IP

As generative AI becomes increasingly accessible and pervasive, many companies are experimenting with these tools to draft full legal agreements. For start-ups and businesses with limited resources, the appeal is obvious: AI can produce contracts quickly and at a fraction of the cost of traditional legal drafting. What once may have required days of attorney time and high legal fees can now theoretically be generated in minutes with a simple prompt.

While this efficiency is attractive, it comes with significant risks. AI-generated agreements frequently contain significant issues that ultimately make them unusable. Unlike an experienced attorney, AI lacks legal judgment, contextual understanding, and knowledge of specific client needs. It can generate provisions that appear polished on the surface but collapse under scrutiny.

One recurring issue is the inclusion of multiple conflicting provisions. For example, a recent AI-generated supply agreement included three different payment mechanisms for the same transaction: upfront payment, milestone-based installments, and payment upon delivery after invoicing. With three competing payment obligations for a single transaction, the contract leaves the payor guessing and sets the stage for potential disputes.

Another problem is language that reads like legal boilerplate but is, in fact, incoherent or legally meaningless. AI may generate complex wording that mimics the tone of a lawyer’s drafting, but it lacks the precision required in contract language. This can make agreements unnecessarily confusing and difficult to interpret. For example, a recent AI-generated commercial contract included the following dispute resolution provision:

“Any dispute, controversy, or claim arising out of or relating to this Agreement, or the breach, termination, or invalidity thereof, shall be finally settled by arbitration in São Paulo, Brazil, in accordance with the rules of the American Chamber of Commerce, Canadian Chamber of Commerce, or other mutually agreed renowned Chamber of Arbitrations.”

This dispute resolution clause has several problems. First, it does not identify the exact set of rules governing arbitration proceedings between the parties. More importantly, there are no such rules of the “American Chamber of Commerce” or the “Canadian Chamber of Commerce” and it is unclear what would be considered a “renowned Chamber of Arbitrations.” Finally, it is highly unlikely that parties resolving a dispute in Brazil would choose to apply American or Canadian-based arbitration rules. An attorney with even minimal experience in drafting arbitration provisions would not make these errors.

The underlying issue is that AI generates text based on patterns, not legal reasoning. It predicts what “sounds” like a contract without understanding enforceability, legal doctrine, or commercial practicality. Given the risks, companies should treat AI-generated contracts with caution. As such, attorney review remains essential to make sure agreements are clear, consistent, and tailored to the business’ needs.

Several U.S. treaty partner jurisdictions have recently become aggressive in extending their taxation rights to cross-border acquisition transactions and the movement of assets, such as intellectual property. As a result, multinational companies should consider seeking advance unilateral or bilateral advance pricing agreements (also referred to as “APAs”) to resolve potential disagreements with foreign tax authorities and avoid lengthy and expansive audits and litigation proceedings.

What are “APAs”?

Commonly, following an acquisition of a foreign company by a U.S.-based multinational company, certain IP assets of the foreign target may need to be integrated with such company’s other operating assets to better align the ownership of IP assets with such company group’s operating structure, functions, other assets, and risks. Such an alignment of assets could involve the license, sale, or transfer of IP to the U.S. parent company or to another member of the multinational company group located in a jurisdiction different than that of the target. A cross-border transfer of assets could result in income recognition based on the value of the assets being transferred.

An APA is an agreement between a multinational company and a taxing authority or authorities regarding the transfer pricing methodology, valuation, and pricing of assets and certain transactions. A bilateral or multilateral APA (which involves the multinational company and two or several tax authorities, respectively) provides a non-adversarial alternative to resolving potential cross-border transfer pricing disputes, among many other benefits. Furthermore, the IRS is expected to be more likely to support valuation methodologies and adjustments that are based on acceptable international tax principles and valuation methodologies. The IRS’s support of a company’s valuation methodology in an APA process could be helpful in a dispute or litigation with a treaty partner jurisdiction in support of a company’s position. As a result, a bilateral or multilateral APA process provides an opportunity to set the stage and level the playing field with the treaty partner country(ies). A bilateral or multilateral APA may be a viable alternative to consider for both treaty partners (including Canada, Germany, India, Israel, Japan, Korea, Switzerland, and others) and other jurisdictions.

