Innovative Technology Insights Podcast Archives | Â鶹´«Ă˝ Legal services in Boston, Massachusetts Mon, 02 Feb 2026 20:57:32 +0000 en-US hourly 1 https://wordpress.org/?v=6.8.5 /wp-content/uploads/2024/11/cropped-Â鶹´«Ă˝-Favicon-1-32x32.png Innovative Technology Insights Podcast Archives | Â鶹´«Ă˝ 32 32 Privacy Podcast Episode Four: The Blur Between Privacy and Security /p/102mfce/privacy-podcast-episode-four-the-blur-between-privacy-and-security/ Fri, 30 Jan 2026 19:04:08 +0000 /p/102mfce/privacy-podcast-episode-four-the-blur-between-privacy-and-security/ Key Takeaways The traditional separation between privacy and security is dissolving as technology and regulations force roles and...

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]]> Key Takeaways
  • The traditional separation between privacy and security is dissolving as technology and regulations force roles and responsibilities to converge. CISOs and CPOs increasingly face overlapping decisions — and overlapping accountability — driven by AI, data‑heavy systems, and fast‑changing laws.
  • Organizations widely understand how they protect data, but still struggle to explain why they collect it.
  • Regulators, cyber insurers, and global privacy laws now expect companies to justify purpose, minimize collection, and delete unnecessary data.
  • Future leaders will require hybrid legal‑technical skill sets and the ability to translate across teams, systems, and disciplines.

A Convergence Fueled by Technology and Regulation

As Aaron Tantleff and Jennifer Urban explained in Episode Four of Â鶹´«Ă˝â€™s Privacy Week series, rapid technological evolution — AI, automation, data‑heavy platforms — has reshaped what organizations must manage. At the same time, privacy and cybersecurity laws have expanded dramatically, requiring privacy teams to understand systems and security teams to understand legal risk. This has blurred the once‑clear boundaries between roles.

Privacy now governs legitimacy, proportionality, and fairness, while security ensures resilience and detection — but both influence the same controls, from access management to logging. The result: two disciplines that remain distinct but now move in lockstep.

The Hardest Question Isn’t “How” – It’s “Why”

Most organizations can demonstrate how they protect data — through encryption, access controls, and security protocols. But many cannot clearly answer why they collect the data they have.

 Coming out of the “collect everything” era, companies often lack a full understanding of:

  • What they collect
  • Where it lives
  • How long it stays
  • Whether it serves a legitimate purpose

Even privacy questionnaires frequently reveal gaps: organizations discover data they didn’t realize they held or can’t justify continued retention.

AI has intensified this challenge, making data minimization harder and purpose limitation increasingly complex. As Urban notes, the hardest conversations are often around why data is collected — not how it’s secured.

From Data Hoarding to Data Strategy

Global laws and cyber insurers are pushing organizations to shift from stockpiling data to practicing disciplined data strategy. This includes:

  • Defining clear business purposes for each category of data
  • Limiting secondary uses
  • Reducing data retention
  • Deleting information once its purpose has expired
  • Vetting vendors and AI partners for appropriate safeguards

Tantleff emphasizes that mature organizations are the ones willing to delete data they no longer need — an area where many still struggle.

Building the Next Generation of Data Leaders

Tomorrow’s security and privacy leaders must be part technologist, part lawyer, part strategist, and part translator. Organizations are already hiring attorneys with engineering backgrounds, privacy professionals with technical fluency, and security experts with policy experience. 

Regulators now view a lack of high‑level privacy leadership as a warning sign. Many industries are elevating privacy and security roles to the C‑suite, recognizing that these domains are critical to trust, compliance, and long‑term business sustainability.

Risk Will Never Be Zero – But it Must Be Understood

Both partners noted that security can never be perfect. Organizations must accept a baseline level of risk — but they must understand it, document it, and manage it. 

True stewardship is no longer about collecting everything “just in case.” It’s about being able to articulate:

  • Why the data exists
  • What risks it introduces
  • How it is being minimized
  • When it should be deleted 

And as both experts note, deletion — letting go of unnecessary data — is often one of the strongest indicators of organizational maturity.

Conclusion

The boundary between privacy and security has blurred not by accident, but out of necessity. Modern enterprises face unprecedented complexity, and neither discipline can succeed without the other. The organizations that will thrive in this environment are those that embrace unified governance, hire hybrid thinkers, and shift from defensive checklists to thoughtful data strategy.

Most importantly, they will be the organizations willing to slow down, justify why they collect data — not just how they protect it — and make responsible decisions that build trust for the long term.

Interested in staying ahead of the latest privacy developments?

Listen to Â鶹´«Ă˝â€™s Cybersecurity & Data Privacy Group podcast series, where our attorneys break down evolving regulations, emerging risks, and what they mean for your business.

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]]> Privacy Podcast Episode Three: State of Confusion: Navigating the U.S. Privacy Law Maze /p/102meip/privacy-podcast-episode-three-state-of-confusion-navigating-the-u-s-privacy-la/ Wed, 28 Jan 2026 17:02:40 +0000 /p/102meip/state-of-confusion-navigating-the-u-s-privacy-law-maze/ Key Takeaways U.S. privacy compliance has become significantly more complex due to the rapid growth of state consumer privacy laws, each...

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]]> Key Takeaways
  • U.S. privacy compliance has become significantly more complex due to the rapid growth of state consumer privacy laws, each with unique thresholds, exemptions, rights, and definitions.
  • California remains the most stringent and operationally impactful state, especially because it regulates business‑to‑business and employee data, unlike most other states.
  • Many states follow similar patterns, but critical distinctions—such as the definition of “sale,” applicability thresholds, and treatment of sensitive data—substantially affect compliance programs.
  • Two competing approaches have emerged: the “Race to the Top” (one‑size‑fits‑all) model and the “Different Strokes” (jurisdiction‑specific) framework. Most companies will land somewhere between the two.
  • Even perfect compliance with state privacy laws does not shield companies from litigation risks under older, repurposed laws such as the California Invasion of Privacy Act (CIPA) and the Video Privacy Protection Act (VPPA).
  • Organizations should revisit their website tracking practices, cookie consent strategies, vendor contracts, and arbitration clauses to reduce exposure to these non‑privacy‑law threats.
  • The privacy landscape continues to evolve quickly, and businesses should continuously monitor developments, update internal processes, and refine compliance strategies.
  • Link to Cover Page with Â鶹´«Ă˝â€™s U.S. State Comprehensive Consumer Data Privacy Law Comparison Chart: /insights/publications/2026/01/us-state-consumer-data-privacy-laws/

  • Link to Â鶹´«Ă˝â€™s U.S. State Comprehensive Consumer Data Privacy Law Comparison Chart: /wp-content/uploads/2026/01/U.S.-State-Comprehensive-Consumer-Privacy-Law-Comparison-Chart_V16.pdf

     

Introduction

If you are a company operating across the United States today, you are navigating one of the most complex privacy regulatory environments in the world. Unlike the European Union, which has a single, comprehensive privacy framework in the General Data Protection Regulation (GDPR), the U.S. has no federal privacy law governing the collection and use of personal information. Instead, states have taken the lead — creating a fast‑growing, often contradictory patchwork of rules that can create compliance challenges even for sophisticated businesses with strong privacy practices.

