AI Insights
Client Beware: The Utilization of Artificial Intelligence Platforms and the Potential Waiver of Attorney-Client Privilege | IR Global

[author: Ismail Amin]
The rapid evolution of digital technologies has ushered in a new era for the legal profession—one characterized by both unprecedented promise and intricate new hazards. As practitioners and clients alike become more reliant on artificial intelligence, questions abound regarding the traditional boundaries of confidentiality and privilege that have long served as the bedrock of attorney-client relationships.
The accelerated adoption of machine learning (ML), large language models (LLM) and artificial intelligence (AI) has engendered significant transformation within the legal profession, offering new efficiencies but also introducing complex challenges with respect to confidentiality obligations and evidentiary attorney-client privileges. Among the most pressing of these is the effect of AI platforms on the sanctity of attorney-client communications and the attendant risk of inadvertently waiving the attorney-client privilege by clients.
We analyze the ramifications of clients’ engagement with AI platforms—including generative AI tools, cloud-based legal assistants, and related digital services—on privileged communications. It further evaluates pertinent legal doctrines and proposes measures that legal practitioners may adopt to preserve the integrity of confidential counsel.
I.Attorney-Client Privilege: Foundational Principles
The attorney-client privilege constitutes a sacrosanct cornerstone of the legal system, shielding the confidentiality of exchanges between attorneys and their clients. For purposes of this writing, we examine the privilege in California, Nevada, Texas and New York. This privilege is intended to facilitate candid and comprehensive communication, thereby enabling clients to seek legal guidance without apprehension that their disclosures might be exploited against their interests.
In California, California Evidence Code § 954 establishes the attorney-client privilege, allowing clients to refuse disclosure of confidential communications with their lawyers. The privilege can be claimed by the client, an authorized person, or the lawyer, unless no holder of the privilege exists Cal Evid Code § 954. Cal Evid Code § 912 addresses waiver of the privilege, stating it is waived if the holder voluntarily discloses a significant part of the communication, with exceptions for joint holders and privileged disclosures. Cal Evid Code § 917 presumes communications made in confidence during the attorney-client relationship are privileged unless proven otherwise.
In Nevada, the attorney-client privilege is primarily addressed in Nev. Rev. Stat. Ann. § 49.015, which establishes that no person has a privilege to refuse to disclose matters or prevent others from disclosing unless otherwise provided by law. In Texas, Tex. Evid. R. 503 outlines the attorney-client privilege, protecting confidential communications made to facilitate legal services, with exceptions for furtherance of crime or fraud Tex. Evid. R. 503. In New York, NY CLS CPLR § 4503 clarifies that beneficiaries of an estate are not considered clients of the attorney representing the personal representative, and fiduciary relationships do not waive the privilege NY CLS CPLR § 4503. NY CLS Rules Prof Conduct R 1.6 defines confidential information and restricts its disclosure without client consent, with exceptions for preventing harm or complying with legal obligations NY CLS Rules Prof Conduct R 1.6.
Should a privileged communication be disclosed to a third party, the privilege may be considered waived, resulting in the communication being susceptible to discovery during litigation or governmental inquiry. The attorney-client privilege is fundamentally designed to protect confidential communications between a client and their attorney, fostering open and honest discussions. It is rooted in public policy and aims to ensure effective legal representation. However, the privilege is not absolute and is subject to exceptions, such as when the communication involves furtherance of a crime or fraud. Additionally, the privilege does not extend to certain elements of the attorney-client relationship, such as the fact of representation, dates of representation, or fee arrangements
The inclusion of third parties in communications generally voids the privilege unless the third party qualifies as a representative of the client under specific legal definitions. For instance, in Nevada, representatives are limited to those authorized to obtain legal services on behalf of the client. This principle underscores the importance of maintaining confidentiality within the bounds of the attorney-client relationship.
II.The Intersection of AI Platforms and Privilege
Clients increasingly employ AI platforms to facilitate document drafting, seek legal information, review contracts, and even interface with counsel. AI-powered chatbots and document review solutions deliver efficiency and insight, yet they also present notable risks to confidentiality and privilege.