As a primary benefit, a bilateral or multilateral APA could eliminate the need for uncertain tax position reporting and provide for penalty protection. It would also help parties avoid repetitive tax and transfer pricing audits; limit tax authorities’ ability to change transfer prices retroactively; allow parties to manage transfer pricing real-time (rather than responding to audits years later); and mitigate the risk, cost, and burden of an audit or potentially harmful tax litigation in the U.S. and in the treaty partner jurisdiction. Other benefits may include the suspension of current tax audits or assessments relating to the transactions covered by the bilateral or multilateral APA negotiations until the APA process has been concluded, which could take several years.

For instance, recently at least one tax jurisdiction has gone so far as to argue on several occasions that the value of a target company’s IP could be higher than the entire purchase price paid to acquire such target company. The argument has been that, surely the buyer has taken into account the tax cost associated with moving the IP following the acquisition and, thus, discounted the purchase price paid for the target company and all of its assets, including its IP. Such a result, in the absence of an APA, can have a significant effect on deal structure, outcome, and consideration if not addressed in advance.

While the taxing authorities and the multinational company are not obligated to reach an agreement, they are generally required to try to reach a mutual agreement pursuant to the applicable income tax treaty, including relevant provisions for the relief from double taxation and mutual agreement procedure.

In a welcome development in the U.S., the IRS released additional guidelines on the IRS’s Advance Pricing and Mutual Agreement Program (APMA), a program that looks to identify multinational companies and matters early in the process that are more likely to successfully reach an APA resolution based on the facts at issue. Multinational companies can contact APMA for a pre-submission review and receive a preliminary opinion on whether to proceed with the APA process within just a few weeks of submitting a pre-filing memo and providing additionally requested information.

APMA considers a number of factors, including: the significance of the transaction; the probability that transfer pricing compliance will be significantly enhanced by engaging with the treaty partner; the scope, materiality, and complexity of the company group-covered transactions in the U.S.; whether there is an actual or potential transfer pricing dispute that would be most efficiently resolved through a bilateral or multilateral APA based on the APMA’s experience; country-specific strategy considerations; and the input of the treaty jurisdiction regarding the APA.

In addition to transactions involving IP assets, a bilateral or multilateral APA can cover the provision of services by a non-U.S. entity, the provision of services by a U.S. entity, sale of tangible property into and from the U.S., use of intangible property by a U.S. entity and by a non-U.S. entity, and other transactions. In the majority of “APAs”, the covered transactions involve numerous business functions and risks.

Courts are writing their own rules about generative AI, and in patent cases those rules differ sharply from judge to judge. This survey, current as of September 8, 2026, catalogs the generative-AI requirements in the venues where most patent infringement suits land: the Eastern and Western Districts of Texas, the Northern and Central Districts of California, the Northern District of Illinois, the District of New Jersey, and the District of Delaware and the U.S. International Trade Commission, where no AI-specific rules were identified. Only the Eastern District of Texas has a court-wide rule, making every litigant responsible for verifying AI-assisted filings. Elsewhere the obligations come from individual judges’ standing orders and vary widely, from restating the existing duty to verify what you sign to requiring a separate certificate naming the AI tool, confirmation that a human checked every citation, records of the prompts used, or disclosure of AI use in billing. Penalties include US$500 per violation and having the filing struck.

For private companies backed by venture capital investors, acquisition is frequently the most likely path to liquidity. Founders are often laser-focused on product development, market expansion, and fundraising, without devoting the same early-stage discipline to ensuring the company is well-positioned for a future exit via a merger or acquisition.

M&A preparedness is not a late-stage exercise, but an operational strategy to position your company as an attractive, high-value target to potential acquirors.

Corporate Governance

Some of the most common obstacles to efficient M&A processes stem from issues related to corporate governance. Complex capitalization tables, unclear chain of equity ownership, and unresolved governance issues can create transaction delay and, depending on the structure of the transaction, loss of leverage.

Companies should consider focusing on three key areas of corporate governance to be prepared for future M&A processes: capitalization table discipline, stockholder rights, and board and stockholder alignment.

Capitalization Table Discipline

Maintain clear documentation of all equity issuances with proper board and stockholder approvals; confirm board minutes are complete, approved by the board, and signed; verify that 83(b) elections have been timely filed with respect to restricted stock grants to founders and early employees; and ensure 409A valuations are updated following major events that may impact valuation (such as a financing) and, absent such events, at least annually.

