Privacy in AI-Powered Devices Is More Important Than Ever
AI is transforming small and medium-sized businesses (SMBs), but it brings privacy risks and compliance challenges that can’t be ignored. In 2025, SMBs need to prioritize privacy to protect customer data, comply with laws, and build trust. Here’s what you need to know:
- Consumer Concerns: 68% of people worry about online privacy, and 57% see AI as a threat. But strong privacy laws make 59% feel safer sharing data.
- Regulations: 20 U.S. states now have privacy laws, with penalties reaching $50,000 per violation in some cases.
- Cyber Threats: SMBs face rising risks, with 46% of breaches targeting businesses with fewer than 1,000 employees.
- Privacy Tech: Tools like on-device AI, homomorphic encryption, and blockchain are helping businesses safeguard data.
Quick Tip: Start by adopting privacy-by-design strategies, using AI-powered compliance tools, and providing clear data controls to meet customer expectations.
Read on to learn about new privacy regulations, cutting-edge technologies, and actionable strategies for SMBs to stay ahead in 2025.
New Privacy Regulations and Compliance for SMBs
Navigating privacy regulations is increasingly challenging for small and medium-sized businesses (SMBs) in the U.S. With no unified federal law in place, SMBs must manage a web of state-specific and sector-specific rules that complicate compliance, especially when deploying AI-powered smart devices.
US Privacy Laws and Their Effects
As of April 7, 2025, 20 states in the U.S. have enacted comprehensive data privacy laws, with more states expected to follow suit. Recent additions to this growing list include Delaware, Iowa, Nebraska, New Hampshire, New Jersey, Tennessee, Minnesota, and Maryland.
Among these, the California Consumer Privacy Act (CCPA) stands out as a key regulation. It applies to businesses that meet specific thresholds and collect personal data from California residents. SMBs using tools like Dialzara need to understand these thresholds to ensure compliance.
State privacy laws generally fall into three categories: California-style, Virginia-style, and Utah-style, each offering varying levels of consumer rights and business obligations. For example, Iowa's Consumer Data Protection Act (ICDPA) is considered one of the least restrictive, offering weaker protections for consumers. Meanwhile, the Federal Trade Commission (FTC) enforces data security measures at the national level.
International Privacy Frameworks
For SMBs operating internationally, the compliance landscape becomes even more complex. Over 120 countries now have their own privacy and security regulations, creating a maze of requirements for businesses using AI-driven devices across borders.
The EU's General Data Protection Regulation (GDPR) sets a global standard for privacy, requiring businesses to comply when handling data from EU residents. GDPR gives consumers extensive rights, including access to their data, correction, deletion, and the ability to opt out of targeted ads. Additionally, the EU AI Act introduces a risk-based framework, mandating privacy impact assessments for high-risk AI applications.
Other notable frameworks include China's Personal Information Protection Law (PIPL) and Brazil's Lei Geral de Proteção de Dados (LGPD). These laws differ in their requirements for data classification, cross-border transfers, and obtaining user consent. Between 2021 and 2023, Data Subject Requests (DSRs) surged by 246%, reflecting growing consumer awareness and stricter enforcement. As a result, SMBs must implement systems to handle requests for access, correction, and deletion efficiently.
It’s important to note that no single international privacy law applies globally. Instead, businesses must map their data flows carefully and adhere to the specific requirements of each region they operate in.
Penalties for Non-Compliance
Failing to comply with privacy regulations can lead to hefty fines. For instance, GDPR violations can result in penalties of up to €20 million or 4% of annual global turnover, whichever is higher. In the U.S., penalties vary by state. The CCPA allows fines of up to $7,500 per violation, Connecticut's CTDPA imposes up to $5,000 per violation, and Florida's Digital Bill of Rights (FDBR) can lead to fines of $50,000 per incident, with triple penalties for mishandling children's data or ignoring opt-out requests.
| Regulation | Maximum Penalty | Scope |
|---|---|---|
| GDPR | €20 million or 4% of global turnover | EU residents' data |
| CCPA/CPRA | $7,500 per violation | California residents |
| CTDPA | $5,000 per violation | Connecticut residents |
| FDBR | $50,000 per incident (tripled for children's data) | Florida residents |
| TDPSA | $7,500 per violation | Texas residents |
Beyond financial penalties, non-compliance can damage a company’s reputation. According to IBM, the average cost of a data breach in 2024 was $4.35 million globally. Verizon also reported that 43% of cyber-attacks in 2023 targeted small businesses. A Chicago-based online retailer learned this the hard way in 2023 when it was fined $500,000 under GDPR for failing to handle customer data transparently.