Categories of AI Platforms and Associated Risks
- Generative AI (e.g., ChatGPT, Google Bard): Clients may submit privileged information to generative AI platforms seeking legal advice or clarification regarding legal matters.
- Cloud-Based Legal Assistants: These services store, process, or manage client documents utilizing AI algorithms.
- Third-Party E-Discovery Platforms: Platforms leveraging AI to review evidence or communications.
A common concern is that, when clients transmit confidential legal information through these platforms, such data may be accessible to individuals outside the attorney-client relationship. This can precipitate inadvertent disclosure and, consequently, waiver of privilege.
III.Do AI Platforms Constitute Third Parties?
A critical legal issue is whether engaging an AI platform constitutes disclosure to a third party. Attorney-client privilege generally applies only to confidential communications between the lawyer and client, or their necessary agents. If a client provides privileged details to a platform managed by an entity not directly engaged by the law firm for legal support, courts may determine that privilege has been forfeited.
Relevant considerations include:
- Terms of Service and Privacy Policies: Numerous AI platforms’ terms permit the provider to review, utilize, or share user inputs with affiliates, contractors, or for service improvement.
- Absence of Confidentiality Obligations: Unlike attorneys, most technology providers are not bound by professional obligations to protect privileged information.
- Jurisdictional Variances: Statutes concerning privilege and waiver differ across jurisdictions, complicating cross-border legal matters.
Illustrative Scenarios
- A client uploads a contract draft containing legal advice to a cloud-based AI editing tool; if the tool retains or analyzes content externally, this may constitute disclosure.
- A business proprietor utilizes a generative AI chatbot to summarize a confidential legal memorandum; if platform policies sanction the use of input for model training, privilege may be compromised.
- An in-house counsel employs an AI-driven e-discovery platform vetted and retained by the law firm under robust confidentiality agreements; in this instance, privilege may be preserved.
VI.Legal Precedent and Emerging Standards
The current body of precedent regarding the intersection of AI technology and privilege waivers is still developing and nascent at best. However, courts have consistently held that voluntary disclosure of confidential communications to third parties not essential to legal representation results in forfeiture of privilege. Some courts have recognized that storing privileged communications with a cloud service provider does not result in waivers if reasonable measures are taken to preserve confidentiality, such as encryption and comprehensive contractual protections.
Conversely, use of public or consumer-facing AI services—characterized by ambiguous or unfavorable privacy policies—poses heightened risks. AI platforms frequently analyze, aggregate, and retain user data for purposes beyond mere storage, thereby increasing the potential for waiver.
The concept of implied waiver of attorney-client privilege applies to the use of AI platforms in legal contexts when confidential communications are disclosed to third parties, including AI tools, in a manner that undermines the confidentiality essential to the privilege. Courts have consistently held that the attorney-client privilege is waived, either expressly or by implication, when privileged communications are disclosed to individuals or entities outside the scope of the privilege, such as AI platforms that are not designed to maintain confidentiality United States v. Under Seal (In re Grand Jury Subpoena), 341 F.3d 331, In re Lott, 424 F.3d 446.
Implied waiver occurs when a party’s conduct, such as using an AI platform, places privileged information at issue or makes it relevant to a claim or defense. For example, if an attorney uses an AI tool to process or analyze privileged communications and the tool’s design or operation involves sharing the data with third parties, this could be construed as a voluntary disclosure, thereby waiving the privilege. Courts have emphasized that fairness principles guide the application of implied waiver, particularly when the privilege is used as both a shield and a sword, or when the opposing party is denied access to information vital to their case Dion v. Nationwide Mut. Ins. Co., 185 F.R.D. 288, Patrick v. City of Chicago, 154 F. Supp. 3d 705, UUSI, LLC v. United States, 121 Fed. Cl. 218.
Additionally, the use of generative AI tools, which rely on external data sources to generate content, poses unique risks to attorney-client privilege. These tools may inadvertently expose confidential communications to third parties or fail to safeguard the confidentiality of the information, leading to a waiver of privilege. Attorneys must exercise caution and ensure that any AI platform used complies with confidentiality requirements to avoid breaching the privilege.