Stockholder Rights

Ensure all stockholders have signed the relevant stockholder agreements and that the company’s management team understands the protective provisions embedded within such agreements; similarly, ensure that the company’s management team is familiar with relevant provisions of any investor side-letters (think drag-along mechanics, rights of first refusal, and co-sale rights).

Board and Stockholder Alignment

Understand what approvals are required to approve a sale or merger of the company and whether any investor has blocking rights.

Contracting Discipline

Material contracts, such as key vendor and customer agreements, collaboration agreements, and licensing arrangements, are some of the first diligence requests in an M&A process. These contracts often contain assignment or change-of-control provisions that can require third-party consent, accelerate payment obligations, or trigger termination rights or other contractual rights that could significantly impact the trajectory of a deal. Accordingly, it is important for companies to maintain clear records of all material contracts, ensuring that all contracts are fully executed and include all attachments, exhibits, amendments, and restatements. Companies should track whether any material contracts have upcoming renewals or expiration dates. Additionally, tracking key provisions in such material contracts that may be triggered by an M&A (such as third-party consent requirements) will help streamline the M&A diligence and consent process.

Intellectual property is another value-driver for life sciences companies and technology companies, making it vital for companies to have documentation that clearly delineates intellectual property ownership. Companies should verify that all employees and contractors have signed Proprietary Information and Inventions Assignment Agreements (PIIAAs), review consulting agreements to confirm that intellectual property created by consultants/contractors has been validly assigned to the company, and obtain confirmatory assignments from founders and early contributors, if needed, and at the appropriate time. For companies with affiliated entities, confirm that the company’s core intellectual property assets sit within the target entity and not within any affiliated entities.

Being proactive can save time and expense during the M&A diligence process.

Regulatory Compliance

Depending on industry and geography, regulatory risk can become a gating diligence issue. Companies should identify areas of risk and preemptively resolve any outstanding compliance risks (e.g., data integrity, marketing, industry-specific licensing, etc.). In particular, life sciences companies should consider pursuing regulatory planning with the assistance of healthcare and/or FDA counsel (as needed) to ensure, among other things, that regulatory filings, communications, and approvals are complete and accessible.

Deal Team Preparation

Once the company has decided to start a sale process, identify at the outset who will be part of the core deal team, which will typically consist of a select number of employees and outside advisors. Members of executive management and other key internal personnel with specialized knowledge about the company’s corporate governance, labor and employment practices, employee benefits structure, assets (IP, real estate, etc.), litigation exposure, and regulatory compliance are typically included within the core deal team. Further, at the appropriate time, companies should engage outside advisors, such as outside legal counsel, financial/tax advisors, and investment bankers, all of whom can help quarterback the transaction and efficiently drive the deal process.

After the deal team is in place, consider implementing deal confidentiality procedures to maintain the integrity of the sale process:

• assign code names to the project and company participants;
• limit working group size and access; and
• consider antitrust issues and the use of “clean team” agreements and data rooms.

Data Room Readiness

Prepared companies treat diligence readiness as an ongoing process and not an exercise triggered by a letter of intent or term sheet. First, select a virtual data room that provides strong security and activity tracking. Second, build the company’s data room with organizational discipline, using logical folder structures (corporate, IP, finance, regulatory, benefits, etc.) and uploading documents in a searchable, digital format with consistent document naming conventions. Lastly, in connection with building the data room, flag with the guidance of deal counsel any confidentiality concerns and access restrictions that need to be put in place. For example, are there any documents that need to be redacted or anonymized? Does the transaction present antitrust sensitivity requiring documents to be shared through a “clean room”?

In all, a well-maintained and categorically organized data room significantly accelerates a sale process and signals sophistication to potential acquirors.

The most successful exits rarely begin when a banker is engaged. Ideally, they begin years earlier with strategic and operational foresight. Companies that understand the value of M&A preparedness can preserve negotiation leverage and act more decisively when M&A opportunities arise. After all, engineering an exit is more than closing a deal — it is positioning the company so that the right deal finds you.

