SaaS Artificial Intelligence Lawyers Top Eight Legal Risks for 2025
Examining Legal Risks with SaaS Artificial Intelligence Lawyers in an Evolving Industry
The question is not whether your industry's business practices will face disruption from digital transformation; it is when. The fabric of your industry, whatever it may be, will be altered and redefined by the evolution of Software as a Service (Saas) solutions, particularly those that leverage artificial intelligence. If you are not developing SaaS AI solutions in-house, you will either cease to exist as a business or you will have to pay license fees to businesses that have developed such AI solutions and be exposed to legal risks if those services fail to meet compliance standards or experience breaches.
However, the path to building SaaS AI solutions is not without complications. In embracing their potential, you will encounter several complex legal risks when deploying your operational strategies.
In this article, we will examine the top eight legal risks and compliance challenges of 2025 related to deploying disruptive Saas AI solutions in traditional industries and provide actionable starting points for effectively navigating these challenges.
Our Top Eight Risks Are:
1. Multiple Jurisdiction Legal Compliance.
2. Intellectual Property Considerations.
3. Protecting Digital Content and Reputation.
4. Contractual Liability.
5. Bias and Discrimination.
6. Export Controls and Compliance.
7. Third-party Service Dependencies.
8. Liability for AI Decisions.
1. Multiple Jurisdiction Legal Compliance
1.1 Benefits of Multi-Jurisdiction Deployment
Deploying a SaaS AI solution across multiple jurisdictions offers several commercial benefits, including: (a) market expansion, which allows you to tap into new markets and increase revenue potential and brand visibility; (b) scalability, enabling easy adaptation to local market needs without heavy infrastructure investment; regulatory compliance, as features help you adhere to local laws and reduce legal risks; (c) cost efficiency, leading to lower operational costs by minimising on-premises hardware needs; (d) data localisation, which ensures compliance with data residency regulations, enhancing performance and reducing latency for local users; (e) a diverse talent pool, providing access to global talent that fosters innovation through diverse perspectives; improved customer experience, as tailored AI solutions enhance CRM and user satisfaction, boosting retention and loyalty; (f) competitive advantage, because a unified touchpoint across jurisdictions positions your company as a market leader; cross-market insights, which arise from analysing data across jurisdictions to inform product development and marketing strategies; and (g) risk diversification, as operating in various markets mitigates risk by spreading exposure.
1.2 Tax Implications Across Jurisdictions: One of the main compliance challenges relates to tax implications. Different jurisdictions have varying regulations concerning the taxation of SaaS products.
1.2.1 In the European Union, the Value Added Tax (VAT) Directive (2006/112/EC) provides a comprehensive framework, stipulating that VAT should be charged based on the location of the customer.
1.2.2 Similarly, in the United Kingdom, the Finance Act 2020 introduced measures affecting the taxation of digital services, which include SaaS offerings.
1.2.3 In the United States, tax treatment can significantly differ from state to state, as seen in the South Dakota v. Wayfair, Inc. decision (2018), which upheld the ability of states to impose sales tax on out-of-state sellers. This decision emphasises the importance of understanding interstate tax regulations when providing SaaS AI solutions.
1.3 Employment Law Consideration: Employment laws represent another critical area of concern. Differences in employment legislation between jurisdictions can affect how companies deploy SaaS solutions and manage employment relationships. For example, the EU's General Employment Directive outlines minimum protections for workers, which contrasts with US employment laws that can offer more flexibility for employers in areas like at-will employment. At-will employment means an employer can terminate an employee at any time for any reason, as long as the reason isn't discriminatory. As of 2024, 49 out of 50 states and the District of Columbia follow at-will employment laws by default, with Montana being the only exception. Legal precedents, such as the case of the UK Employment Appeal Tribunal ruling in the matter of Aslam v. Uber (2021), underscore the importance of recognising employee status and rights in the gig economy, which can be particularly relevant for AI solutions that manage or interact with a workforce.
1.4 Consumer Protection Laws: Consumer protection laws must also be considered. Each jurisdiction has its own set of regulations designed to protect consumers from unfair practices. For example, the UK Consumer Rights Act 2015 offers extensive protections that could affect how SaaS AI solutions are marketed and delivered. In the EU, the Unfair Commercial Practices Directive (2005/29/EC) protects consumers against misleading actions and omissions, while in the US, the Federal Trade Commission (FTC) enforces consumer protection laws that address false advertising and unfair business practices, as demonstrated in cases like FTC v. Wyndham Worldwide Corp (2012), which highlights data security obligations that affect SaaS companies.