V.Best practices for Legal Professionals and Clients
Considering these risks, both attorneys and clients must exercise vigilance and adhere to best practices to safeguard privilege:
i.Diligent Selection of Technology Providers
It’s our job as counsel to rigorously assess technology providers, including AI solutions, ensuring the following:
- The existence of comprehensive confidentiality agreements
- Secure, encrypted data storage and processing protocols
- Commitments from providers not to access, utilize, or disclose client data for unrelated purposes
While the American Bar Association’s Formal Opinion 512 issued on July 29, 2024, provides guidance to lawyers, there remains a dearth of guidance to clients, with respect to the ramifications of uploading confidential communications or attorney-work product to AI or LLM platforms.
ii.Clear Communication with Clients
Legal professionals should educate clients about the risks associated with using consumer AI platforms to store, analyze, or transmit privileged information. Establish explicit guidelines identifying approved tools and those to be avoided.
Where use of AI tools is indispensable, disclose only the minimum necessary information and avoid submitting unredacted privileged communications to public or unvetted platforms.
Both attorneys and clients must diligently evaluate the implications of these technologies, recognizing that convenience should not supersede the imperative of protecting attorney-client privilege. Through careful selection of technology providers, client education, and robust internal governance, legal professionals can embrace innovation while upholding one of the profession’s most fundamental protections.
As courts and regulatory authorities continue to address the ramifications of AI within the legal arena, perpetual vigilance and adaptability will remain essential. The privilege resides with the client, yet its preservation in an era dominated by digital technology is a shared responsibility—one that requires both technological acumen and unwavering dedication to confidentiality.
AI Insights
Billionaire Steve Mandel Just Sold Microsoft Stock to Buy This Dominant Artificial Intelligence (AI) Stock Up Nearly 800% Over the Past Decade

Mandel increased his Amazon stake by a sizable amount.
Billionaire Steve Mandel and his hedge fund Lone Pine Capital have been a great one to follow for individual investors. Although some hedge funds have a poor record of underperforming the broader market, Mandel has substantially outperformed the market over the past three years. So, when he makes a move in his portfolio, investors should pay attention.
One thing Mandel did during Q2 was sell off some of his Microsoft shares. Although it wasn’t a massive move, the hedge fund reduced its position by about 5%. Then, Mandel used some of those funds to invest in another promising AI stock that has increased in value by nearly 800% over the past decade.
That stock? Amazon (AMZN -1.16%).
Image source: Getty Images.
AWS is the best reason to invest in Amazon right now
Amazon may not be the first company that comes to mind when you think about AI. Instead, it probably seems more like an e-commerce investment. While that sentiment is true for the consumer-facing portion, the reality is that a large chunk of Amazon’s profits comes from AI-related revenue streams.
The biggest is from Amazon Web Services (AWS), its cloud computing arm. Cloud computing firms are having a strong year, thanks to the massive demand generated by AI workloads. Because more companies can’t justify spending millions (or even billions) of dollars on a data center dedicated to training AI models, it’s far more reasonable to rent computing power from a firm that already has the capacity. That’s the idea behind cloud computing, and it has translated into strong growth for the business unit.
In Q2, AWS’s sales rose 17% to $30.9 billion. That’s strong growth, but it is a bit slower than its peers, Microsoft Azure and Google Cloud, which each grew revenue by more than 30% in Q2. However, AWS is much larger than both of these units, so it shouldn’t surprise investors that AWS is growing at a slower rate. AWS accounted for about 18% of Amazon’s total revenue in Q2, but it made up 53% of its operating profit. That’s because AWS has far superior margins compared to its commerce business units, making AWS a critical part of the Amazon investment thesis.
AWS is experiencing a significant boost from AI, making it a strong stock pick in this space.
But Microsoft is also a solid AI pick, so why is Mandel moving from Microsoft to Amazon?
Amazon’s stock looks more promising over the long term
From a valuation perspective, both companies trade at fairly expensive levels for their growth. However, they’re both priced about the same from a forward price-to-earnings (P/E) standpoint.
AMZN PE Ratio (Forward) data by YCharts
One thing Amazon has going for it that Microsoft doesn’t is the steady upward pressure on Amazon’s margins. Thanks to AWS and its advertising service business units being the fastest growing in Amazon, its margins are steadily improving. Although Amazon’s revenue growth rate appears to be somewhat slow, its operating income growth rate is actually quite rapid.