Whether a company is gearing up for an acquisition, a growth equity financing, or an IPO, a due diligence review will be an inevitable part of that transaction, and that review will test not only the current business but also the integrity of a company’s historical records. Readiness for that review is critical, as once a diligence process begins, gaps in corporate approvals, equity records, contract management, intellectual property ownership, and regulatory compliance can quickly become leverage for purchase price adjustments, closing conditions, and/or special indemnities. At best, diligence gaps can consume management attention at a time when a company has little bandwidth to spare. At worst, they can detract from a company’s credibility and can have a meaningful impact on deal speed and certainty. Most issues are fixable, but the available solutions often narrow after a deal is already on the table. This article provides an overview of actionable steps leadership at mid- to late-stage private companies can take to make transaction readiness an ongoing discipline rather than a pre-signing scramble.

Set Up and Maintain a Virtual Data Room

Rather than waiting until a letter of intent is signed, companies should stand up and maintain a virtual data room (VDR) early, using records they already keep locally, and treat it as a living repository of critical corporate documents. Management teams that prepare to address anticipated diligence focus areas and maintain organized virtual records early are better positioned when a process launches than teams that start flat-footed. Companies can get a head start by asking outside counsel for a standard due diligence request list, which serves as an organizational and gap-identification tool, as well as an organized table of contents for their VDR. This ensures that documents are comprehensive and indexed by categories prospective investors and acquirers will expect.

The VDR should contain current, fully executed, and dated documents together with all amendments, statements of work, and side letters. Superseded and terminated agreements should be archived, not deleted or mixed with operative versions. One small but time-saving step in setting up a VDR is using a consistent and intuitive naming convention as documents are uploaded, which will help not only management but also third-party reviewers quickly navigate the VDR’s contents. Once a diligence process begins, access should be staged and subject to tiered permissions, with additional controls for competitively sensitive information, compensation data, and litigation files; privileged materials should be withheld or handled through a process designed to preserve privilege. Particularly when a potential buyer is a competitor, or when the underlying material is subject to confidentiality restrictions that do not permit sharing with a potential acquirer or investor, counsel should advise prior to upload and contemplate redactions, clean-team arrangements, and restrictions on downloading or printing. When in doubt, leave it out; it is easier to pause early and evaluate permissions and other protections than to pull back a document after it has been shared.

A word of caution: prospective investors now run AI review tools that can scan an entire data room in minutes, and while that process can generate false positives, it can also magnify every internal inconsistency across the VDR, including in the cap table, contracts, and other materials. As a best practice, keeping the VDR updated quarterly helps identify issues early and positions the company and management to earn credibility from the moment that transaction diligence begins.

Maintain a Corporate Record Book and Organizational Documents

M&A buyers and growth equity investors will expect clean and current corporate governance records. This means prospective investors will review: current versions of the certificate of incorporation (including all amendments) and bylaws; board and stockholder minutes; and fully executed, dated written consents. An improperly compiled consent with a missing signature page or date can cost the company meaningful time and resources to track down or, worse, require corrective action to cure. Every material corporate action should tie out to a corresponding board and/or stockholder approval, including equity issuances, option grants, director and officer elections, and subsidiary formations.

Companies should also at least annually confirm good standing in their state of incorporation and in every jurisdiction in which they are qualified to do business. Outside counsel can obtain verbal good standing confirmations from third-party service providers, often for a nominal or no cost to the company. Good standing lapses can trigger fees, taxes, and penalties and, in many states, can bar the company from bringing suit in local courts until the lapse is cured, although a lapse does not typically invalidate contracts executed while the company was not in good standing. For an additional layer of caution, companies can consider ordering lien and litigation searches from third-party service providers in the same set of jurisdictions.

Ensure Vigilant Capitalization Table Hygiene

The company should expect buyers or investors to request a current copy of the capitalization table and, in the case of an equity financing, a pro forma cap table reflecting the completed round. Most cap table hygiene issues exist well before a contemplated transaction and surface in the diligence process. Common hiccups include unsigned option grants, undocumented stock issuances, unrecorded convertible note draws, and inconsistencies between vesting schedules and employment terms. Cap table accuracy is key: a company’s representations about its capitalization are often treated as fundamental representations, giving buyers or investors the ability to claim breach even for minor discrepancies. Moreover, a messy cap table can be perceived as poor ownership discipline by the company or its management.

With assistance from outside counsel, the company should reconcile the cap table against the stock ledger and equity grant documentation, ensuring that every stock and option issuance is supported by board resolutions, grant agreements, evidence of payment of the exercise or purchase price, and, if applicable, an approved, unexpired equity incentive plan. Each option grant should also be supported by a current 409A valuation that supports the board’s determination of the fair market value of the underlying shares.