Gartner predicts that by 2025, over 80% of global enterprises will face privacy compliance challenges across multiple jurisdictions. SMBs must take a proactive approach to compliance by implementing privacy programs that prioritize data minimization, explicit user consent, and clear data handling practices.
As Sterling Miller, CEO of Hilgers Graben PLLC, advises:
"Tell people what you are doing with their personal data, and then do only what you told them you would do. If you and your company do this, you will likely solve 90% of any serious data privacy issues."
These developments highlight the urgent need for SMBs to adopt robust privacy measures, setting the stage for the technical solutions explored in the next section.
New Privacy-Protecting Technologies (PETs)
With privacy regulations tightening and cyber threats on the rise, small and medium-sized businesses (SMBs) need advanced tools to safeguard user data without compromising functionality. Privacy-Enhancing Technologies (PETs) provide a way to process and analyze data while keeping sensitive information secure, especially in AI-driven smart devices. These tools address both regulatory and operational challenges, giving SMBs practical defenses against modern threats.
In 2024, Amazon reported a staggering 750% surge in cyberattacks, with nearly one billion daily attempts. This dramatic increase underscores why traditional security measures are no longer enough to protect customer data in smart devices.
On-Device AI for Better Privacy
On-device AI is reshaping how smart devices handle sensitive information. By processing data locally on the device, it significantly reduces privacy risks.
For SMBs, this approach offers clear benefits. Currently, 38% of SMBs are incorporating AI into their operations, and many are finding that local data processing not only enhances security but also cuts operational costs. When sensitive customer data never leaves the device, businesses face fewer compliance hurdles and are less exposed to breaches.
Take Dialzara as an example. This platform uses on-device AI for local voice processing, ensuring customer data stays secure while enabling real-time features like call screening and appointment scheduling.
Adopting on-device AI starts with identifying specific use cases. Nearly half (47%) of small businesses have already implemented new technology platforms to strengthen security, with many opting for on-device solutions due to their reduced attack surface.
"Small business owners are entering a new chapter of digital business with the rise of AI." - Aparna Khurjekar, Chief Revenue Officer, Business Markets and SaaS, Verizon Business
SMBs should evaluate their current security needs to pinpoint where on-device AI can make the biggest impact. Areas like customer service automation, voice recognition, and basic data analysis are often ideal for local processing. Combining on-device AI with encryption methods can further enhance data security by minimizing external exposure.
Homomorphic Encryption for Data Security
Homomorphic encryption is another powerful tool for protecting data. This technology allows businesses to perform calculations on encrypted data without decrypting it, ensuring sensitive information remains secure throughout the process.
This method is especially useful for SMBs that need to analyze patterns or run AI algorithms while maintaining strict privacy protections. Homomorphic encryption comes in three types: Partially Homomorphic Encryption (PHE), Somewhat Homomorphic Encryption (SHE), and Fully Homomorphic Encryption (FHE). For most SMBs, PHE or SHE is sufficient, as they require less computational power.
"As 2025 dawns, FHE (fully homomorphic encryption) is a PET (privacy-enhancing technology) on the cusp of going mainstream." - Jorge Myszne, Chief Product Officer, Niobium Microsystems
The applications for homomorphic encryption are expanding rapidly. For example, healthcare providers can analyze patient data for trends without exposing individual records, while financial services can assess risk patterns while keeping customer information encrypted. Even customer service teams can evaluate call metrics without compromising privacy.
Although homomorphic encryption requires specialized expertise and can be computationally demanding, its benefits for handling sensitive data make it a worthwhile investment. SMBs can start with simpler implementations and scale up as their needs grow.
