Governance and Challenges of Intellectual Property Compliance in the Age of AI

Dear directors and executives, good afternoon. I am delighted to be invited by the Taiwan Directors Association to share legal issues related to AI with you at Chia Hsin Cement Corporation. Today’s topic is “Governance and Challenges of Intellectual Property Compliance in the AI-Driven Era.” With the rapid development of artificial intelligence (AI) technology, corporate boards are facing unprecedented governance challenges, and the role of boards is also transforming. We will explore this from four perspectives: First, what governance challenges AI technology development brings to boards and how board roles are changing. Second, the importance of intellectual property rights in the AI era and risk management. Third, how to leverage generative AI to enhance intellectual property governance effectiveness. Finally, the responsibilities and practical directions boards should undertake in the AI era across four dimensions: governance, transparency, digital, and innovation. I hope through these insights to help you prepare comprehensively in corporate compliance and governance.

I. Governance Challenges and Board Role Transformation Brought by AI Technology Development

First, let’s look at the new challenges AI technology’s rapid development brings to boards and how board roles are transforming. AI technology evolves rapidly, and its nature and impact on business operations are often difficult to grasp in real-time. Related regulations are also accelerating due to AI, requiring boards to constantly monitor the latest regulatory trends. Additionally, AI has lowered the barriers to cross-disciplinary knowledge and industry competition. All forms of language-presented knowledge can potentially be processed by large language models (LLMs), giving AI inherent cross-disciplinary application potential. This means traditional industry boundaries are dissolving, and cross-industry competitive risks are increasing—new technologies or models from different fields may overturn existing industry competitive landscapes in a short time.

In this environment, board composition and decision-making methods also face transformation. Previously, boards might have emphasized members covering various professional fields, but now, even lacking directors with certain specific expertise, one can obtain opinions from different fields with the help of generative AI. Relatively speaking, directors need to cultivate integrated judgment and decision-making abilities more than just single-field professional knowledge. The importance of decision quality and data governance is also increasingly prominent, and decision-making processes will become increasingly transparent. AI tools can greatly improve board decision quality, but the prerequisite is that board members must properly use AI tools without over-reliance, avoiding the trap of “AI is always right.” At the same time, the data quality AI decisions rely on is crucial: if companies don’t establish good data governance, with incorrect or incomplete data, even the most powerful AI cannot make correct decisions. Therefore, boards need to urge companies to ensure data correctness, completeness, and usability to maximize AI’s decision-support benefits. Worth mentioning is that with AI assistance and information transparency trends, improper decisions are more easily reviewed and pursued after the fact, which serves as another form of oversight and reminder for boards—requiring us to be more careful and thorough in decision-making.

Beyond technology and decision-making levels, AI brings values and ethical challenges. AI adoption usually accompanies overall corporate digital transformation, potentially impacting the company’s existing core values. For example, even OpenAI, currently the world’s most influential AI company, has experienced dramatic conflicts between board members due to different philosophies: founder Elon Musk previously questioned OpenAI’s shift toward commercialization and closed nature and filed lawsuits; in 2023, the board suddenly dismissed CEO Sam Altman, then quickly rehired him and reorganized the board due to strong employee backlash; and tensions in the strategic relationship between OpenAI and Microsoft—all fundamentally related to choices about “core values.” These events show that corporate governance decisions in the AI era are not just technical issues but choices about values and ethics. The more powerful the technology, the more severe the ethical challenges.

Additionally, applying AI to production line monitoring can improve quality and efficiency but may raise concerns about employee privacy violations; providing AI-driven products or services to consumers may involve unexpected personal data and information security risks—should companies launch these products even if they are popular in the market? Or, to obtain more complete training data, companies may be tempted to collect data from illegal sources—clearly violating compliance principles. It’s clear that new problems brought by AI technology applications often transcend traditional management scope, rising to corporate governance-level issues, forcing boards to invest more effort in decision-making.