AMZN Revenue (Quarterly YoY Growth) data by YCharts
This trend still has years to unfold, which is a solid reason to transition from Microsoft to Amazon. I believe this will be a winning trade over the long term, as Amazon’s profits are expected to grow at a significantly faster rate than Microsoft’s, resulting in the stock outperforming its peer over the long term due to their similar valuations.
However, both stocks are still solid AI picks, and you can’t go wrong with either one.
Keithen Drury has positions in Amazon. The Motley Fool has positions in and recommends Amazon and Microsoft. The Motley Fool recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy.
AI Insights
How Artificial Intelligence is Redefining Business Process Automation

In today’s fast-paced economy, businesses are under constant pressure to operate more efficiently while reducing costs and improving customer experiences. Automation has long been a solution, but traditional methods such as simple scripts or rigid workflows often fall short in terms of adaptability and intelligence. This is where artificial intelligence comes into play. By partnering with an Artificial Intelligence Development Company, organizations can unlock new opportunities for smarter decision-making, streamlined operations, and scalable growth.
The growing interest in AI-driven automation reflects its role as a key enabler of digital transformation. Unlike conventional automation, AI systems can analyze large datasets, learn from patterns, and make predictions that allow businesses to stay competitive in increasingly dynamic markets.
Why AI for Business Process Automation
Traditional automation methods—such as scripts or Robotic Process Automation (RPA)—are useful for handling repetitive, rule-based tasks. However, they lack flexibility and cannot adapt to new or changing conditions without manual intervention. Artificial intelligence takes automation a step further by enabling systems to learn, adapt, and improve over time.
Through machine learning and advanced data analytics, AI can identify hidden patterns, make predictions, and support real-time decision-making. This makes it possible not only to automate processes but also to optimize them dynamically, driving more value than traditional approaches.
Key Areas of Application
Finance
AI enables faster and more secure payment processing, advanced transaction analysis, and fraud detection systems that continuously learn to recognize suspicious patterns.
Marketing and Sales
From demand forecasting and personalized customer experiences to intelligent chatbots, AI helps companies better understand their audience and increase conversion rates.
Manufacturing and Logistics
AI-powered tools streamline supply chain management, predict equipment maintenance needs, and reduce downtime, ensuring smoother operations and higher efficiency.
Human Resources (HR)
Recruitment processes are enhanced through automated resume screening, predictive analysis of employee retention, and data-driven insights for workforce planning.
Advantages of Implementation
The implementation of AI in business processes brings several clear advantages. One of the most significant is cost reduction: by automating repetitive, labor-intensive tasks, companies can cut manual rework and optimize resource allocation, which lowers operating expenses without sacrificing quality. AI also accelerates processes, as models are capable of handling large data streams in near real time.
This speed translates into faster approvals, more efficient routing, more accurate forecasting, and quicker customer responses, all of which shorten cycle times. Another key benefit is error minimization. With advanced pattern recognition and anomaly detection, AI reduces human error, ensures data consistency, and helps stabilize performance metrics across workflows.
Finally, AI offers unmatched flexibility and scalability. Systems continuously learn from new data, allowing them to adapt to changing rules and business volumes, while cloud-native deployments make it possible to scale operations seamlessly as demand increases.
Potential Challenges
Despite these benefits, businesses face certain challenges when adopting AI automation. Costs and timelines are among the first hurdles. The discovery phase, data preparation, model training, and integration require significant upfront investment, and success often depends on a phased delivery approach to manage risk.
Data quality is another critical factor. If the available data is incomplete, biased, or siloed, the outcomes will inevitably suffer. Strong governance, robust cleaning pipelines, and continuous monitoring are necessary to maintain reliable results. Ethical and legal considerations must also be addressed.
Organizations need to ensure that their AI solutions operate with transparency, fairness, and respect for privacy, while remaining fully compliant with regulatory standards and internal policies.
Conclusion
AI-driven automation is now a core lever of competitiveness, improving speed, accuracy, and margins while enabling adaptive operations. Start small, pick a high-impact process, validate with a pilot, then scale iteratively with robust data governance and clear ROI checkpoints.
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