Additionally, this technology helps businesses meet compliance requirements. By keeping data encrypted during processing, companies can more easily adhere to regulations like GDPR, CCPA, and HIPAA. This reduces regulatory risks while enabling valuable insights from data analysis.
Blockchain for Decentralized Access Control
Blockchain technology is revolutionizing how SMBs manage data access and maintain tamper-proof records. By distributing data across decentralized networks, blockchain eliminates single points of failure and provides transparent, unchangeable audit trails of all data interactions. These features align well with strict compliance standards.
For smart device ecosystems, blockchain offers unique benefits in access control. It enables decentralized systems to verify permissions across multiple nodes, making unauthorized access much harder. Every interaction with customer data is logged on the blockchain, creating a permanent record that regulators and customers can trust.
Blockchain-based encryption is emerging as a key trend for 2025. By combining traditional cryptography with distributed ledger technology, businesses can create stronger security frameworks. SMBs can use these solutions to protect customer data while maintaining operational flexibility.
Implementation often begins with targeted use cases rather than overhauling entire systems. Common starting points include managing customer consent, tracking data-sharing agreements, and maintaining access logs. Over time, businesses can expand to more advanced applications like smart contracts for automated compliance.
Blockchain also supports data sovereignty, allowing businesses to control where their data is stored and processed. This is particularly important as regulations increasingly emphasize local data control and limit cross-border transfers.
Costs for blockchain implementation vary based on the scope of use. While enterprise solutions can be pricey, many cloud providers now offer blockchain-as-a-service options, making the technology more accessible to smaller businesses. The key is to start with focused projects that deliver measurable benefits before scaling up.
How SMBs Can Meet Consumer Privacy Expectations
Small and medium-sized businesses (SMBs) are now facing the dual challenge of meeting consumer privacy expectations while navigating the complexities of AI-powered technologies. With data protection laws covering 6.3 billion people worldwide, customers increasingly demand transparency and control over their personal data. For SMBs, this isn't just about ticking regulatory boxes - it's about building trust and ensuring long-term survival. Consider this: SMBs are the most frequent targets of malicious emails, with one in every 323 being aimed at them. Strong privacy practices are no longer optional - they're essential.
Building Clear AI Interfaces
Transparency starts with technology that's easy for users to understand. AI systems should clearly show how user inputs lead to specific outputs. For example, if a smart device makes recommendations or decisions, it’s crucial to provide straightforward explanations that users can grasp without needing a technical background.
Using interpretable models like decision trees or rule-based systems can simplify this process. For more complex AI, explanation frameworks such as LIME or SHAP can help break down the "why" behind decisions. Consistency is key, too - users should see stable and reproducible explanations for similar inputs, which builds confidence in the system.
"Trust in AI begins with understanding - when our clients see the why and how, they can truly harness its potential in video marketing and beyond." - Michelle Connolly, Director
"A transparent AI is a trusted AI. By unpacking the 'black box' and making AI operations intelligible, we not only comply with ethical standards but also empower users to exploit AI with confidence and critical understanding." - Stephen McClelland, ProfileTree's Digital Strategist
SMBs should also ensure their AI interfaces allow users to override decisions or opt out entirely. Documenting data sources, preprocessing steps, and model assumptions is equally important. Presenting this information through user-friendly dashboards or reports can make a big difference. For example, Dialzara provides clear explanations of how their AI phone agents handle customer interactions, helping businesses communicate their AI’s functionality effectively.
Transparent interfaces lay the groundwork for offering consumers greater control over their data.
Providing Detailed Data Controls
Once transparency is established, the next step is empowering users with robust data controls. With nearly 80% of global data now under privacy regulations, consumers expect granular management of their personal information. This means going beyond a simple "accept all" or "decline all" approach. Instead, offer consent options that let users choose specific data uses while rejecting others. Make it easy for users to withdraw consent without jumping through hoops.
Privacy dashboards can help here. These should clearly show what data is being collected, how it’s used, and who it’s shared with. Avoid legal jargon - write privacy policies in plain language so they’re understandable to everyone, not just legal experts.