In the State of Confusion: Navigating the U.S. Privacy Law Maze episode of Â鶹´«Ă˝ & Lardner’s Privacy podcast, attorneys Sam Goldstick and Alex Misakian from Â鶹´«Ă˝â€™s Technology Transactions, Cybersecurity & Privacy Practice Group broke down this maze with clarity, humor, and practical insights. Their discussion covered the evolution of state privacy laws, the nuances that distinguish them, and the operational decisions companies must make to remain compliant. They also explored why, even when companies “get privacy right,” they are still vulnerable to lawsuits under older statutes that predate the modern internet.

The Rise of the State-Based Privacy Regime

When the GDPR took effect in 2018, it redefined expectations worldwide for data protection. That same year, California passed the California Consumer Privacy Act (CCPA) â€” the first comprehensive consumer privacy law in the U.S., later amended and expanded into the California Privacy Rights Act (CPRA). California’s law set the tone, and over the following years, more than 20 additional states enacted their own privacy statutes.

As Goldstick noted, the U.S. privacy landscape today is defined by similarity on the surface but divergence in the details. All these laws grant certain consumer rights — like the right to access personal data and the right to delete it — but they implement these rights differently. Each state uses its own definitions, exemptions, applicability thresholds, timelines, and obligations.

This divergence is not merely academic. It determines whether your business must comply, how operationally burdensome compliance will be, which data must be protected, and how companies must respond to consumer requests.

Despite calls for a federal privacy law, disagreements over preemption and private rights of action have stalled progress in Congress. In the absence of federal legislation, states continue to fill the void.

California: The Most Impactful State in the United States

California remains the heavyweight in U.S. privacy law. It enforces some of the strictest requirements and includes several features other states do not.

A Standalone Revenue Threshold

California is the only state whose privacy law applies when a business meets a standalone revenue threshold â€” $26,625,000 (inflation-adjusted from the original $25M) in annual gross revenue — regardless of how many consumers’ data it processes. This threshold means many business‑to‑business companies and non‑consumer‑facing organizations are subject to the law.

Employment and B2B Data Coverage

Most states limit their consumer privacy laws strictly to “consumers.” California applies its law to:

  • Employees
  • Job applicants
  • Contractors
  • Business representatives/contacts

This dramatically expands compliance obligations for HR teams and sales operations, especially for national companies that meet California’s applicability threshold.

Opt-Out vs. Opt-In for Sensitive Data

Many states require opt‑in consent to process sensitive data. California instead generally restricts businesses from using or disclosing residents’ “sensitive personal information” beyond those purposes specifically enumerated in the CPRA (and does not require covered businesses to obtain prior opt-in consent from individuals), making the CPRA surprisingly less stringent than the vast majority of other existing state consumer privacy laws in this respect. But in nearly every other regard — enforcement, thresholds, rights, and scope — California remains the most complex state to comply with.

For any business evaluating its privacy compliance program, understanding California’s operational impact is essential.

Baseline States: The Virginia Model and Its Variations

Outside of California, many states have enacted laws modeled on the Virginia Consumer Data Protection Act (VCDPA). These “baseline states” include:

  • Virginia
  • Indiana
  • Kentucky
  • Tennessee
  • Texas
  • Nebraska
  • Rhode Island

These baseline states generally provide:

  • Right to access
  • Right to delete
  • Right to correct
  • Right to portability
  • Right to opt out of sales
  • Right to opt out of targeted advertising (or “sharing” under the CPRA)
  • Right to opt out of profiling in certain contexts

But, as Misakian explained, even these “similar” states include differences that can create major compliance challenges.

Key Distinctions Among State Privacy Laws

  1. Definition of “Sale”

Many states adopt California’s broad definition of “sale,” which means sharing personal data for “valuable consideration”, even if no money is exchanged. Under this definition:

  • Third‑party analytics
  • Targeting cookies
  • Pixel‑based ad tools
  • Cross‑context behavioral advertising

…may be considered a “sale,” requiring specific disclosures and opt‑out rights.

Some states, however — such as Virginia and Indiana — take a narrower view, requiring monetary consideration for a sale to occur.

This single definitional difference can dramatically alter compliance strategies for cookies, pixels, and analytics tools.

  1. Applicability Thresholds

States diverge sharply in when their laws apply.

  • California: Standalone revenue threshold.
  • Texas & Nebraska: No numerical thresholds; if you do business in the state and are not a small business under federal rules, the law applies.
  • Others: Consumer‑count thresholds ranging from 35,000 to 175,000 residents.

Connecticut is especially notable: starting July 1, 2026, its threshold is so low that many companies will qualify unexpectedly.

  1. Exemptions

Differences in exemptions create significant compliance headaches, especially for financial services, healthcare, and utilities.

Examples:

  • Some states exempt GLBA‑covered financial institutions entirely.
  • Others exempt only GLBA‑covered data, not the entity.
  • Some exempt utilities, while others do not.
  • Some exempt nonprofits, while others regulate them.

A business subject to one state’s law may be exempt from another’s, even if its operations are identical.

  1. Consumer Rights & Timelines

Response timelines also vary:

  • Some states require responses within 45 days
  • Others require 30 days
  • California requires a 10‑day acknowledgment in all cases

Appeal timelines differ as well, creating additional burdens for companies with high request volumes.

  1. Data Rights Variability 

Even core privacy rights differ across states.

Examples:

  • Iowa offers no correction right.
  • Utah does not require opt‑outs for profiling.
  • Oregon and Minnesota require businesses to disclose specific third parties with whom they share information.

These variations may seem small, but they meaningfully impact operations and consumer communications.

