复杂的数据架构，支持灵活的部署选择和保护敏感信息。 Rizvi还预览了与结构化和非结构化数据合作的能力，构建AI agents而不将信息转移到独立的平台，并支持AI生成的应用程序开发。 安全仍然是一个主要优先事项，Oracle侧重于从源头保护数据，迅速应对威胁，在发生事件时保持复原力。
在CUBE的完整采访中找到更多内容。
3. 数据库级别控制为自主AI agents建立信任。
根据任务关键数据和人工智能引擎高级副总裁Tirthankar Lahiri、Oracle数据库以及产品管理、任务关键数据和AI引擎、Oracle数据库的VPSara Narayan的说法，获取敏感企业信息的AI agents必须在可执行的安全和商业规则范围内运作，即使应用程序或agents受到破坏。 他们即将举行的会议将显示Oracle在数据、获取、知识和执行四个领域的信任办法。 高管们预览了能力，包括将自然语言请求连接到已验证的响应的Trusted Answer Search，以及JSON Dality Views，通过控制API帮助限制agent启动的数据库更改。 他们的讨论还有推出 Oracle数据库的深层信任架构，强调无论请求来自用户，应用程序还是自主agents，都适用的数据库强化保护。
别错过关于CUBE的全部讨论。
4. AI发动的网络攻击增加了数据库安全的紧迫性。
AI协助的网络攻击正在改变企业必须如何快速识别弱点并部署安全更新，据软件工程的SVP，数据库安全，位于Oracle. Samar解释说，攻击者可以越来越多地用反向引擎软件补丁来识别弱点，使得传统的维护时间表不足以适应当今的威胁环境。 他的Oracle AI World Conference将专注于提高整个数据库车队的风险能见度，并加快部署安全补丁，然后才能利用脆弱性。 Oracle的战略重点是从源头获取数据，以机器速度作出反应，并加强抵御日益复杂的攻击的能力。
更多关于CUBE的采访
5. 自主数据库基础设施为企业AI提供了规模的基础。
根据Oracle产品和研究的EVP，数据仓库和自主数据库，有希望的AI原型与生产准备的应用程序之间的差距往往下降到基础数据基础设施的强度。 Özbütün强调，现代AI的工作量对自动化安全、关键任务可用性和弹性提出了更大的要求，同时增加了控制业务费用的压力。 他即将到来的会议将展示Oracle自主AI数据库如何通过自动化管理，安全补丁和可缩放的基础设施支持企业AI工作量。 讨论还涉及数据库自动化的经济学，以及为什么各组织需要可靠的数据基础来实现人工智能投资的有意义的收益。
在CUBE的完整采访中找到更多内容。
6. 自主AI Lakehouse 带来分析与AI驱动的决策共同进行。
根据Nipun Agarwal，软件工程的SVP,Oracle Database, at Oracle. Agarwal预览了新的Oracle自主AI Lakehouse能力，目的是帮助各组织分析分布式数据环境中的信息，而不需要广泛的数据移动。 他的活动会话将探讨如何自动丰富业务环境，更有选择地检索相关信息和扩大Apache Iceberg支持可以改善AI的结果，同时降低推论成本。 受访者还将更仔细地审视集中式安全，数据线条和一个AI辅助工作空间，旨在简化分析与AI开发。
请不要错过CUBE的完整采访。
7. Exadata创新提高了AI的性能和数据库的复原力。
根据Jia Shi(图片，右)，在Oracle数据系统软件工程组VP，管理AI工作量与任务关键交易需要能够提供高性能而又不损害可用性的基础设施。 Shi强调Exadata Live Migration，它使使用远程直接内存访问的活跃数据库虚拟机能够在服务器之间移动，同时保留其连接并避免应用程序故障时间。 她即将到来的会话还将涵盖Exadata如何加速AI向量搜索，并支持在Oracle云基础设施，其他主要云平台和景点上的环境进行部署。 另一个重点是利用代理AI通过自动化工具诊断和解决数据库输入/输出性能问题。
在CUBE的完整采访中获得细节。
8. APEXlang 带来 AI生成的应用程序更接近企业生产。
AI编码agents使软件开发更加方便，但企业仍然需要能够理解，维护和安全的应用程序，据Mike Hichwa所说，Oracle软件工程的SVP. Hichwa预览了APEXlang，是一种正式的应用程序定义语言，它允许AI编码agents使用结构化，可编译的格式生成低码应用程序。 该方法使OpenAI Codex和Claude等工具在依靠Oracle APEX引擎处理基础执行要求的同时生成应用程序配置。 他即将举行的会议将讨论这种抽象如何减少技术债务，维护人类对AI生成的应用的理解，并支持企业对治理和可扩展性的要求。
在CUBE的完整采访中找到更多内容。
9. Oracle AI World通过实践会议将代理AI发展付诸实践。
Oracle 大赦国际据Oracle数据库产品营销的SVPArpan Shah称，世界与会者将有机会超越对AI战略的讨论，直接与生产准备应用技术合作。 Shah概述了Data Deep Dive方案，该方案将执行产品聚光灯会议与技术演示、操作实验室和关于数据库安全和agent开发的讨论结合起来。 一个主要的吸引力是十月28日的黑客座，集合了OpenAI Codex和Oracle AI数据库，参与者可以在Oracle和OpenAI专家的指导下构建应用程序。 该活动是为专业开发人员和其他技术好奇的参与者设计的，为利用企业数据库基础设施开发AI应用程序提供了实用的介绍。
请不要错过CUBE的完整采访。
对话为CUBE于10月28日在拉斯维加斯现场报道Oracle AI World 2026搭建了舞台。 通过与Oracle执行官和行业专家的访谈，CUBE将对企业AI，数据库创新和网络安全的最新发展提供更多的视角，重点是各组织如何运用这些技术。 报道还将重点介绍活动的主要公告和实际外卖。
(*披露：CUBE是Oracle AI World的付费媒体合作伙伴。 无论是CUBE事件报道的发起人Oracle还是其他发起人，都没有对CUBE或SiliconANGLE上的内容进行编辑控制。 ).