"The privacy of our customers' data is very important to us, and we want to make sure we are acting in accordance with their wishes as well as complying with all state laws. Ketch helps us do this without a lot of overhead so we can focus our internal resources on growing our technology capabilities and supporting our aggressive omni-channel growth plans." - Mike Early, Chief Technology Officer, Francesca's
Customizable preference centers can further enhance user control by allowing adjustments to data-sharing settings. Timely notifications that explain when and why data is being collected are another way to build trust. Streamline processes for data access, correction, and deletion requests, and conduct regular audits to ensure only necessary information is retained. Adopting data minimization practices not only simplifies compliance but also strengthens customer relationships.
Protecting Data Sovereignty
Data sovereignty means ensuring that data complies with the laws of the country where it’s stored. For SMBs using AI-driven technologies, this is a critical component of both trust and compliance. One straightforward approach is data localization - keeping data storage and processing within national borders to reduce cross-border compliance risks.
When transferring data internationally, strong encryption and access controls are a must. Clear data protection agreements should be in place, ensuring that both the source and destination jurisdictions meet regulatory standards. SMBs must also scrutinize third-party vendor contracts to ensure compliance with privacy laws. Pair these efforts with secure IT infrastructure and robust encryption to safeguard data during transit.
It’s equally important to communicate openly with customers about where their data is stored, how it’s processed, and who has access. Platforms that automate consent management tasks can help SMBs navigate the challenges of multi-jurisdictional regulations.
"The key features of privacy software will help companies find sensitive data across their systems, understand how it flows, and handle requests from customers to access their information. Pre-set compliance options for major laws like GDPR will also be a must-have to make regulatory compliance a breeze." - Jedd Macosko, CEO of Academic Influence
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Practical AI Privacy Strategies for SMBs
Small and medium-sized businesses (SMBs) are navigating the tricky waters of implementing effective and affordable AI privacy measures in 2025. With data protection laws now affecting 6.3 billion people - 79% of the global population - SMBs must act fast to meet these regulations while staying competitive. The following strategies provide actionable steps to help SMBs tackle these challenges.
Using Privacy-by-Design
Privacy-by-Design (PbD) shifts the focus from reactive fixes to proactive privacy protection by integrating safeguards directly into systems during their development. For SMBs leveraging AI-powered tools, this means addressing privacy concerns right from the start of the product-development process. This approach aligns with existing privacy regulations and complements privacy-enhancing technologies.
To get started with PbD, conduct a thorough data audit to understand what data is collected, how it’s stored, and how it’s used. This includes cataloging personal data types and mapping how customer information, such as voice data, moves through an AI phone system - from the initial call to storage or deletion. Anonymizing personal data by removing identifiable markers is another critical step. Strengthen your defenses with access controls, encryption, and secure storage. Additionally, establish clear agreements with third-party vendors to ensure they also maintain high privacy standards.
AI-Powered Privacy Tools
AI-powered privacy tools offer SMBs advanced solutions that are both effective and budget-friendly. For example, compliance management tools can cut manual compliance work by up to 40%. These platforms often deliver a strong return on investment, boosting the productivity of compliance teams. Even for businesses with limited budgets, tools like Osano and Enzuzo provide cost-effective options. Some solutions can save up to 80 hours per month on compliance tasks and reduce audit preparation time by 50–70%.
These tools typically include features like automated compliance workflows, real-time tracking, centralized document management, and analytics to flag non-compliance risks. AuditBoard, for instance, has been particularly effective in this area. Melissa Pici, Senior IT Audit Manager at Syniverse, shared her experience:
"AuditBoard AI has been a game-changer for me and my team… something that used to take twenty minutes now takes only five."
Affordable Data Protection Methods
Beyond high-tech tools, SMBs can adopt straightforward, cost-effective security measures to protect their data without overhauling their infrastructure. Key methods include implementing multi-factor authentication (MFA) to block unauthorized access, using network segmentation to separate AI systems from customer data, and deploying firewalls, encryption, and secure cloud services for added protection.
Another powerful approach is adopting a Zero-Trust Architecture, which operates on the principle of "never trust, always verify." This model ensures every access request is verified, reducing vulnerabilities. SMBs can simplify their security efforts by choosing platforms that streamline management, minimize hidden costs, and address potential security gaps, ensuring robust data protection without breaking the bank.