Compliance Approaches: One-Size-Fits-All vs. Tailored Models

Goldstick and Misakian debated two primary approaches companies can take when building privacy programs.

Both approaches offer strengths and weaknesses, and most organizations will eventually land somewhere between them.

Approach One: “Race to the Top” 
(One-Size-Fits-All)

This approach applies the most stringent requirements from across all applicable states to all consumers, regardless of their state of residence.

Advantages

  • Simplifies internal operations
  • Reduces risk of misclassification
  • Promotes consistency across systems
  • Helps future‑proof against new state laws
  • Allows companies to market strong privacy protections
  • Creates potential legal risk:
    By voluntarily applying California rights to all consumers, companies may expose themselves to enforcement if they miss deadlines or mishandle rights requests.
  • May impose unnecessary obligations:
    For instance, treating all consumers as if they are subject to Washington’s My Health My Data Act would require universal opt‑in consent for health data — highly impractical for many businesses.

Employees are less likely to apply the wrong rule because there is only one rule.

Challenges

  • Creates potential legal risk:
    By voluntarily applying California rights to all consumers, companies may expose themselves to enforcement if they miss deadlines or mishandle rights requests.
  • May impose unnecessary obligations:
    For instance, treating all consumers as if they are subject to Washington’s My Health My Data Act would require universal opt‑in consent for health data — highly impractical for many businesses.

Approach Two: “Different Strokes for Different Folks” (Jurisdiction-Specific)

This approach builds ˛őłŮ˛ąłŮ±đ‑s±č±đł¦ľ±´Úľ±ł¦ workflows, often supported by geolocation tools, to apply the right rules to the right consumers.

Advantages

  • Supports flexibility where it matters
  • Avoids over‑compliance
  • Allows businesses in regulated industries to tailor rules for specific states
  • Reduces operational burdens in states with fewer requirements

This method works well for organizations needing to preserve business agility — for example, healthcare and financial services companies, or businesses whose success depends heavily on data analytics.

Challenges

  • More operationally complex
  • Requires branching logic
  • Higher risk of employee or system error
  • Requires rigorous training and internal oversight

Regulators may also perceive inconsistency across jurisdictions as a red flag if programs are not carefully implemented.

Finding the Middle Ground

As both agreed, most companies will adopt a hybrid approach.

For example:

  • Apply a uniform set of rights across most states
  • But tailor obligations for outlier states like Washington or Texas
  • Use a common privacy notice with addendums
  • Introduce ˛őłŮ˛ąłŮ±đ‑s±č±đł¦ľ±´Úľ±ł¦ overlays only where absolutely necessary
  • Preserve flexibility where it materially impacts business operations

This approach reduces over‑compliance while avoiding the operational chaos of fully splintered programs.

The Hidden Thread: Non-Privacy-Law Lawsuits

Even perfect compliance with state privacy laws does not protect companies from exposure to an entirely separate and growing category of litigation: claims under older laws not written for modern technologies.

Two statutes in particular have become favorites of the plaintiffs’ bar.

The California Invasion of Privacy Act (CIPA)

Originally enacted in 1967 as a wiretapping law, CIPA was never intended to regulate pixels, cookies, chatbots, or web analytics. Yet plaintiffs now argue that:

  • When a website uses third‑party tools like the Meta Pixel
  • And those tools collect browsing or interaction data
  • The website operator is “aiding and abetting” third‑party eavesdropping

This theory has resulted in hundreds of lawsuits, with statutory damages up to $5,000 per violation or three times actual damages (whichever is greater), plus injunctive relief.

Even nuisance claims can be expensive to resolve.

Although legislative efforts to modernize CIPA exist, progress has stalled. Businesses must assume these lawsuits will continue.

The Video Privacy Protection Act (VPPA)

Passed in 1988, the VPPA was designed to protect video rental records in the era of Blockbuster. Today, plaintiffs argue that:

  • A user watching a video clip on a website
  • Combined with third‑party tracking tools
  • Equals unlawful disclosure of “viewing history”

Courts have entertained this theory, and several large settlements — including $46 million in 2024 across six major cases — show how serious the exposure can be.

Industries most at risk include:

  • Media
  • Retail
  • Finance
  • Healthcare
  • Any website with embedded video and Meta Pixel installed

POST-PODCAST UPDATE: On January 26, 2026, the U.S. Supreme Court granted certiorari in Salazar v. Paramount Global, which may provide clarity on key questions about VPPA standing and scope; until then, VPPA litigation remains a major risk vector. 

Risk-Reduction Strategies for These Non-Privacy Laws

To mitigate the risk of CIPA and VPPA lawsuits, Goldstick and Misakian recommend:

  • Using YouTube A‑Frame players with upfront disclosures
  • Implementing robust cookie consent managers
  • Conducting website tracking audits
  • Reviewing contracts with vendors that receive personal data
  • Ensuring arbitration clauses exist in Terms of Use
  • Maintaining ongoing monitoring of legal developments

Many clients are surprised to learn what tracking tools are running on their websites. And because litigation theories shift quickly, businesses should treat this as an ongoing compliance area — not a one‑time review.

The Privacy Compliance Bottom Line

The podcast concluded with three major takeaways for organizations evaluating or maturing their privacy programs:

1. The Privacy Landscape Is Only Getting More Complicated

With over 20 comprehensive state consumer privacy laws currently in effect and more on the way, the patchwork of state privacy laws across the U.S. will remain fragmented for the foreseeable future. Companies cannot rely on federal legislation to unify the rules anytime soon.

2. Your Compliance Approach Must Fit Your Business

Whether you choose a race‑to‑the‑top approach, a tailored jurisdiction‑specific model, or a hybrid solution, the right choice depends on:

  • Your operations
  • Your systems
  • Your risk tolerance
  • Your industry
  • The nature of your data
  • Your internal resources

3. Even Perfect Compliance Is Not Enough

CIPA and VPPA claims create additional litigation risk, which requires separate risk‑reduction strategies beyond privacy law compliance.

Conclusion

State consumer privacy laws have created a dynamic, often dizzying patchwork of requirements that businesses must navigate carefully. Understanding each state’s unique thresholds, definitions, exemptions, and consumer rights is foundational — but choosing the right approach for your company’s privacy program is equally important.

Whether your organization leans toward a one‑size‑fits‑all strategy, a more tailored approach, or a hybrid model, thoughtful planning and consistent execution are essential. And because legal threats increasingly arise from older statutes not designed for modern technologies, companies must review their web tracking practices, vendor relationships, and disclosures with equal rigor.

