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Artificial Intelligence (AI) has evolved into a crucial asset for organizations, with three-quarters now leveraging it to enhance innovation, efficiency, and growth. Analysts predict that by 2026, 80% of enterprises will utilize AI-enabled applications, significantly transforming various industries. The marketing and advertising sectors are at the forefront, using AI to secure a competitive edge. However, as AI becomes more prevalent, concerns regarding data confidentiality arise, particularly regarding the use of sensitive business and personal information in training AI systems. Ensuring confidentiality is vital not only for security but also for building trust and fairness in AI-driven decisions. The challenges of AI, often referred to as the "black box problem," highlight the need for transparency in AI systems. Users frequently struggle to understand how AI makes decisions, raising concerns about accountability and ethical standards. Privacy issues are compounded by the handling of personal data, and data sovereignty becomes a critical consideration, especially with cross-border data flows. As AI increasingly influences our lives, companies face the dual challenge of ensuring security while also finding ways to monetize AI applications without compromising user privacy. Confidential AI emerges as a solution to these challenges, emphasizing secure data handling and decision-making processes. At iExec, the focus on confidential computing ensures that sensitive data remains protected throughout the AI workflow. By utilizing blockchain technology, iExec enhances the verifiability and trustworthiness of AI processes, allowing stakeholders to track each step and verify results. This integration of Confidential AI with blockchain not only safeguards data but also provides a framework for monetizing AI applications while maintaining user privacy. As advancements continue in this field, the future of Confidential AI looks promising, with ongoing developments aimed at enhancing security, transparency, and ethical considerations in AI applications.

As Decentralized Confidential Computing (DeCC) gains traction in 2024, iExec has been a pioneer in this domain, merging Confidential Computing with blockchain since 2018. Collaborating with Intel, iExec launched the first Trusted Compute Specification for the Ethereum Enterprise Alliance, laying the groundwork for secure data processing in Web3. By 2019, iExec became the first Web3 company to join the Confidential Computing Consortium, solidifying its role in decentralized data protection. These early innovations have paved the way for DeCC, which redefines data privacy and security in the Web3 landscape. Confidential Computing is a critical component of DeCC, addressing the need to protect data not only at rest and in transit but also during processing. This technology isolates sensitive data or code using hardware enclaves, creating a trusted execution environment that processes encrypted data in memory. By employing hardware-based attestation reports, Confidential Computing ensures that only authorized programs can access the data within these enclaves. This approach safeguards various types of data, from personal information to complex algorithms, enhancing security in an increasingly fragmented data landscape. The DeCC movement promotes a broader understanding of privacy in Web3, emphasizing user control and decentralized security. With the formation of the DeCC Alliance, which includes leading projects in Confidential Computing, the initiative aims to educate the public on the capabilities of DeCC and its necessity for secure data usage. iExec's mission is to empower users by tokenizing their data and establishing governance rules, ensuring that data remains secure and private. As DeCC continues to evolve, it is set to transform the Web3 ecosystem, making privacy and data ownership a fundamental right for users in the digital age.