One of these things (is not like the others)

It's been forever in the tech development timescale, but Software as a Service (SaaS) was only popularized in the early 2000s. Salesforce was launched in 1999, followed by Google Apps and Amazon Web Services (AWS) in 2006. Going to the cloud allows businesses to access Software without needing local installations. More importantly, the idea of daily releases that can address critical bugs and provide much-needed features revolutionized the enterprise software distribution model.

Now, let's fast forward to today. According to an article published by Deloitte in March of this year, tech investors in 2024 prioritize AI, cloud computing, cybersecurity, advanced connectivity, and infrastructure modernization. AI-native applications are expected to be adopted across various operational workflows in financial institutions.

As organizations increasingly rely on SaaS solutions, maintaining strong data governance and understanding data lineage become critical. Data governance establishes rules for managing data, while data lineage tracks its journey. With external AI services, these are crucial for maintaining control, ensuring compliance, and understanding data flow and storage across external systems.

Data Governance and Data Lineage Concerns

Services like ChatGPT and other third-party AI solutions became popular due to their ease of use and powerful capabilities. However, using these services often involves sending your data to external servers where the AI processes it.

Unlike databases with discrete entries, AI systems encode information across numerous interconnected parameters. This distributed representation makes it nearly impossible to isolate and "delete" specific pieces of knowledge. Removing information could unintentionally alter unrelated knowledge, as the AI's outputs emerge from complex interactions within its neural network, not from easily separable data points.

As a result, sharing your data with third-party AI services introduces several risks:

• Data Privacy: Sensitive business data could be exposed, risking leaks or breaches that could compromise competitive intelligence.
• Compliance Risks: Different regions have varying regulations regarding data protection (e.g., GDPR in Europe). Ensuring compliance can be challenging when external services handle data.
• Loss of Control: Once data is sent to an external service, control over its use and management is significantly reduced. This could lead to unauthorized usage or unintended data sharing.
• Intellectual Property Risks: Proprietary data and insights, which form the core of your competitive advantage, could be at risk if mishandled by third-party services.

Why On-Premise AI Makes Sense

Given these concerns, building AI solutions on-premise can offer significant advantages, particularly for enterprises keen on safeguarding their data and maintaining control over their processes:

• Enhanced Security: On-premise AI solutions allow businesses to implement stringent security measures tailored to their specific needs, reducing the risk of data breaches and unauthorized access.
• Compliance Assurance: Managing data on-premise simplifies adherence to regional data protection regulations, as businesses retain complete control over how data is stored, processed, and used.
• Full Control: With on-premise AI, businesses oversee entirely their data, ensuring it is used exclusively for intended purposes. This control extends to data transformations and lineage tracking, maintaining data integrity and quality.
• Protection of Intellectual Property: Keeping AI processes in-house ensures that proprietary data and insights remain confidential, preserving the enterprise's competitive edge.

On June 10th of this year, Apple debuted Apple Intelligence. Apple Intelligence addresses data governance and privacy concerns through a multi-faceted approach. At its core, there is an emphasis on on-device processing, leveraging Apple chips to handle AI tasks locally whenever possible. Apple utilizes Private Cloud Compute (PCC) for more complex operations without persistent data storage, deleting user information after request fulfillment.

Interestingly, Apple also allows independent experts to inspect PCC software and offers bounties for identifying security issues. The company claims it cannot access user data processed by PCC due to the absence of remote access tools.

Apple's unique advantage is having the sole ownership in its distribution of hardware. By putting AI in your device, Apple effectively decentralized the functionality, placing the capability "on-premise" and in your hands.

This is not to say that third-party AI services lack merit. In practice, we used external AI to build a proof of concept and expedite our research by magnitudes of efficiency gain. However, on-premise AI solutions provide a robust alternative for enterprises prioritizing security and wishing to maintain strict control over their data and intellectual property. In the age of cloud software, AI is one thing that is not like the others.