For organizations navigating this complex terrain, Â鶹´«Ă˝â€™s Technology Transactions, Cybersecurity & Privacy Practice Group is here to help — offering practical, actionable guidance grounded in deep experience.

Interested in staying ahead of the latest privacy developments?

Listen to Â鶹´«Ă˝â€™s Cybersecurity & Data Privacy Group podcast series, where our attorneys break down evolving regulations, emerging risks, and what they mean for your business. 

Click Here to Listen to other Privacy Podcast Episodes.

The post Privacy Podcast Episode Three: State of Confusion: Navigating the U.S. Privacy Law Maze appeared first on Â鶹´«Ă˝.

]]> Privacy Podcast Episode Two: A Practical Guide to Risk Assessments and Automated Decision-Making Requirements /p/102meco/privacy-podcast-episode-two-a-practical-guide-to-risk-assessments-and-automated/ Tue, 27 Jan 2026 16:52:39 +0000 /p/102meco/privacy-podcast-episode-two-a-practical-guide-to-risk-assessments-and-automated/ Key Takeaways New CCPA regulations effective January 1, 2026, introduce significant new obligations for businesses, including...

The post Privacy Podcast Episode Two: A Practical Guide to Risk Assessments and Automated Decision-Making Requirements appeared first on Â鶹´«Ă˝.

]]> Key Takeaways
  • New CCPA regulations effective January 1, 2026, introduce significant new obligations for businesses, including cybersecurity audits, risk assessments, and automated decision‑making technology (ADMT) requirements.
  • Cybersecurity audits apply only to organizations whose processing presents a “significant risk” to consumers and roll out on a phased schedule through 2030.
  • The regulations require detailed, evidence‑based audits — meaning businesses must prepare policies, logs, configurations, and documentation, not just attestations.
  • New risk assessments are required for certain processing of sensitive personal information, ADMT, biometric data, and data sharing or selling activities.
  • California’s new framework raises the compliance bar and will require companies to invest early, document thoroughly, and engage experienced auditors to avoid bottlenecks.
  • Organizations should begin preparation now by reviewing data processing activities, identifying ADMT use, and assessing whether they will meet the newly defined thresholds.

Introduction

The California Consumer Privacy Act (CCPA) has evolved considerably since its original passage, and the latest wave of regulations — approved by the Office of Administrative Law on September 23, 2025, and effective January 1, 2026 — introduces some of the most sweeping changes to date. These updates reflect several years of engagement between the California Privacy Protection Agency (now rebranded as Cal Privacy) and a broad group of industry stakeholders.

In a recent Â鶹´«Ă˝ podcast, privacy leaders Steve Millendorf and Gabe Wild, both attorneys in the Technology Transactions, Cybersecurity, and Privacy Practice Group, walked through the regulations and their implications for businesses. Their discussion made one truth clear: these rules represent a significant operational uplift for many organizations, especially those processing large amounts of personal information or using automated decision‑making technologies.

Risk Assessment Requirements

While cybersecurity audits focus on system security, privacy risk assessments examine how businesses use personal information — and the risks associated with that use.

What Triggers a Risk Assessment?

A business must conduct a risk assessment if it engages in processing that presents a significant risk to consumer privacy, including:

  • Selling or sharing personal information
  • Processing sensitive personal information
  • Using ADMT in ways that affect consumers’ rights or opportunities
  • Processing biometric or identity‑verification data
  • Training automated systems on personal information

Importantly, some practices — such as targeted advertising — are generally excluded unless elevated risk factors are involved.

Timelines and Retention

For existing processing activities, the first risk assessment is due by:

  • December 31, 2027

After that, risk assessments must be updated:

  • Every three years, or
  • Within 45 days of a material change in processing

All assessments must be retained for five years.

What Must the Risk Assessment Include?

The assessment must document in detail:

  • The business purpose for processing
  • Categories and sources of personal information
  • Methods of collection, use, retention, and disclosure
  • The logic and limitations of ADMT (if applicable)
  • Risks to consumers, including:
    • Bias or discrimination
    • Loss of control
    • Economic impacts
    • Psychological or reputational harm
  • The benefits to consumers and stakeholders
  • Safeguards to mitigate harms

After completing the analysis, the business must evaluate whether risks outweigh benefits and, if so, discontinue processing.

This requirement echoes elements of the GDPR’s Data Protection Impact Assessments but is more explicitly tied to documented harm and mitigation.

Automated Decision‑Making Technology

The regulations introduce new transparency and risk assessment rules for ADMT — defined broadly to include:

  • Profiling
  • Predictive analytics
  • Machine learning models
  • AI tools influencing employment, credit, or other significant decisions
  • Technologies using biometric or physiological data for identification

Businesses must provide information about:

  • The logic used
  • The role of human involvement
  • How outcomes affect consumers
  • Rights to opt out (in certain contexts)

Given the rapid adoption of AI and machine learning, this will likely become a focal area for Cal Privacy in enforcement.

Preparing Now – What Businesses Should Do Immediately

Both attorneys emphasized that early preparation is key. Even if your first audit or risk assessment is years away, the evaluation window may already have begun.

Recommended next steps include:

1. Conduct a Readiness Assessment

Review existing cybersecurity measures, documentation, and data processing activities to identify:

  • Documentation gaps
  • Missing policies
  • Incomplete configurations
  • Outdated security tools
  • High‑risk processing activities

2. Start Building Documentation

If it isn’t documented, it doesn’t exist. Begin creating:

  • Policies
  • Procedures
  • Logs
  • Reports
  • Records of data flows

3. Identify External Partners Early

Auditors, AI explainability experts, and risk assessment consultants will be in high demand.

4. Analyze All ADMT Use Cases

Many organizations use machine learning models without realizing they fall under ADMT definitions.

5. Budget for Compliance

Cybersecurity audits and risk assessments will require:

  • Staff time
  • External auditor costs
  • Technology investments
  • Remediation of identified issues

6. Perform an Internal Dry Run

Simulate an audit or risk assessment to identify:

  • Unprepared teams
  • Missing knowledge
  • Gaps in system visibility

As the attorneys emphasized: you don’t want the first person to discover a flaw to be your auditor — or a regulator.

What This Means for California Businesses

These regulations significantly expand California’s privacy framework and bring it closer to GDPR‑style governance, especially with respect to:

  • Accountability
  • Documentation
  • Transparency
  • Risk balancing
  • Consumer rights

The common theme across the podcast discussion is that this is not a check‑the‑box exercise. These regulations require thoughtful planning, technical expertise, and cross‑functional collaboration.