1.5 Cultural and Ethical Considerations: Cultural and ethical considerations are a concern. Different regions may have varying expectations regarding ethical AI use, which can impact the deployment of SaaS solutions. In addition to ethical implications, data protection and privacy laws significantly influence the design and operation of AI systems. The General Data Protection Regulation (GDPR) is a pivotal piece of EU legislation that sets stringent requirements for data processing and privacy, including the rights of individuals to access and control their personal information. In the UK, the Data Protection Act 2018 aligns closely with GDPR principles. In the US, the California Consumer Privacy Act (CCPA) provides substantial consumer rights, influencing how personal data is handled by SaaS providers. Relevant case law, such as the case of Facebook, Inc. v. Duguid (2021), further illustrates the legal complexities surrounding data privacy.
1.6 Blockchain Technology Compliance: The use of Blockchain technology for authentication within AI solutions introduces additional legal considerations. The Regulation on European Blockchain Services Infrastructure (EBSI) in the EU aims to create a secure framework for blockchain use. The EU has also implemented Mica (Markets in Crypto-Assets Regulation) to create a unified, pan-European regulatory framework for crypto-assets. MiCA aims to provide comprehensive regulation for the crypto industry, including blockchain infrastructure services. It establishes rules for crypto-asset service providers (CASPs) and sets out requirements for their activities. While the UK has implemented measures to address crypto-related activities concerning financial products under the authority of the Financial Conduct Authority, it hasn't established a standalone regulatory regime specifically for blockchain infrastructure services in the same way as the EU. The UK has proposed regulations concerning crypto assets and blockchain technology to ensure compliance, particularly concerning financial products. In the US, various state-level blockchain laws, such as Wyoming's blockchain statutes, clarify the legal status of blockchain records and transactions. Landmark cases like SEC v. Ripple Labs, Inc. (2020) illustrate the regulatory landscape surrounding blockchain technology and emphasise the need for compliance with existing legal frameworks.
1.7 In conclusion, successfully deploying SaaS AI solutions across different jurisdictions necessitates a nuanced understanding of tax implications, employment laws, consumer protection regulations, ethical considerations, data protection and privacy laws, and the legal context of blockchain technology. Addressing these complex regulatory challenges is essential for ensuring compliance and minimising potential legal risks.
2. Intellectual Property Considerations in SaaS AI
2.1 Intellectual property (IP) is a cornerstone in developing and deploying Software as a Service (SaaS) AI solutions. These technologies often build upon existing IP, making understanding and managing IP rights essential. In the UK, the Patents Act 1977 and the Copyright, Designs and Patents Act 1988 provide the legal framework for protecting innovations in software and algorithms. In the US, the Patent Act (35 U.S.C. § 101) and the Copyright Act (17 U.S.C. § 101) serve similar purposes, while the EU's Directive 2001/29/EC addresses copyright in the digital environment.
2.2 For SaaS AI providers, safeguarding innovations is crucial. This involves identifying patentable aspects of AI algorithms and software applications. Proper documentation and filing can help secure these innovations. For instance, the case of Alice Corp. v. CLS Bank International (573 U.S. 208, 2014) in the US highlights the importance of demonstrating the technical aspects of software to qualify for patent protection.
2.3 On the user side, if you are using SaaS AI you need to ensure they do not inadvertently violate IP rights. This requires vetting software for potential infringement risks. Due diligence helps avoid costly legal battles, as seen in the UK case of CCH Canadian Ltd. v. Law Society of Upper Canada (2004 SCC 13), which emphasises the need for users to be aware of copyright implications.
2.4 Licensing agreements are pivotal in defining IP ownership. Articulated contracts safeguard both providers' and users' interests. These agreements should explicitly outline usage rights and restrictions, as demonstrated in the EU's Directive 2009/24/EC on the legal protection of computer programs, which mandates that software licenses must be clear and comprehensive.
In conclusion, navigating the complex IP landscape in SaaS AI requires a thorough understanding of relevant statutes and case law across jurisdictions. By proactively managing IP rights, both providers and users can foster innovation while minimising legal risks.
3. Protecting Digital Content and Reputation
3.1 Clear policies can define user interactions. Well-crafted terms of service and privacy policies guide user behaviour. They help manage expectations and ensure compliance with legal standards. Ultimately, protecting digital assets and reputation requires a multifaceted approach. You can safeguard your digital presence effectively by utilising SaaS AI solutions and sound legal guidance.