Importantly, companies should develop a clear understanding of how antidilution provisions operate and how change-of-control acceleration clauses (single-trigger and double-trigger) may affect the equity/distribution waterfall in a transaction. Modeling these scenarios in advance allows management to communicate the deal economics clearly to all stockholders and avoids last-minute surprises that can derail negotiations.

Understand Key Provisions in Material Contracts

Counsel for buyers and investors will expect the opportunity to review each contract that is material to the business. These typically include: contracts with key customers and suppliers above certain revenue or expense thresholds; license agreements; leases; employment and severance agreements with key personnel; and other contracts that are important to the business. These contracts often contain change-of-control consent triggers, rights of first refusal, out-licensing restrictions, most favored nation provisions, exclusivity, non-solicit, non-compete, and other restrictive covenants. In certain circumstances, a counterparty may have a notice, consent, or termination right in connection with a transaction. Accordingly, with the help of outside counsel, a company should be generally aware of which key agreements contain those provisions and should have a plan for obtaining consents or providing timely notice in advance of entering into a transaction process. Seeking consent late in the process can give leverage to the counterparty, which can increase overall costs and decrease deal certainty.

Confirm Intellectual Property Ownership and Assignment of IP

Depending on the company’s core business, clean IP title is often a significant driver of the diligence process. One consideration that comes up time and again is whether every founder, employee, and contractor who contributed to the company’s IP portfolio has executed an invention assignment agreement that assigns all intellectual property rights to the company. It isn’t uncommon for advisors and early contributors in early-stage companies, often compensated in equity, to miss the assignment paperwork altogether, or to execute, but not date, the assignment. Any gaps in assignment should be addressed ahead of the buyer or investor diligence process, which can be done with the help of outside IP counsel. Companies should also routinely conduct an audit of open-source software usage to confirm compliance with applicable license terms.

Maintain Compliance with Industry-Specific Regulatory Requirements

Companies operating in regulated industries, such as healthcare, financial services, energy, and government contracting, should confirm that all material licenses, permits, and registrations are current and in good standing. Identifying regulatory approvals or notices that would be required in connection with a change-of-control or assignment of a license can avoid an additional layer of investor diligence caused when gaps are identified later in the deal negotiation process. Regulatory non-compliance discovered during diligence can significantly delay closing or reduce deal certainty.

As AI vendors become integral to business operations, their potential bankruptcy creates complex challenges under a Bankruptcy Code that has yet to fully adapt to AI technology. The first of a two-part series, this article focuses on intellectual property considerations: specifically, how companies that license AI tools or models can protect their continued access when a vendor enters bankruptcy. Among the key risks is a debtor’s ability to reject executory contracts, which could strip away the ongoing services that make a licensed AI tool usable, even where the bare license itself survives. Proactive contractual measures, including escrow arrangements and source code and deployment rights, can mitigate these risks before a vendor crisis occurs.

AI is reshaping drug discovery and development by accelerating research timelines, optimizing clinical strategies, and improving manufacturing efficiency, but adoption brings a complex web of legal considerations that life sciences companies must navigate. This article, published in Drug Discovery World, examines regulatory pathways for AI-assisted drug development, intellectual property ownership challenges, and data protection and privacy obligations arising from AI model training, and outlines practical steps organizations can take to capture the benefits of AI while managing regulatory, IP, and contractual risks.

IP will be a core focus for a biotech company and its investors through its entire lifecycle. While the company’s IP strategy can and should evolve over time, there are certain steps that an early-stage company can take at the outset to establish a strong foundation. This article identifies several key principles that, in addition to an intelligently crafted IP portfolio, will help set an emerging company up for future success.

Document Ownership

Too many deals — licenses, acquisitions, or otherwise — stumble due to questions about ownership of a company’s core inventions. Fortunately, a few simple documents can avoid most issues. Founders and other employees should have straightforward agreements assigning (using “present tense” assignment language) relevant inventions to the company. Companies should also understand whether key personnel have parallel or prior obligations to academic institutions, and be able to clearly explain those obligations, and ensure that CROs, consultants, and other service providers also appropriately assign IP generated for the company.