Organizations should treat preparation as a multi‑year journey rather than a deadline‑driven scramble. Those who start early will be best positioned to navigate the new landscape.

Conclusion

The newly adopted CCPA regulations represent one of the most consequential expansions of privacy governance in the United States. For many companies, compliance will require substantial operational changes — especially for those using automated technologies or processing data at scale.

But preparation is achievable with early planning, disciplined documentation, and the right partners. By understanding the requirements now and taking proactive steps, businesses can reduce risk, streamline compliance, and prepare confidently for the new regulatory environment.

Interested in staying ahead of the latest privacy developments?

Listen to Â鶹´«Ă˝â€™s Cybersecurity & Data Privacy Group podcast series, where our attorneys break down evolving regulations, emerging risks, and what they mean for your business.

In case you missed yesterday’s first episode and part one of the series,

The post Privacy Podcast Episode Two: A Practical Guide to Risk Assessments and Automated Decision-Making Requirements appeared first on Â鶹´«Ă˝.

]]> Privacy Podcast Episode One: A Practical Guide to the New CCPA Regulations /p/102me5g/privacy-podcast-episode-one-a-practical-guide-to-the-new-ccpa-regulations/ Mon, 26 Jan 2026 20:56:10 +0000 /p/102me5g/privacy-podcast-episode-one-a-practical-guide-to-the-new-ccpa-regulations/ Key Takeaways New CCPA regulations effective January 1, 2026, introduce significant new obligations for businesses, including...

The post Privacy Podcast Episode One: A Practical Guide to the New CCPA Regulations appeared first on Â鶹´«Ă˝.

]]> Key Takeaways
  • New CCPA regulations effective January 1, 2026, introduce significant new obligations for businesses, including cybersecurity audits, risk assessments, and automated decision‑making technology (ADMT) requirements.
  • Cybersecurity audits apply only to organizations whose processing presents a “significant risk” to consumers and roll out on a phased schedule through 2030.
  • The regulations require detailed, evidence‑based audits — meaning businesses must prepare policies, logs, configurations, and documentation, not just attestations.
  • New risk assessments are required for certain processing of sensitive personal information, ADMT, biometric data, and data sharing or selling activities.
  • California’s new framework raises the compliance bar and will require companies to invest early, document thoroughly, and engage experienced auditors to avoid bottlenecks.
  • Organizations should begin preparation now by reviewing data processing activities, identifying ADMT use, and assessing whether they will meet the newly defined thresholds.

Introduction

The California Consumer Privacy Act (CCPA) has evolved considerably since its original passage, and the latest wave of regulations — approved by the Office of Administrative Law on September 23, 2025, and effective January 1, 2026 — introduces some of the most sweeping changes to date. These updates reflect several years of engagement between the California Privacy Protection Agency (now rebranded as Cal Privacy) and a broad group of industry stakeholders.

In a recent Â鶹´«Ă˝ podcast, Steve Millendorf and Gabe Wild, both attorneys in the Technology Transactions, Cybersecurity, and Privacy Practice Group, walked through the regulations and their implications for businesses. Their discussion made one truth clear: these rules represent a significant operational uplift for many organizations, especially those processing large amounts of personal information or using automated decision‑making technologies.

Why the New CCPA Regulations Matter

California has long been at the forefront of privacy regulation in the United States. The latest expansion of the CCPA reflects the state’s continued commitment to consumer protection — particularly in an environment of increasing cybersecurity incidents, sophisticated data use practices, and rapid advancements in artificial intelligence.

The new rules focus on three major areas:

  1. Cybersecurity audits
  2. Privacy risk assessments
  3. Automated decision‑making technology requirements

They also include clarifications to existing regulations and updated thresholds that determine which businesses fall within scope. While not every organization will be immediately impacted, the timelines are structured such that businesses must begin preparing now.

The New Cybersecurity Audit Requirements

Who Must Conduct Cybersecurity Audits?

Cybersecurity audits under the new Article 9 regulations apply only to businesses whose processing of personal information creates a “significant risk” to consumers’ security. The definition of significant risk varies across regulatory contexts, but for audits, businesses are included if they:

  • Derive 50% or more of annual revenue from selling or sharing consumer personal information
    OR
  • Meet the CCPA’s revenue threshold (currently $26.625 million) and process:
    • Personal information of 250,000 or more California consumers or households annually
    • OR sensitive personal information of 50,000 or more consumers annually

As Millendorf and Wild emphasized, these thresholds are intentionally high. Many businesses subject to the CCPA will never meet them. But for organizations that do, the requirements are extensive.

The Phased Timeline: What Businesses Need to Know

The timing for compliance is one of the most complex aspects of the regulations.

If annual revenue exceeds $100 million in 2026:

  • Audit must cover calendar year 2027
  • Certification due April 1, 2028

If annual revenue is between $50 million and $100 million in 2027:

  • Audit must cover calendar year 2028
  • Certification due April 1, 2029

If annual revenue is under $50 million in 2028:

  • Audit must cover calendar year 2029
  • Certification due April 1, 2030

After the initial cycle, audits recur annually, with each covering the prior calendar year.

Because audits must reflect a full year of activity, companies effectively have three months to complete and submit them — a timeline both attorneys described as exceedingly tight.

What Must the Cybersecurity Audit Include?

The required audit elements go far beyond checking whether a business has basic cybersecurity policies. Instead, the regulations reflect a comprehensive, highly technical, evidence‑based review.

Key categories include:

  • Authentication protocols (including multi‑factor authentication)
  • Encryption at rest and in transit
  • Access controls and privilege management
  • Secure configuration settings
  • Internal and external vulnerability scanning
  • Penetration testing
  • Audit log management
  • Network monitoring (including EDR and NDR tools)
  • Secure coding practices
  • Data retention and minimization policies
  • Incident response plans

This approach reinforces a guiding principle: there is no privacy without security. Companies will need broad visibility across systems storing personal information — not just those used for narrowly defined privacy functions.

Internal vs. External Auditors 

Businesses may use internal auditors, but they must be:

  • Qualified
  • Objective
  • Independent
  • Not involved in day‑to‑day cybersecurity operations

As the podcast discussion noted, this requirement is difficult for many organizations. Internal cybersecurity staff typically manage the very systems being audited, creating unavoidable conflicts.