Conclusion: Preparing for AI Privacy Trends
The world of AI privacy is evolving at lightning speed. With 77% of small and medium-sized businesses (SMBs) already leveraging AI and 91% reporting revenue gains, the question isn’t whether to adopt AI - it’s how to do it responsibly.
The stakes couldn’t be higher. Between 2021 and 2023, Data Subject Requests skyrocketed by 246%, and 70% of AI users now voice concerns about privacy.
"We're super supercharging SMBs to do more with less, which will enable them to better compete with larger enterprises."
- Kris Billmaier, Executive Vice President and General Manager, Sales Cloud and Growth, Salesforce
But with great power comes great responsibility. Cybercrime is projected to cost the world $10.5 trillion annually by 2025, making it clear that businesses need strong privacy measures in place. While AI offers incredible opportunities, it also introduces risks. Today, protecting privacy isn’t just a regulatory requirement - it’s a way to stand out in the market.
For SMBs, this means taking a strategic approach to privacy. It’s not enough to simply meet compliance standards. Businesses need to adopt Zero-Trust security frameworks, integrate Privacy-Enhancing Technologies, and create clear AI governance policies. This includes offering practical tools like user-friendly privacy dashboards, granular consent controls, and transparent data practices.
For example, AI-powered communication tools - like Dialzara's virtual phone answering service - must ensure sensitive voice data is protected with strong encryption and strict access controls.
FAQs
How can SMBs ensure compliance with state and international privacy laws when using AI-powered smart devices?
SMBs can tackle the challenges of state and international privacy laws by taking a proactive approach to compliance. This means keeping up with changing regulations, such as state-specific privacy laws in the U.S., which focus on data protection and transparency when managing customer information. A good starting point is to establish clear policies for how data is collected, stored, and shared.
To make compliance easier, SMBs can turn to AI-driven tools that streamline privacy management. These tools can handle tasks like tracking data usage, ensuring compliance with both local and international regulations, and minimizing the risk of violations. By making privacy a priority and using the right technology, SMBs can strengthen customer trust and steer clear of penalties in a constantly evolving regulatory environment.
What are the benefits and challenges of using on-device AI for privacy in smart devices, and how can SMBs identify the best ways to apply it?
On-device AI brings a big advantage: better privacy. By processing data directly on the device, sensitive information stays put, minimizing the risk of breaches. Plus, it delivers quicker responses and a more seamless user experience since there’s no need to rely on cloud communication. For small and medium-sized businesses (SMBs), this translates to greater control over customer data and smoother operations.
That said, there are hurdles to consider. Protecting AI models from tampering is a key concern, as is keeping up with ever-changing privacy regulations. SMBs need to assess their specific needs - whether it’s automating customer support, handling sensitive information, or something else entirely. Practical applications could include real-time customer interactions, tailored marketing efforts, or streamlined inventory management. By matching AI capabilities to their business goals, SMBs can enjoy the dual benefits of enhanced privacy and efficiency while staying on the right side of compliance rules.
How can Privacy-Enhancing Technologies like homomorphic encryption and blockchain help SMBs protect customer data and comply with privacy regulations in 2025?
Privacy-Enhancing Technologies (PETs) for SMBs in 2025
Technologies like homomorphic encryption and blockchain are transforming how small and medium-sized businesses (SMBs) handle customer data in 2025. These tools not only help meet regulatory requirements but also ensure robust data protection, which is essential for maintaining customer trust.
Homomorphic encryption is a standout innovation. It allows businesses to process and analyze sensitive information without ever exposing it. This means companies can comply with privacy laws while significantly reducing the risk of data breaches - making data security stronger than ever.
Blockchain, on the other hand, provides a secure and transparent system for managing data transactions. By decentralizing storage and granting access only to authorized users, it aligns perfectly with privacy principles like data minimization and obtaining user consent. These features make it easier for SMBs to meet today’s strict regulatory standards.
By integrating these technologies, SMBs can do more than just stay compliant - they can position themselves as champions of customer privacy. This commitment not only protects their operations but also builds trust and loyalty in a market where privacy matters more than ever.