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9 executive interviews reveal what’s ahead for enterprise AI at Oracle AI World
Moving enterprise AI applications into production requires more than increasingly capable models. Enterprises need secure access to business data, reliable infrastructure and greater control over autonomous agents as organizations look to turn AI experimentation into measurable business results.
“AI is moving fast. Threats are moving just as fast, and the race is on to build enterprise AI that’s not just intelligent, but trusted, secure and, of course, ready for production,” said Dave Vellante (pictured, left), chief analyst at theCUBE Research. “One of the biggest conversations at Oracle AI World will be about what it takes to move enterprise AI from experimentation to production and how to secure it against an entirely new generation of AI-driven threats.”
Ahead of Oracle AI World 2026, taking place Oct. 25–28 in Las Vegas, Oracle Corp. executives joined Vellante for nine pre-event interviews previewing the conference’s “Data Deep Dive” programming. Their conversations highlight Oracle’s approach to trusted agentic AI, database modernization, cybersecurity and application development, along with the technical innovations intended to help enterprises deploy AI at scale.
The interviews also preview Oracle’s upcoming product spotlight sessions, technical demonstrations and hands-on activities, including a hackathon combining OpenAI Codex with Oracle AI Database. TheCUBE will extend these conversations with on-site coverage of Oracle AI World on Oct. 28, featuring additional insights into enterprise AI strategies and the technologies shaping their adoption. (* Disclosure below.)
Here are nine key insights from Oracle executives ahead of Oracle AI World 2026:
1. Enterprise AI trust requires security across the entire technology stack.
Enterprise adoption of agentic AI depends on whether organizations can trust systems to make decisions and take actions involving critical business processes, according to Juan Loaiza, executive vice president of Oracle Database Technologies. Speaking with theCUBE, Loaiza explained why adding security guardrails to existing architectures is insufficient when AI applications require consistent protection and reliability. His upcoming Oracle AI World session will address how integrating AI, data management and application development into a unified architecture can provide security and control throughout the technology stack. The discussion establishes a central theme of Oracle’s Data Deep Dive programming: Trust must be engineered into the underlying architecture rather than delegated to individual AI models.
Don’t miss the full interview on theCUBE.
2. Oracle AI Database advances enterprise AI with new capabilities and stronger security.
Making AI useful to businesses requires connecting intelligent applications with the enterprise data that gives their responses meaning, according to Hasan Rizvi, EVP of product and research, database engineering, at Oracle. His upcoming session will cover Oracle AI Database advancements designed to simplify complex data architectures, support flexible deployment choices and protect sensitive information. Rizvi also previewed capabilities for working with structured and unstructured data, building AI agents without transferring information to separate platforms and supporting AI-generated application development. Security remains a major priority, with Oracle focusing on protecting data at its source, responding rapidly to threats and maintaining resilience when incidents occur.
Find out more in the full interview on theCUBE.
3. Database-level controls establish trust for autonomous AI agents.
AI agents accessing sensitive enterprise information must operate within enforceable security and business rules, even when applications or agents are compromised, according to Tirthankar Lahiri, senior vice president of mission-critical data and artificial intelligence engines, Oracle Database, and Sara Narayan, VP of product management, mission-critical data and AI engines, Oracle Database. Their upcoming session will demonstrate Oracle’s approach to trust across four areas: data, access, knowledge and execution. The executives previewed capabilities including Trusted Answer Search, which connects natural-language requests to validated responses, and JSON Duality Views, which help restrict agent-initiated database changes through controlled APIs. Their discussion also introduces Oracle Database’s Deep Trust Architecture, emphasizing database-enforced protections that apply regardless of whether requests originate with users, applications or autonomous agents.