This means most businesses will rely on external cybersecurity auditors, who — due to the tight time window — are likely to be in exceptionally high demand. Companies should expect:

  • Higher audit fees
  • Scheduling bottlenecks
  • Longer lead times
  • Possible competition for qualified assessors

Millendorf and Wild compared the anticipated rush to tax season — except now organizations must complete both financial and cybersecurity audits at once.

Documentation Matters: Evidence, Not Promises

One of the most important takeaways from the conversation: auditors cannot rely on employee statements. They must verify compliance through evidence, meaning:

  • Written policies
  • Security logs
  • System configurations
  • Records of training
  • Change management documentation
  • Reports from scanning tools
  • Incident response data

For companies with strong but undocumented cybersecurity practices, this may be the most significant lift. Without documentation, auditors cannot certify compliance.

Conclusion

The newly adopted CCPA regulations represent one of the most consequential expansions of privacy governance in the United States. For many companies, compliance will require substantial operational changes — especially for those using automated technologies or processing data at scale.

But preparation is achievable with early planning, disciplined documentation, and the right partners. By understanding the requirements now and taking proactive steps, businesses can reduce risk, streamline compliance, and prepare confidently for the new regulatory environment.

Interested in staying ahead of the latest privacy developments?

Listen to Â鶹´«Ă˝â€™s Cybersecurity & Data Privacy Group podcast series, where our attorneys break down evolving regulations, emerging risks, and what they mean for your business.

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]]> Semiconductors Podcast – Data Centers: The Role of AI and Semiconductors in Transforming an Industry /p/102ly7j/semiconductors-podcast-data-centers-the-role-of-ai-and-semiconductors-in-trans/ Thu, 18 Dec 2025 16:17:39 +0000 /p/102ly7j/data-centers-the-role-of-ai-and-semiconductors-in-transforming-an-industry/ Data Centers: The Role of AI and Semiconductors in Transforming an Industry   Key Takeaways AI is driving unprecedented demand for data...

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]]> Data Centers: The Role of AI and Semiconductors in Transforming an Industry

 

Key Takeaways

  • AI is driving unprecedented demand for data centers, with global spending projected at USD 1.4 trillion.
  • Legal complexity is increasing, spanning real estate, construction, finance, technology transactions, and energy contracts.
  • Power availability is the biggest constraint, prompting innovation in renewable integration and storage solutions.
  • Rollout of new GPUs, improvements in semiconductors at the edge, and improvements in data center infrastructure technology, will drive further improvements in AI technology.
  • Major tech and semiconductor players are investing heavily, signaling confidence in long term growth.
  • Data centers are becoming the new utilities, forming the backbone of the AI driven economy.

Introduction

The rise of artificial intelligence has triggered a tectonic shift in the technology landscape, with a transformed data center industry providing the critical infrastructure layer that makes modern AI possible.  The industry transformation was sparked by two catalysts: breakthroughs in AI models and algorithms, and advances in semiconductors that make those models economically and technically viable at scale. 

From Fiber Networks to AI Hyperscale: A Brief History

Data centers have come a long way since the dotcom era. Initially focused on co-location and basic cloud infrastructure, the industry matured through the rise of hyperscalers like AWS, Microsoft, and Google. For years, growth was steady and predictable, centered on efficiency and sustainability. Then came the release of GPT 3.5 and ChatGPT, a seismic event that redefined computing needs overnight.

Today, the anticipated global spending on new data centers exceeds USD 1.4 trillion, a figure that dwarfs previous investment levels. This surge reflects the insatiable demand for high performance computing, enabled by high performance semiconductors, which requires entirely new configurations, cooling technologies, and power solutions.

Legal Complexities Behind the Curtain

Building and operating a data center is no longer a simple real estate transaction. These projects resemble micro M&A deals, involving a multidisciplinary team of legal experts. Key areas include:

  • Site Acquisition and Zoning: Real estate diligence, environmental compliance, and negotiations with local governments for tax incentives.
  • Construction and Engineering: Highly specialized build to suit facilities with advanced cooling and security systems.
  • Project Finance: Structuring investments and securing lending for billion dollar builds.
  • Technology Transactions: Carrier agreements, cross connects, and service level agreements governing uptime, power availability, and security.
  • Energy Contracts: Power purchase agreements with utilities and renewable providers, plus strategies for redundancy and sustainability.

The Power Problem: A Race Against Time

Power availability has become a defining constraint in data center development. Traditional grid connections remain common, but operators are increasingly exploring behind the meter solutions pairing facilities with solar farms, wind farms, and battery arrays. While nuclear technology garners attention, it remains years away from practical deployment.

The challenge is urgent: industry leaders anticipate a power cliff by 2027 to 2028, driving accelerated investment today.

AI and the New Compute Economy

AI workloads demand GPU based high density configurations, a stark departure from traditional CPU driven models. This shift has elevated former crypto miners already adept at liquid cooling and high-density clusters into unexpected leaders in the space.

Backed by the major semiconductor companies and other major players with deep pockets, this growth is fundamentally different from growth in the dotcom era.

 

Looking Ahead: Utilities of the Future

As computing demand skyrockets, data centers are emerging as the new utilities, critical infrastructure underpinning commerce and daily life. For semiconductor companies, this trend promises sustained growth, not only in data center chips but also in edge computing solutions.

Conclusion

The data center boom is more than an industry trend; it is a structural shift in how technology is delivered and consumed. For businesses, investors, and legal professionals, understanding this ecosystem is essential. Those who adapt quickly will help shape the future of AI.

 

 

Get more on the rapidly evolving world of data centers. Artificial intelligence is driving explosive growth and a surge in data center development. But big questions remain: What will an AI market correction look like? Can expansion keep pace with demand? And how will we secure the energy to power it? 

 

The Â鶹´«Ă˝ 2026 Data Center Development Report launches in January. Sign up now to get it delivered to your inbox.

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]]> AI Fair Use Decisions Bode Well for the Semiconductor Industry /p/102l0r2/ai-fair-use-decisions-bode-well-for-the-semiconductor-industry/ Mon, 25 Aug 2025 14:48:09 +0000 /p/102l0r2/ai-fair-use-decisions-bode-well-for-the-semiconductor-industry/ Summary judgment was recently granted for defendants based on fair use in two copyright infringement actions challenging the training of...