In summary, under the AI wave, boards must adjust their roles and more actively lead corporate technology strategy and risk management. At the same time, board members must enhance their understanding and skills regarding AI to effectively supervise management’s use of AI. Facing values and ethical challenges raised by AI, boards should play a dual role as the company’s “conscience” and strategic navigator: while promoting technological innovation, uphold the company’s core values and compliance principles, ensuring the company doesn’t deviate from the right path in pursuing innovation.

II. Importance and Risk Management of Intellectual Property Rights in the AI Era

Next, let’s discuss the importance of intellectual property rights (IP) in the AI era and related risk management. With industrial digitalization and knowledge economy development, intellectual property rights have become one of the most important intangible assets for companies. However, they are also sources of intangible risks that must be incorporated into business management. For companies, IP is like a double-edged sword: on one hand, it’s a source of competitive advantage; on the other hand, if poorly managed, infringement disputes will bring high costs and reputational damage. Therefore, boards need to ensure companies establish sound intellectual property management systems and incorporate IP management into corporate governance plans.

In fact, Taiwan’s corporate governance regulations already explicitly require boards to take IP management seriously. Article 37-2 of the “Corporate Governance Best Practice Principles for TWSE/TPEx Listed Companies” stipulates that boards should evaluate and supervise the company’s intellectual property management direction and performance across several dimensions under the Plan-Do-Check-Act (PDCA) management cycle to establish an effective IP management system. This specifically includes five aspects:

1. Policies and Systems: Formulate IP management policies, goals, and systems linked to corporate operational strategies. In other words, a company’s IP layout and management should be considered in conjunction with overall strategy.
2. Acquisition and Utilization: Based on company scale and type, establish and implement management systems for acquiring, protecting, maintaining, and utilizing intellectual property. Ensure the company systematically acquires patents and trademarks, protects trade secrets, and effectively utilizes these IP resources.
3. Resource Investment: Boards must decide and provide sufficient resources to effectively implement and maintain IP management systems. Without resource support, even the best systems are difficult to operate.
4. Risk Monitoring: Observe internal and external risks or opportunities related to IP management and take appropriate countermeasures. For example, monitor regulatory changes, competitors’ patent dynamics, and new opportunities brought by technological development to prevent potential risks in advance.
5. Continuous Improvement: Plan and implement continuous improvement mechanisms to ensure IP management system operations and effectiveness align with company goals. That is, continuously review and optimize IP management to keep pace with the times.

This shows IP management has become an important part of corporate governance, and boards are responsible for supervising IP management performance from a strategic height.

So what risks arise if companies neglect IP management? IP infringement is a major minefield in corporate compliance, including both criminal and civil liability. Let’s first look at criminal liability: although companies themselves won’t serve prison sentences for crimes, they still have the potential to incur criminal liability. Employees who actually commit infringement, supervisors who order or fail to prevent infringement, or even responsible persons may all be identified as criminal actors and face criminal punishment. Under Taiwan’s Copyright Act and Trade Secrets Act, if company personnel infringe others’ copyrights or trade secrets, not only may those personnel be held criminally liable, but the legal person (company) may also face joint fines.

Next is civil liability: IP infringement usually leads victims to claim damages. Courts can award not only actual losses and lost profits but also, when damages are difficult to prove, allow courts to determine statutory compensation amounts. Article 89 of the Copyright Act even stipulates that victims may request infringers to publish the judgment’s main text or summary in newspapers at their own expense to restore reputation through such public means—a situation many companies desperately avoid, and historically, companies have often been more willing to actively settle with rights holders considering this risk. Courts can also issue injunction-like judgments to prevent infringement, and before actual trial of infringement cases, to prevent damage expansion leading to irreparable harm to rights holders, they may issue provisional injunctions prohibiting specific acts—posing significant operational risks for companies, potentially requiring entire production lines to shut down and possibly creating breach of contract disputes with customers.

Looking at cross-border infringement risks: in international trade, countries all have border protection measures based on international treaties. If a company’s products involve infringing patents, trademarks, or copyrights in other countries, they may be seized by customs during export or import. Once detained at borders, not only are goods damaged, but it may also lead to breach disputes or litigation between the company and buyers. This reminds us that in the global market, companies need stricter IP risk management to ensure products and technologies don’t infringe others’ rights in all target markets.