4. Contractual Liability
4.1 Adaptation is critical in contract law, too. Contracts must evolve to address unique risks associated with SaaS AI. Traditional agreements often lack terms reflecting AI-specific considerations, necessitating innovative legal drafting. In-house lawyers must stay agile and responsive to new legal challenges to ensure that contracts and practices remain relevant and effective in a rapidly evolving landscape.
5. Managing Bias and Discrimination Risks
5.1 These risks arise from the inherent biases in AI algorithms, which can lead to unfair treatment of individuals based on race, gender, age, or other protected characteristics.
5.2 In the UK, the Equality Act 2010 provides a statutory framework to protect individuals from discrimination. This legislation mandates that organisations must ensure their AI systems do not inadvertently perpetuate bias. For instance, the case of R (on the application of the Equality and Human Rights Commission) v. The Secretary of State for Justice (2019) highlighted the importance of ensuring that algorithms used in decision-making processes do not discriminate against protected groups.
5.3 In the US, the Civil Rights Act of 1964 prohibits discrimination based on race, colour, religion, sex, or national origin. The application of this act to AI technologies is increasingly scrutinised, especially in cases like National Fair Housing Alliance v. Facebook (2019), where the court examined whether Facebook's advertising algorithms discriminated against certain demographics. This case underscores the necessity for companies to conduct regular audits of their AI systems to ensure compliance with anti-discrimination laws.
5.4 The European Union has also taken significant steps to address these issues through the General Data Protection Regulation (GDPR) and the proposed AI Act. The GDPR emphasises the right to non-discrimination and requires organisations to implement measures that prevent bias in automated decision-making processes. The AI Act, which is currently under discussion, aims to establish a legal framework for AI that includes provisions to mitigate bias and ensure transparency in AI systems.
5.5 If you are deploying SaaS AI solutions, you must proactively manage these risks effectively. This includes conducting thorough impact assessments, implementing bias detection and mitigation strategies, and ensuring compliance with relevant statutory sources and case law across jurisdictions. By doing so, organisations can protect themselves from legal repercussions and foster trust and fairness in their AI applications.
6. Export Controls and Compliance Risks
6.1 In the United Kingdom, the Export Control Act 2002 and the Export Control Order 2008 govern the export of controlled goods and technology, including software. The UK government has established a list of controlled items, which may include certain AI technologies, that require a license for export. Additionally, the UK's National Cyber Security Centre (NCSC) provides guidance on the security implications of deploying AI solutions, emphasising the need to comply with domestic and international regulations.
6.2 In the United States, the Export Administration Regulations (EAR) administered by the Bureau of Industry and Security (BIS) outline the requirements for exporting dual-use technologies, which can include AI software. The International Traffic in Arms Regulations (ITAR) also play an important role in regulating the export of defence-related technologies. Case law, such as the 2018 decision in United States v. Zhenhua Logistics Group Co., highlights the legal ramifications of non-compliance with these regulations, underscoring the importance of adhering to export controls when deploying SaaS AI solutions.
6.3 In the European Union, the EU Dual-Use Regulation (Regulation (EC) No 428/2009) governs the export of dual-use items, including software that could be used for both civilian and military applications. The regulation requires exporters to obtain licenses for certain AI technologies, and the European Commission has been actively working on a framework for AI regulation that addresses ethical considerations and compliance risks. The case of C-482/17 Czech Republic v European Parliament and Council of the European Union illustrates the complexities of compliance within the EU, as it pertains to the export of sensitive technologies.
6.4 Organisations must be vigilant in understanding the specific legal frameworks and compliance requirements in each jurisdiction where they operate. This includes conducting thorough risk assessments, implementing robust compliance programs, and staying informed about changes in legislation and case law that may impact their SaaS AI deployments. By proactively managing these export controls and compliance risks, you can mitigate potential legal liabilities and ensure the successful deployment of their AI solutions across borders.
7. Third-party Service Dependencies
7.1 The legal landscape surrounding AI technologies is still evolving, and you must be aware of the statutory frameworks and case law that govern their operations in different regions, including the UK, US, and EU.