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]]> Summary judgment was recently granted for defendants based on fair use in two copyright infringement actions challenging the training of large language models (LLMs), one against Meta relating to its Llama LLMs,[1] and the other against Anthropic relating to its Claude LLMs.[2] The decisions bode well for the continued development of the generative AI industry, and therefore for the semiconductor industry, which is building out the infrastructure and higher layers of the generative AI tech stack.

In both cases, authors challenged the unauthorized downloading of their copyrighted works and their copying and use for training LLMs, and in Anthropic’s case, also the creation of a general-purpose digital library. Neither case involved challenges to the LLMs’ outputs.       

LLM Training

Training of an LLM involves the use of an enormous number of texts (including, for Claude and Llama, millions of books), which are copied in a multistep process that starts with each text being translated into short sequences of words and punctuation called “tokens,” which are the units on which training is performed. Training then involves the use of a statistical language model to learn patterns from these “tokenized” texts, including predicting the next word in a sequence, given the context from the preceding words, and then repeating the process.  The prediction is compared to the original, and the statistical model is accordingly adjusted so that next time it is more likely to predict correctly.  The statistical language model operates through the use of “vectors,” which are a sort of multi-dimensional matrix that captures the relatedness (called “weights”) of different words, grammar patterns, or story themes. At a general level, the Anthropic court described training as using the authors’ works to “iteratively map statistical relationships between every text-fragment and every sequence of text-fragments so that a completed LLM could receive new text inputs and return new text outputs as if it were a human reading prompts and writing responses.”  

Copyright Law and Fair Use

The policy behind the 1976 Copyright Act is to promote the progress of science and the arts through encouraging authors to create new creative works. Section 106 of the 1976 Copyright Act grants a copyright holder exclusivity with respect to enumerated actions, such as reproduction, preparation of derivative works, and distribution of copies. It does not grant a monopoly over all uses of the copyrighted work. Section 107 of the Copyright Act provides the affirmative defense of “fair use” for acts otherwise infringing the exclusive rights of a copyright holder, the test for which includes the following four factors: 

(1)    The purpose and character of the use, including whether such use is of a commercial nature or is for nonprofit educational purposes;

(2)    The nature of the copyrighted work;

(3)    The amount and substantiality of the portion used in relation to the copyrighted work as a whole; and

(4)    The effect of the use upon the potential market for or value of the copyrighted work.

Fair use is an affirmative defense that is applied holistically and has been described as an “equitable rule of reason”.[3] Courts have typically viewed the first and fourth factors as the most significant, with the fourth particularly important.   

The Anthropic Decision

The materials used by Anthropic included millions of books downloaded from pirated sources, and millions of print books that Anthropic purchased and scanned into digital form with machine-readable text. This was both for the purposes of creating a general research library for potential future use and for training Claude.  

Judge Alsup bifurcated his analysis into the use of books for training the LLM and the use of books to build a central library. He held that both the use for training and the digitization of purchased books to build a central library were fair use, but the use of pirated books to build a central library was not. He made clear that summary judgment did not extend to future copies made from the central library that were not used for training LLMs.   

With respect to the first factor, Judge Alsup held that the purpose and character of using the copyrighted works to train LLMs to generate new text was “quintessentially transformative.” The use was not simply to memorize and replicate the works it trained on, but “like a reader aspiring to be a writer” to learn from them and create something different. Accordingly, the first factor weighed in favor of fair use for the training copies.

With regard to copies used to build the central library, Judge Alsup bifurcated his analysis into the pirated copies and those Anthropic purchased in print and then digitally converted. He held that the latter group, which facilitated storage and searchability and did not result in new copies being shared with third parties, was transformative. On the other hand, Judge Alsup held that the use of the pirated works was “inherently, irredeemably infringing,” and their use to build a research library was not transformative. Judge Alsup distinguished other decisions, including where copies were unavailable for purchase or loan, copies were transformed into a significantly different form, or the defendant already possessed authorized copies. 

Judge Alsup held that the second factor — the nature of the copyrighted work — weighed against fair use because the works at issue involved expressive content, which were entitled to greater protection under copyright laws than factual works.  

Judge Alsup held that the third factor — the amount and substantiality of the work used — involved an assessment of whether the amount of copyright-protected material was reasonable in relation to the purpose for copying it. The key to the analysis was not how much text was copied, but how much was made accessible to the public. With respect to training, Judge Alsup held that while the entire books were used, there was no allegation that the material was made available to the public as output. He found that the third factor favored fair use for training because of the large amount of data that Anthropic reasonably needed for training its LLMs. With respect to building a central library, Judge Alsup held that the third factor favored fair use for the purchased copies, but against fair use for the pirated copies, given that Anthropic had no right to hold them at all.

Judge Alsup held that the fourth factor — market dilution — also favored fair use regarding training LLMs. He held that the fourth factor focuses on the extent to which the challenged use acts as an actual or potential market substitution for the copyrighted work. Judge Alsup noted that the authors conceded that the LLMs did not produce exact copies or infringing knockoffs of the authors’ works. Instead, the authors argued that the LLMs would “result in an explosion of works competing with their works.” Judge Alsup analogized the plaintiffs’ argument to a complaint that “training schoolchildren to write well” would also result in an explosion of competing works and held that this “is not the kind of competitive or creative displacement that concerns the Copyright Act. The Act seeks to advance original works of authorship, not to protect authors against competition” (citing Sega Enterprises Ltd. V. Accolade, Inc., 977 F.2d 1510, 1523-24 (9th Cir. 1992)).  Judge Alsup also rejected the plaintiffs’ arguments that training LLMs would harm an emerging market for licensing work to train LLMs, holding that the Copyright Act does not entitle plaintiffs to exploit such a market that could develop.  

Judge Alsup held that the fourth factor was neutral with respect to the purchased library copies that were converted to digital form and pointed against fair use for the pirated works, given that pirated copies “plainly displaced demand” for the plaintiffs’ books. 

Judge Alsup, weighing all the factors, thus granted Anthropic’s motion for summary judgment on the issue of fair use with respect to the training copies and books legitimately purchased to build a digital library, but denied summary judgment for Anthropic on the pirated copies, reserving the decision for trial.