Document these arrangements when relationships begin — not several years later when an investor or potential acquirer asks for the paperwork and it may be logistically difficult or expensive to reconstruct a chain of title for IP.

License for the Long-Term

When a company is in its very early stages, there can often be a lot of time pressure to secure any third-party IP rights, such as a foundational IP license from a university. It is also important, however, to keep in mind that licenses are long-term instruments and the same document may be scrutinized several years later in a due diligence process when the company’s situation is very different. While perfection can often be the enemy of good, foresight does not have to be the enemy of speed. Negotiating the material license or collaboration with an eye towards future-proofing in a few key areas can even increase the value of the agreement to the company.

Patent then Publish

Once out of stealth, scientific publications, conference presentations, and other disclosures can be integral to a young biotech company’s success. They can also have irreversible consequences for patent protection if not timed properly — i.e., a publication prior to patent filing can preclude the issuance of the patent.

Early training for employees and a simple process can go a long way in mitigating this risk. A one- or two-hour IP 101 training from counsel can be very effective, and can also roll out a straightforward process to ensure that both technical and other personnel know to check with patent counsel before submitting a manuscript for publication or disclosing proprietary information in a pitch without a confidentiality agreement in place.

The rule of thumb is simple: when potentially patentable technology is about to leave the building, determine whether to file a patent application first.

Joint Ownership Does Not Simplify

Negotiating a transformative IP agreement can sometimes take considerably longer than initially thought, and it can often be tempting to take the negotiation path of least resistance. When it comes to IP ownership, this path equates to “joint ownership” of inventions. On its face, joint ownership sounds like a great solution. It is fair, equitable, and does not require a complex analysis of each party’s contributions to the invention. It is jointly owned, no matter what. The problem lies in operationalizing the joint ownership.

The rules governing jointly owned IP vary by jurisdiction and can create complications around licensing, patent prosecution, enforcement, and commercialization. Joint ownership can also become particularly cumbersome in future transactions — e.g., an acquirer is a competitor of a joint owner. While it may take a little extra negotiation, there are many ways to allocate ownership of IP other than just inventorship that can suit both parties, including ownership based on relation to background IP, subject matter, or type of IP.

Data Is a Key Asset

A biotech’s most valuable assets increasingly extend beyond patents and traditional know-how. Preclinical results, clinical data, biomarker datasets, manufacturing data, and datasets used to develop or validate computational tools may all have substantial strategic value. Data rights and restrictions should be given the same level of focus as the development of an IP strategy. Particular attention should be paid to distinctions among raw data, processed data, derived data, and analytical outputs — and to privacy, consent, or contractual restrictions that may constrain future uses.

Generative artificial intelligence (GenAI) tools are becoming increasingly utilized by employees in the workplace to enhance productivity. However, employees are frequently leveraging these tools without formal approval or oversight. While the benefits of GenAI tools may be substantial, use of GenAI may pose significant risks to organizations, including legal liabilities, data breaches, and reputational damage. This article explores certain key concerns associated with employee use of GenAI tools and essential components of an AI use policy.

Understanding the Risks

Data Privacy and Security

One of the most significant risks with the use of GenAI is that information entered into prompts or uploaded to common GenAI platforms may reveal to the AI tool sensitive or confidential company information or information about clients or customers, including information the company may have contractually agreed to keep confidential. Similar risks exist with inputs of personally identifiable information, such as email addresses or other identifiers. Typically, on publicly-available versions of such tools, data that is entered is used to train the AI or may otherwise be stored or used by the AI tool developer.

To mitigate risks of exposing potentially sensitive company data or potentially breaching customer confidentiality agreements, companies may want to consider purchasing enterprise versions of GenAI tools that operate in a closed-loop system, meaning the developer is not permitted to use or store inputs for purposes other than to provide the GenAI tool. Companies may also want to have an approved list of AI tools, which might include enterprise versions of common GenAI tools. Also helpful in mitigating risks is employee training and raising awareness of these risks.

Another significant and emerging risk is that GenAI tools are increasingly being used as a tool for cybercriminals, including through the orchestration of complex injection attacks that exploit the fact that these tools do not think, but rather, simply follow instructions. For example, attackers can embed instructions in publicly available links that, when uploaded to the GenAI tool, tell the tool to maliciously attack the host system and override instructions. Alternatively, the embedded instructions in public links could produce PDFs or other outputs that themselves contain malicious code. Companies should consult with their security team about the risks unique to their business and implement recommended controls if applicable. In addition, companies may want to consider working with external cybersecurity training providers to ensure their materials include coverage of AI tool injection attacks in employee training modules.

