AI Concerns: Addressing Privacy in the Age of Artificial Intelligence

AI is exploding onto the business scene, hailed as the future of innovation—but it’s not without its dark side. From 2017 to 2022, the number of businesses adopting AI has more than doubled. While these early AI adopters are reaping significant benefits, how data is handled can pose significant risks to companies. Without the right safeguards, businesses risk losing control of their most valuable asset: their data.

Companies must be able to benefit from AI adoption and control their data simultaneously. In this article, we will expand on why privacy matters, the effect of poor privacy management in AI, and the best options for an AI-driven, secure future. 

Why Privacy Matters in AI

AI is a transformative tool that elevates productivity and allows companies to compete at higher levels. The ethical concerns about safe data processing must be addressed to fully appreciate AI’s benefits.  

Data Sensitivity in Business

According to the Global State of Responsible AI Survey, 51% of organizations reported that data governance and privacy–related risks are pertinent to their AI adoption strategy. The webAI AI Trends Report found that data privacy and security were the first considerations in choosing both local and cloud-based AI
(38% and 37%, respectively) implementations. Businesses know that sensitive data (customer information, proprietary data, etc.) must be protected. 

However, the third quarter of 2024 witnessed data breaches that exposed more than 422 million records worldwide. After a breach, businesses face potential legal action, revenue loss, brand damage, and more. 

Regulations and Compliance

General Data Protection Regulation (GDPR), the Health Insurance Portability and Accountability Act of 1996 (HIPAA), and the California Consumer Privacy Act (CCPA) are just a few regulatory bodies that enforce strict data handling and privacy protocols. Businesses must partner with compliant AI technology that protects shareholders and users. 

Trust and Brand Reputation

Mishandling data can lead to breaches of trust, reputational damage, and severe financial penalties. After a privacy breach, the Federal Trade Commission (FTC) recommends: 

• Securing digital and physical breach areas
• Mobilizing a breach response team
• Assembling a team of investigatory experts
• Hiring a data forensics team
• Consulting with legal counsel
• Stopping additional data loss
• Removing improperly posted information from the web (when possible)
• Taking extensive steps to fix vulnerabilities
• Following all proper legal requirements (including informing the public)
  

‍

This is the bare minimum when facing a privacy breach. Best practices involve working with a PR team, allocating extensive resources to stopping a breach, and possibly partnering with a different AI system. 

Key Privacy Concerns Businesses Face with AI

AI tools can and do put businesses at risk for privacy and security breaches. 

Data Collection and Storage

There are legitimate concerns over how AI systems gather and store sensitive data, sometimes without clear boundaries. There's a significant difference between an AI company claiming they won't gather company data and literally not being able to—that's the difference data collection-wise between big cloud providers and local AI providers like webAI. 

‍

Data Security and Breaches

With humans at the helm, businesses face risks like corporate espionage and accidental data leaks. When cloud-based AI systems are in place and data is stored on third-party servers, businesses risk data breaches. The webAI AI Trends Report found that 44% of reporting companies experienced data breaches and/or security incidents related to AI from August 2023 to August 2024. 

Breach and security concerns also increase depending on the size of the company. Large organizations manage significant amounts of data and report correspondingly large concerns. 

Data Sharing with Third Parties

When AI models rely on external data centers, businesses may have limited control over how their data is accessed or shared. This reality is one of the primary methods by which threat actors access and abuse business data. The AI Trends Report found that local AI users are more likely to be more concerned about privacy
and security (74%) than those leveraging
cloud solutions (58%). This suggests that companies using local AI understand the inherent risks of the cloud and are utilizing a more secure environment.

Model Transparency and Bias

The Foundation Model Transparency Index reveals a significant lack of transparency among AI developers, particularly in disclosing training data and methodologies. This opacity challenges leaders' understanding of AI systems' robustness and safety. Businesses must work with AI companies that are fully transparent regarding how data is processed and potential bias issues that may arise.

Private AI: What It Means for Businesses

As data breaches continue to highlight the vulnerabilities of cloud-based systems, businesses are increasingly turning to local AI as a secure and efficient alternative. Keeping AI deployments on your company’s own devices reduces exposure to external threats by ensuring data stays local, where it’s better protected.

Enhanced Data Privacy and Security
Local AI minimizes the need for data transfers to remote servers, which significantly lowers the risk of breaches and unauthorized access. Unlike cloud-based solutions, where data often travels long distances and passes through third-party systems, local processing keeps sensitive information within your organizational walls.

Greater Data Control and Ownership
With local AI, businesses retain complete ownership of their data, avoiding dependency on cloud providers. This gives companies the flexibility to customize deployments, optimize hardware usage, and scale on their own terms—all while maintaining tighter security.

Improved Efficiency and Reduced Vulnerability
By eliminating the need to transfer massive datasets across networks, local AI reduces latency and streamlines real-time data processing. Solutions like webAI allow businesses to process information directly on their devices, enabling faster, more efficient decision-making without compromising data integrity.

Real-World Use Cases: Privacy-First AI in Action

Many AI solutions will promise advanced human decision-making and premier capabilities without true security transparency and privacy-first design. Discover how webAI gives you the reins on privacy, eliminates dependency, and supercharges your AI on your terms.

• Healthcare: Part of new HIPAA regulations includes eliminating third-party vendor access to patient data. webAI can help healthcare providers protect patient data and comply with regulations by keeping sensitive information within the organization. 
• Manufacturing: Manufacturing companies must protect IP and proprietary formulas. You need AI that functions as an internal department—never risking a leak of highly damaging proprietary data.
• Legal and Government: Modern data laws are continuing to evolve, and many call for strict control and maintenance of cloud data, especially across borders. webAI’s privacy-first approach is ideal for law firms or government entities dealing with confidential data as it keeps your data in your hands, negating the risk of legal action.

How Businesses Can Prioritize Privacy in Their AI Strategy

Consider platforms that ensure complete data privacy, control, and efficiency. Use the following steps to guide your journey to a privacy-first ecosystem. 

1. Implement Local AI Solutions: Look for solutions like webAI that offer local processing and enhanced privacy.
2. Evaluate Data Handling Practices: Assess how AI models process and store data, especially if using third-party providers.
3. Train Teams on Privacy Best Practices: Educate employees on data handling and privacy measures to prevent internal risks.

The Future of AI: Privacy-First Innovation with webAI

Findings show that privacy concerns and a desire for smooth adoption are likely to drive more local, secure AI deployments. Local AI users are more likely to increase their investment in the coming year compared to cloud AI users due to higher reported success and effectiveness in adoption. Nearly half (48%) of companies deploying most of their AI locally describe the adoption process as “very smooth,” compared to 40% of cloud-heavy businesses. 

Local AI users also report stronger outcomes: 73% say their investments have “exceeded expectations,” and 57% are “very satisfied” with AI’s ability to address business challenges, compared to 61% and 42%, respectively, among cloud users. 

webAI’s mission is to provide cutting-edge AI without sacrificing data privacy, setting a new standard in the industry.

Empower Your Business with Privacy-First AI

The alarming number of recent AI-related breaches highlights the urgent need for business and technical leaders to elevate their approach to safeguarding data. Enhancing data privacy and security is essential. 

Learn more about webAI’s privacy-focused solutions and explore how local AI can support your business goals while safeguarding data. Learn more about our innovative process, sign up, and get started now. 

‍