
Oracle Eloqua
Based exclusively on public evidence • 20 criteria (Privacy + AI)
Last review: 21 Feb 2026
AI Trust Summary
- •Regarding AI: it does not mention ethical principles or anti-bias measures, which may generate distrust about data usage.
- •Regarding Core Privacy: it does not provide a Data Processing Agreement, impacting customer security and trust in their data management.
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Attention Points in AI (3)
AI criteria that require attention. Buy the Premium Analysis to see all 3 criteria.
- •Oracle Eloqua
- •Does not provide a Data Processing Agreement, creating insecurity about data processing.
- •Omission of ethical AI principles can negatively impact customer trust.
- •It is advisable to require contractual clauses that address these critical points.
Ethical AI principles and anti-bias measures not documented
There is no mention of ethical AI principles, which can negatively impact customer trust in the use of lead data.
Automated AI decisions have no explanation available
The lack of explanation for automated decisions can generate distrust among customers about how their lead data is used.
AI decision contestation mechanism not available
The absence of a mechanism for contesting automated decisions can negatively impact customer trust in the use of lead data.
Source: vendor public documents
Compliances in AI (3)
AI criteria the company meets. Buy the Premium Analysis to see all 3 criteria.
- •Oracle Eloqua
- •Clearly identifies 'Oracle America Inc.' and 'Cerner Corporation' as data controllers, facilitating communication.
- •Connects data categories with specific purposes, ensuring clarity in information use.
- •These practices strengthen customer trust during due diligence.
AI features clearly identified with their purposes
The policy describes specific functionalities that use AI and their purposes, helping customers understand how their lead data is processed.
AI training opt-out control available
The policy mentions general privacy rights, allowing customers to limit the use of their lead data for AI training.
AI data retention policy clearly documented
The policy defines a specific and short retention period for chat transcripts, helping ensure compliance in lead data management.
Source: vendor public documents
Highlights in Privacy (3)
Most relevant criteria for this category. Buy the Premium Analysis to see all 3 criteria.
Data Processing Agreement (DPA) not available for customers
The absence of a Data Processing Agreement can generate insecurity about how lead data is processed, impacting customer trust.
Data controller and processor roles clearly defined
The policy clearly identifies Oracle as responsible, detailing scopes by business lines, essential for transparency in lead generation and nurturing.
Data controller identity and contact clearly disclosed
The policy provides clear information about who is responsible for data processing, facilitating communication and customer trust.
Source: vendor public documents
Critical Alerts
- •Princípios de IA ética e medidas anti-viés não documentados: A falta de compromisso ético pode gerar desconfiança entre os clientes..
- •Decisões automatizadas por IA não têm explicação disponível: A transparência nas decisões automatizadas é crucial para a confiança dos clientes.
Conformance analysis (20)
Data controller and processor roles clearly defined
Reference: ISO/IEC 27701 (7.3)
Identity and contact of the data controller clearly informed
Reference: ISO/IEC 27701 (7.3)
Recipients of personal data clearly identified in the policy
Reference: ISO/IEC 27701 (7.3)
Source: vendor public documents
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Enhancing Your Marketing Automation with Oracle Eloqua: A Privacy and AI Governance Perspective
Strength in Data Transparency
Oracle Eloqua excels in its commitment to transparency regarding data privacy practices. Users can easily identify the data controller, which is crucial for understanding who is responsible for managing their personal data. This clarity fosters trust and allows users to make informed decisions about their data. Additionally, Eloqua provides detailed categorizations of data processing purposes, ensuring that users know exactly how their data will be utilized. This level of transparency is vital for compliance with regulations such as GDPR and LGPD, which mandate clear communication about data usage.
Robust International Data Transfer Documentation
Another strength of Oracle Eloqua lies in its documentation concerning international data transfers. The platform clearly outlines how data may be transferred across borders, which is essential for users operating in multiple jurisdictions. This transparency helps users assess potential risks associated with data transfers and ensures compliance with international data protection laws. By understanding these processes, users can better manage their data privacy obligations and maintain compliance with regulations like ISO 27701.
Lack of Data Processing Agreement (DPA)
Despite its strengths, Oracle Eloqua has notable weaknesses that users should consider. One significant concern is the absence of a Data Processing Agreement (DPA) for clients. A DPA is a critical document that outlines the responsibilities of both the data controller and the processor, ensuring that data is handled securely and in compliance with applicable laws. Without a DPA, users may face increased risks regarding data security and accountability. To mitigate this risk, users should inquire about the possibility of establishing a DPA directly with Oracle or explore alternative platforms that provide this essential document.
Absence of Ethical AI Principles
Another area of concern is the lack of documented ethical AI principles and anti-bias measures within Oracle Eloqua's AI functionalities. The AITS AI Score of 46% indicates potential risks associated with automated decision-making processes. Users should be aware that without clear ethical guidelines, there may be a lack of accountability in how their data is processed and analyzed. To address this, users should actively seek information on how Oracle is addressing these ethical concerns and consider implementing additional oversight measures when utilizing AI features.
Understanding Automated Decision-Making
Furthermore, Oracle Eloqua does not provide explanations for decisions made by its AI systems. This lack of transparency can lead to uncertainty about how data-driven decisions are made, potentially impacting user trust. Users should take proactive steps to understand the implications of automated decision-making within the platform. This may involve requesting more information from Oracle regarding their AI processes or considering supplementary tools that offer greater transparency in AI-driven decisions.
Practical Steps for Enhanced Privacy Management
To enhance privacy management while using Oracle Eloqua, users should regularly review their account settings and data sharing preferences. Enabling privacy features, such as data anonymization and limiting data sharing with third parties, can significantly reduce risks. Additionally, users should stay informed about updates to Oracle's privacy policies and AI governance practices. Engaging with Oracle's support team to clarify any concerns regarding data processing and ethical AI practices can also empower users to make more informed choices about their data.
In conclusion, while Oracle Eloqua offers strong transparency in data management, users must remain vigilant about its weaknesses, particularly regarding data processing agreements and ethical AI practices. By taking proactive measures, users can effectively navigate these challenges and leverage the platform's strengths to enhance their marketing automation efforts.
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Source: vendor public documents
Analyzed Sources
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Scope & Limitations
TrustThis/AITS assessments are based exclusively on publicly available information, duly cited with date and URL, following the AITS methodology (privacy & AI transparency).
The content is indicative in nature, intended for screening and comparison, not replacing internal audits.
TrustThis/AITS does not perform invasive tests, does not access vendor technology environments and does not process customer personal data. Conclusions reflect only the vendor's public communication at the date of collection.
Source: vendor public documents