7.2 In the UK, the Data Protection Act 2018 and the General Data Protection Regulation (GDPR) set stringent data processing and privacy requirements, which can impact SaaS providers' liability. For instance, if a SaaS AI solution mishandles personal data, both the provider and the user may face significant penalties. The case of Google LLC v. Lloyd (2021 UKSC 50) illustrates the potential for liability when data protection laws are breached, emphasising the need for robust compliance measures.
7.3 In the US, the legal framework is more fragmented, with various state laws and federal regulations influencing liability. The California Consumer Privacy Act (CCPA) is one such regulation that imposes strict obligations on you regarding consumer data. The case of Facebook, Inc. v. Duguid (2021) highlights the importance of understanding the nuances of liability in the context of technology and data privacy, as it addresses the definition of automated systems and their implications for liability.
7.4 The EU's approach to AI liability is encapsulated in the proposed AI Act, which aims to create a comprehensive regulatory framework for AI technologies. This legislation seeks to establish clear liability rules for AI systems, particularly those classified as high-risk. The case of C-434/16, Asociación Profesional Elite Taxi v. Uber Systems Spain, SL (2017) demonstrates the EU's commitment to regulating technology companies and ensuring accountability, which is crucial for SaaS providers operating across borders.
7.5 If you are deploying SaaS AI solutions, you must proactively manage third-party liability dependencies by understanding and complying with each jurisdiction’s relevant statutory sources and case law. This mitigates legal risks and fosters trust with users and stakeholders, ultimately contributing to the success of the AI deployment.
8. Liability for AI Decisions
8.1 Deploying Software as a Service (SaaS) AI solutions across multiple jurisdictions presents a complex liability landscape concerning AI decisions that organisations must navigate carefully. The legal framework governing AI liability varies significantly between the UK, US, and EU, necessitating a thorough understanding of statutory sources and relevant case law.
8.2 In the UK, the legal landscape is shaped by the Data Protection Act 2018, which incorporates the General Data Protection Regulation (GDPR) principles. Under these regulations, organisations deploying AI must ensure their systems comply with data protection laws, particularly concerning automated decision-making.
8.3 The Information Commissioner's Office (ICO) has issued guidance on the use of AI, emphasising the need for transparency and accountability in AI-driven decisions. For instance, the case of R (on the application of the Information Commissioner) v. The Secretary of State for Health and Social Care (2021) highlights the importance of lawful processing and the potential liabilities arising from non-compliance.
8.4 In the United States, the legal framework is less centralised, with various states enacting their own regulations. The California Consumer Privacy Act (CCPA) is one of the most significant pieces of legislation affecting AI deployment, as it grants consumers rights regarding their personal data and imposes strict penalties for violations. Additionally, the Federal Trade Commission (FTC) has been active in addressing deceptive practices related to AI, as seen in cases like In the Matter of Everalbum, Inc., where the FTC took action against a company for misleading users about its AI practices. This indicates that companies must be vigilant about the claims they make regarding their AI systems to avoid liability.
8.5 The European Union has taken a proactive approach to AI regulation with the proposed AI Act, which aims to establish a comprehensive legal framework for AI technologies. This legislation categorises AI systems based on risk levels and imposes stringent requirements on high-risk AI applications, including those used in critical sectors such as healthcare and transportation. The EU's commitment to ensuring that AI is used responsibly is evident in the case of C-311/18 Data Protection Commissioner v. Facebook Ireland Ltd., which underscores the importance of data protection in the context of AI.
Conclusion
Importance of Legal Consultation for SaaS AI
As your organisation embarks on the SaaS AI journey, consider the legal implications seriously. Engage with an experienced digital media lawyer, like Mr. Peter Adediran of PAIL Solicitors, who can provide tailored advice and ensure compliance with the latest regulations. Investing in a technology specialist lawyer whose career has been forged in creating strategies to deal with the intersection between legal compliance and innovative, disruptive digital technologies will equip your business for future success.
Investing in Legal Expertise for Future Success
By taking these proactive measures, you can confidently leverage SaaS AI solutions, driving innovation and growth while maintaining legal compliance.
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For a quotation, please contact us at (020) 7305-7491 or peter@pailsolicitors.co.uk. We would be delighted to assist you. The writer is Mr Peter Adediran, the owner and principal solicitor at PAIL® Solicitors and a specialist and one of the legal pioneers in digital technologies law having worked with omnichannel customer experience and CRM electronic communication systems of multinational companies since their earliest formation in the early 90’s. Subscribe to our newsletter to get blog post updates and other information about the firm straight to your inbox.