Intellectual Property Concerns

Companies should also seriously consider the significant intellectual property (IP) risks posed by employees’ use of GenAI tools. These IP risks arise from two factors: (1) the material used as “input” to train the AI models; and (2) the material generated by the AI model as “output”. AI models are frequently trained on vast datasets which include copyrighted material used without the author’s permission. Furthermore, use of such copyrighted material may cause the GenAI tool to generate outputs that replicate or closely resemble the copyrighted material, further exposing the user to potential copyright infringement claims.

Another IP risk associated with employees’ use of GenAI tools is the lack of IP protection for works and innovations created using GenAI. In the United States, works and innovations created solely by AI without human contribution are not eligible for copyright or patent protection. Without such protections, a company’s competitive advantage may fall into the public domain, where anyone can use it for free.

Use of GenAI may also compromise trade secret protection of a company’s proprietary information. If an employee inputs confidential proprietary information into GenAI tools without proper contractual protections, such information may be used to train the underlying AI models. As noted above, GenAI tools may generate outputs that replicate or closely resemble the inputs, in this case, the proprietary information, potentially exposing the trade secret to other users and compromising the company’s trade secret protection of the information.

Hallucinations and Bias

AI systems, particularly generative models, can produce outputs that appear plausible but are factually incorrect or nonsensical, a phenomenon known as “hallucinations.” These inaccuracies can lead to misguided business decisions, flawed reports, and erosion of trust in AI tools. For instance, an AI-generated report might cite non-existent studies or fabricate data, potentially leading to compliance issues or reputational damage.

Shadow AI Usage

Employees may use unauthorized AI tools (sometimes referred to as “shadow AI”) without the knowledge or approval of IT departments. This practice can result in data security breaches, compliance violations, and loss of control over sensitive information. For example, inputting confidential company data into unvetted AI platforms could inadvertently expose proprietary information. Companies should implement strict policies around shadow AI use and consider limiting access to popular AI tools on workplace computers.

Regulatory Compliance Challenges

The rapidly evolving landscape of AI regulations, such as the European Union’s AI Act, presents compliance challenges for organizations. Failure to adhere to these regulations can result in legal penalties and hindered innovation. Organizations must stay informed about regulatory changes and implement robust governance frameworks to ensure compliance.

DO’S & DON’TS:

Legal Compliance & Policy Design

DO:

• Establish a clear, tailored AI usage policy in collaboration with legal, IT, and compliance teams.
• Define “AI” in plain language, and specify which tools are approved.
• Include a mission or purpose statement to ground the policy in transparency, fairness, and innovation.
• Update the policy regularly to reflect evolving laws (e.g., EU AI Act, state legislation like Colorado’s).

DON’T:

• Don’t use one-size-fits-all policy templates. Each policy should reflect specific business risks and use cases.
• Don’t treat the AI policy as a one-time exercise. Legal exposure grows without active maintenance.

Data Security & Confidentiality

DO:

• Prohibit inputting sensitive, proprietary, or customer data into public AI tools unless specifically authorized.
• Include clear confidentiality provisions related to AI use in employee and vendor contracts.
• Conduct vendor due diligence to confirm AI platforms’ compliance with privacy laws and data handling standards.
• Consider using enterprise versions of AI tools to keep data inputs confidential.

DON’T:

• Don’t assume that AI tools won’t retain user input; review each tool’s terms of service and retention practices.
• Don’t allow shadow IT (e.g., unauthorized browser plugins, personal-use tools) without approval or audit trails.

Intellectual Property & Ownership

DO:

• Review AI vendor agreements to ensure the vendor has proper rights to use training data and provides adequate protections if infringement claims arise.
• Implement human review processes for AI-generated materials to identify potentially infringing content.
• Document human contributions in connection with the development of AI-assisted works and innovations.

DON’T:

• Don’t allow employees to generate customer-facing or public materials without review for potentially infringing content.
• Don’t use AI models trained on unlicensed data without understanding the risk of potential IP infringement claims.
• Don’t allow employees to input confidential proprietary information into AI tools without proper confidentiality and use restrictions.