Don’t miss the full discussion on theCUBE.
4. AI-powered cyberattacks increase the urgency of database security.
AI-assisted cyberattacks are changing how quickly enterprises must identify vulnerabilities and deploy security updates, according to Vipin Samar, SVP of software engineering, database security, at Oracle. Samar explained that attackers can increasingly reverse-engineer software patches to identify vulnerabilities, making traditional maintenance schedules inadequate for today’s threat environment. His Oracle AI World session will focus on improving risk visibility across entire database fleets and accelerating the deployment of security patches before vulnerabilities can be exploited. Oracle’s strategy centers on securing data at its source, responding at machine speed and strengthening resilience against increasingly sophisticated attacks.
Hear more in the full interview on theCUBE.
5. Autonomous database infrastructure provides a foundation for enterprise AI at scale.
The gap between promising AI prototypes and production-ready applications often comes down to the strength of the underlying data infrastructure, according to Çetin Özbütün, EVP of product and research, data warehouse and autonomous database, at Oracle. Özbütün emphasized that modern AI workloads place greater demands on automated security, mission-critical availability and elastic scalability while increasing pressure to control operational costs. His upcoming session will demonstrate how Oracle Autonomous AI Database supports enterprise AI workloads through automated administration, security patching and scalable infrastructure. The discussion also addresses the economics of database automation and why organizations need a reliable data foundation to realize meaningful returns on AI investments.
Find out more in the full interview on theCUBE.
6. Autonomous AI Lakehouse brings analytics and AI-driven decision-making together.
Enterprise lakehouses are expanding beyond traditional analytics to become platforms for AI-driven decisions, according to Nipun Agarwal, SVP of software engineering, Oracle Database, at Oracle. Agarwal previewed new Oracle Autonomous AI Lakehouse capabilities intended to help organizations analyze information across distributed data environments without requiring extensive data movement. His event session will address how automatically enriched business context, more selective retrieval of relevant information and expanded Apache Iceberg support can improve AI results while reducing inference costs. Attendees will also get a closer look at centralized security, data lineage and an AI-assisted workspace designed to simplify analytics and AI development.
Don’t miss the full interview on theCUBE.
7. Exadata innovations improve AI performance and database resilience.
Running AI workloads alongside mission-critical transactions requires infrastructure capable of delivering high performance without compromising availability, according to Jia Shi (pictured, right), group VP of data systems software engineering at Oracle. Shi highlighted Exadata Live Migration, which enables active database virtual machines using Remote Direct Memory Access to move between servers while preserving their connections and avoiding application downtime. Her upcoming session will also cover how Exadata accelerates AI vector searches and supports deployment across Oracle Cloud Infrastructure, other major cloud platforms and on-premises environments. Another focus is the use of agentic AI to diagnose and address database input/output performance problems through automated tools.
Get the details in the full interview on theCUBE.
8. APEXlang brings AI-generated applications closer to enterprise production.
AI coding agents are making software development more accessible, but enterprises still need applications they can understand, maintain and secure, according to Mike Hichwa, SVP of software engineering at Oracle. Hichwa previewed APEXlang, a formal application-definition language that allows AI coding agents to generate low-code applications using a structured, compilable format. The approach enables tools such as OpenAI Codex and Claude to generate application configurations while relying on the Oracle APEX engine to handle underlying execution requirements. His upcoming session will address how this abstraction can reduce technical debt, preserve human understanding of AI-generated applications and support enterprise requirements for governance and scalability.
Find out more in the full interview on theCUBE.
9. Oracle AI World puts agentic AI development into practice through hands-on sessions.
Oracle AI World attendees will have opportunities to move beyond discussions of AI strategy and work directly with technologies for building production-ready applications, according to Arpan Shah, SVP of database product marketing at Oracle. Shah outlined the Data Deep Dive program, which combines executive product spotlight sessions with technical demonstrations, hands-on labs and discussions about database security and agent development. A major attraction is the Oct. 28 hackathon bringing together OpenAI Codex and Oracle AI Database, where participants can build applications with guidance from Oracle and OpenAI experts. The event is designed for professional developers and other technically curious attendees, offering a practical introduction to developing AI applications using enterprise database infrastructure.
Don’t miss the full interview on theCUBE.
The conversations set the stage for theCUBE’s on-site coverage of Oracle AI World 2026 on Oct. 28 in Las Vegas. Through interviews with Oracle executives and industry experts, theCUBE will provide additional perspectives on the latest developments in enterprise AI, database innovation and cybersecurity, with a focus on how organizations are putting these technologies to work. The coverage will also highlight key announcements and practical takeaways from the event.
(* Disclosure: TheCUBE is a paid media partner for Oracle AI World. Neither Oracle, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)
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