The Meta Decision

The Meta decision involved an action by 13 authors against Meta for downloading their works from so-called “shadow libraries” of pirated works and using them to train Meta’s LLM. A key difference between the two decisions was the primary weight that Judge Chhabria gave to the fourth factor and his views, expressed in a lengthy dictum, that in many cases, LLM conduct may fail the fair use test because LLMs often “dramatically undermine the market” for the materials on which they train. By way of example, Judge Chhabria speculated that an LLM capable of producing endless books about how to take care of a garden could greatly diminish the market for human-authored garden books. He indicated that Judge Alsop’s Anthropic decision was overly focused on the transformative nature of generative AI (the first factor in the fair use analysis), “while brushing aside concerns about the harm it can inflict on the market for the works it gets trained on” (the fourth factor).  Judge Chhabria, therefore, appeared to endorse a market dilution argument that, based on Sega, Judge Alsop flatly rejected. This theory was also recently supported by the U.S. Copyright Office in its May 2025 report “Copyright and Artificial Intelligence,” albeit acknowledging the “uncharted territory.” Judge Chhabria raised a number of questions that were implicated in a market dilution analysis, including whether Llama was capable of generating books, and if so, what type of books, what impact it would have on competition, and what the impact on the market for plaintiffs’ books would be where Llama could use their books for training versus being unable to use them. 

Both judges rejected another argument concerning the fourth factor that the unauthorized training of LLMs harmed the market for licensing books for LLM training.  Both courts held that this was not the type of market that the Copyright Act entitles the plaintiffs to exploit.  

Regarding the first factor, Judge Chhabria also ultimately agreed that the LLMs’ use was transformative, which is key to finding that the first factor favors fair use. But Judge Chhabria took a different approach from Judge Alsup regarding whether the analysis should focus on LLM training as the sole “use.”  Judge Chhabria rejected the plaintiffs’ attempt to bifurcate the analysis into Meta’s downloading of the books and use of the books for LLM training, stating that the downloading must be considered in light of the ultimate purpose of LLM training. Judge Alsup permitted a bifurcated analysis, albeit with respect to building a library, as opposed to simply downloading. Using this bifurcated approach, Judge Alsup held that the use of pirated works in the library weighed against fair use. Judge Chhabria, on the other hand, just considered the use of shadow libraries in connection with his unitary analysis and dismissed its significance. Judge Chhabria held that while it was relevant to the issue of bad faith, and could have been significant if Meta’s downloading had been a part of a peer-to-peer file sharing that had helped to perpetuate the shadow libraries, that was not the case here.  

What Are the Implications for the Future Development of LLMs?

There is clear recognition of the significant transformative nature of LLMs, which is an important factor favoring fair use. One weak spot for future decisions is Judge Chhabria’s endorsement of a market dilution test. But this endorsement should be considered in light of the associated questions he raised. Importantly, this is an inquiry heavily dependent on the nature of the market. It is a safe guess (for now) that most users of LLMs are not writing novels, so the “explosion” of competing, LLM-generated novels may end up being more of a theoretical concern. But for other works, for instance, news articles, biographies, and other nonfiction that can be quickly produced en masse by LLMs, Judge Chhabria suggested that there may be market dilution concerns. Judge Chhabria’s dictum also applies outside of text-based works. For instance, an LLM training on a specific songwriter’s catalogue could produce works diluting the market for that artist’s music or any genre uniquely associated with that artist, disincentivizing the artist and potentially others to continue making music in that space. Appropriate guardrails could limit the exposure to market dilution claims, should the market dilution theory gain judicial traction.

Another takeaway from the decisions is that the use of pirated works in connection with training should be avoided. In Anthropic, the fact that the books were pirated weighed heavily against fair use. And in Meta, Judge Chhabria also left open the possibility that use of pirated works could be relevant to a fair use analysis.

A third takeaway is that it was important in both decisions that the LLMs could not reproduce more than very short passages from the training materials. So LLMs should continue including guardrails that prevent memorization and regurgitation of extensive passages of training materials. For instance, Judge Chhabria’s decision emphasized how Llama was configured to return no more than 50 words from any given training source.

A related point is that the cases did not involve outputs. Consequently, the decisions do not address the situation where an LLM produces an unauthorized replica of a copyrighted work, whether through a generative process or memorization.

As indicated above, the decisions do not provide a compelling reason to put the brakes on the generative AI industry, nor do markets seem to have viewed them that way. The continued growth will drive further demand for the semiconductor products needed to support that growth. Moreover, even if copyright infringement were found in a future case, the risk of secondary liability for chipmakers seems trivial given available defenses, such as those based on the existence of non-infringing uses.  

[1] Kadrey v. Meta Platforms, Inc., No. 3:23-cv-03417-VC (N.D. Cal. June 25, 2025)

[2] Bartz v. Anthropic PBC, No. 3:24-cv-05417-WHA (N.D. Cal. June 23, 2025)  

[3] Google LLC v. Oracle Am., Inc., 593 U.S. 1, 19 (2021).

 

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]]> Episode 11: AI for Good with Heejae Lim of TalkingPoints /insights/publications/2024/02/episode-11-ai-good-heejae-lim-talkingpoints/ Wed, 07 Feb 2024 15:09:34 +0000 /?p=105852 The post Episode 11: AI for Good with Heejae Lim of TalkingPoints appeared first on Â鶹´«Ă˝.

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]]> Episode 10: Building the Decarbonized Future with Chris Rezendes of Context Labs /insights/publications/2023/12/episode-10-decarbonized-future-chris-rezendes-context-labs/ Wed, 13 Dec 2023 14:39:49 +0000 The post Episode 10: Building the Decarbonized Future with Chris Rezendes of Context Labs appeared first on Â鶹´«Ă˝.

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]]> Episode 9: Frontiers of AI with Aaron Erickson of NVIDIA /insights/publications/2023/11/episode-9-frontiers-ai-aaron-erickson-nvidia/ /insights/publications/2023/11/episode-9-frontiers-ai-aaron-erickson-nvidia/#respond Thu, 09 Nov 2023 20:45:15 +0000 The post Episode 9: Frontiers of AI with Aaron Erickson of NVIDIA appeared first on Â鶹´«Ă˝.

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]]> /insights/publications/2023/11/episode-9-frontiers-ai-aaron-erickson-nvidia/feed/ 0 Episode 8: Building The Founder’s Brand with Parna Sarkar-Basu of Brand and Buzz Marketing /insights/publications/2023/08/episode-8-building-founder-brand-parna-sarkar-basu/ Wed, 16 Aug 2023 05:00:00 +0000 https://foley.com/insights/publications/2023/08/episode-8-building-founder-brand-parna-sarkar-basu/ The post Episode 8: Building The Founder’s Brand with Parna Sarkar-Basu of Brand and Buzz Marketing appeared first on Â鶹´«Ă˝.

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