Training, Governance, & Oversight

DO:

• Require regular employee training on the capabilities, limits, and risks of AI tools.
• Designate responsible roles (e.g., AI Compliance Lead, Tool Vetting Committee) to oversee implementation and approvals.
• Monitor AI tool usage, audit outputs periodically, and solicit user feedback to improve policies.

DON’T:

• Don’t deploy AI tools enterprise-wide without pilot testing, user education, and risk assessment.
• Don’t assume all departments or roles should have equal access to AI tools — access should be role-specific.

Ethical Use & Bias Prevention

DO:

• Embed fairness, transparency, and accountability principles into the company’s AI governance framework.
• Monitor AI systems for evidence of bias, particularly in HR, marketing, or customer interaction tools.
• Require disclosures when AI is used to create or assist in work product — internally or externally.

DON’T:

• Don’t use generative AI content without fact-checking — misleading outputs could carry reputational or legal costs.
• Don’t let AI output go unlabeled in sensitive contexts (e.g., client deliverables, compliance filings).

With sweeping cuts to federal research funding driving academic scientists in the life sciences toward entrepreneurship, there are practical steps for navigating this transition: adopting an entrepreneurial mindset that embraces risk and redefines success; leveraging university incubators, tech transfer offices, and alumni networks; broadening professional networks through industry events and mentorship; validating ideas through market research and minimum viable products; understanding regulatory pathways and engaging FDA-specialized counsel early; learning intellectual property fundamentals and working with IP attorneys to build a competitive strategy; developing a comprehensive business plan with milestones and financial projections; securing a diverse mix of funding from grants, angel investors, and venture capital; assembling a multidisciplinary team with complementary expertise; and launching pilot projects to demonstrate feasibility and build credibility with investors and partners.

Texas Governor Abbott signed House Bill 40, significantly expanding and refining the Texas Business Court just two years after its creation. Key changes include lowering the amount-in-controversy threshold from US$10 million to US$5 million across all case types, expanding substantive jurisdiction to cover intellectual property, trade secrets, and arbitration enforcement cases, clarifying that only business, commercial, or investment contracts may elect business court jurisdiction by agreement, authorizing transfer of pre-September 2024 cases by agreed motion, and tasking the Texas Supreme Court with establishing a jurisdictional framework and rulemaking procedures. The legislature also eliminated the sunset provision for unfunded court divisions, signaling the business court is a permanent fixture in the Texas legal system.

Although AI-related patent filings have surged dramatically over the past two decades, patent litigation involving AI technologies has not yet kept pace, a trend the article suggests may mirror the delayed wave of smartphone patent litigation that followed the technology’s commercial growth. In this piece for Bloomberg Law, Sidley partner Alexis Cohen argues that AI companies should begin preparing now for increased future litigation by evaluating and strengthening their intellectual property protections, including patents and trade secrets, while also improving documentation, ownership records, employee agreements, and internal processes.

Reproduced with permission. Published May 21, 2026. Copyright 2026 Bloomberg Industry Group 800-372-1033. For further use, please visit: Bloomberg Industry Group copyright and usage guidelines.

England’s High Court has issued the UK’s first ruling in a copyright fight against an AI developer with an outcome that favors the AI industry. In Getty Images v. Stability AI, Getty (which licenses photos and video) alleged that Stability scraped millions of its images to train the Stable Diffusion image generator. During trial Getty dropped its main copyright claim because it could not show the training actually happened in the UK. Copyright is territorial, so no act in the UK means no UK infringement.

That left a narrower question: whether importing the already-trained model into the UK made it an “infringing copy” under the Copyright, Designs and Patents Act 1988. The court said no. A model’s weights are just numbers derived from statistics; they do not store or contain the underlying images, so supplying the model is not secondary infringement. Getty won only on a historic and limited trademark point about its marks appearing in outputs. The decision settles little about whether UK-based training would infringe, and Getty may appeal.

On June 22, 2026, the White House issued two executive orders on quantum technology: “Ushering in the Next Frontier of Quantum Innovation” and “Securing the Nation Against Advanced Cryptographic Attacks.” Quantum computers can solve certain problems far faster than ordinary computers, which opens up new commercial possibilities but also threatens the encryption that protects most online communication and stored data today. The orders push federal agencies past pure research toward deployment, commercialization, workforce building, and national security uses.