Facing all these risks, boards should adopt a proactive management attitude in IP governance. There’s a saying: “If you don’t manage your money, money won’t manage you”—applied to intellectual property, if companies don’t proactively manage their IP, the law won’t automatically protect you. In fact, IP protection often requires advance deployment: patents and trademarks need to be registered individually in target countries, and trade secrets require confidentiality measures in advance. If you wait until disputes arise to think about deployment or asserting rights, it’s often too late. Therefore, boards should require management to treat IP as assets to be managed and do preventive work.

In IP management strategy, it can be summarized as “opening sources and reducing expenditures.” “Opening sources” refers to creating revenue through IP, such as licensing patents or technology to others, actively using law to protect rights (filing lawsuits for compensation), cooperating with others on development, and monetizing IP value through marketing—these are core means of IP management to open revenue streams for companies. On the other hand, “reducing expenditures” refers to using IP management to save costs and reduce losses for companies: reuse existing IP resources to improve R&D efficiency; more importantly, avoid infringing others’ IP to avoid litigation or compensation. Only by emphasizing both opening sources and reducing expenditures can a company’s IP strategy both generate revenue and avoid losses from infringement.

Additionally, boards should ensure companies adopt comprehensive IP protection thinking. In vertical deepening, for a single IP right, make its protection as tight and complete as possible, even extending its term. Don’t miss opportunities to obtain complete protection due to ignoring legal requirements or procedures. For example, whether invention patents need simultaneous utility model applications or patent life extension—these are considerations for vertical deepening of protection. In horizontal linking, different types of IP rights are combined. A single product or service can often be protected by multiple IP rights simultaneously, for example: protect core technology with trade secrets during R&D, apply for patents after launch to guarantee exclusivity after technology disclosure, while using trademarks and copyrights to protect brand image and content creativity. Different rights complement each other, building a protective network that competitors can’t easily overcome.

Furthermore, IP management should start with basic documents: companies’ R&D achievement records, copyright or patent registration certificates, transaction or licensing contracts, and other documents should all be properly managed and preserved. Documents are key evidence for future rights assertion or litigation defense—lacking key documents may put the company in a disadvantageous position in disputes. At the same time, consider the different duration periods of various IP rights and plan in advance for renewal or extension possibilities (such as trademark renewal before expiration, developing improved technologies for new patent applications before patent expiration). Only through vertical and horizontal advancement, combining offense and defense in IP strategy, can companies maintain innovation momentum while minimizing risks in the AI era.

IP indeed plays a key role in the AI era: AI model development relies on massive data and algorithms, which are usually subject to copyright, database rights, or patent regulations; AI products and services also need trademarks, patents, copyrights, trade secrets, etc., to protect market position. Therefore, boards must highly value IP assets, treat them as part of corporate competitive strategy, and ensure the company not only makes good use of its own IP but also doesn’t cross others’ IP red lines.

III. Leveraging Generative AI to Enhance Intellectual Property Governance Effectiveness

Third, let’s explore how to leverage generative AI to enhance IP governance effectiveness. We mentioned earlier that AI brings challenges, but AI, especially generative AI, can also become a powerful tool for boards, helping us manage IP more intelligently and reduce risks. Specifically, generative AI can play a role in the following areas:

1. Strengthening Strategic Decision-Making: Generative AI excels at extracting useful information from large amounts of data to provide decision references. For example, it can quickly digest internal company data, competitors’ public information, and overall industry trends, helping boards view IP as part of corporate competitive strategy. Through AI analysis, boards can more proactively participate in formulating IP management policies and goals closely linked to the company’s medium- and long-term operational strategies. In short, AI can transform scattered IP-related information into high-level insights, allowing boards to integrate IP considerations into the company’s development blueprint when formulating strategies.
2. Supporting Investment Evaluation: In the AI era, companies’ IP layouts don’t necessarily rely entirely on self-developed R&D; outward investment, M&A, and licensing are also ways to acquire IP. But investing in others’ technologies and IP outside familiar industries is often full of uncertainty. Generative AI’s cross-disciplinary data interpretation ability can greatly reduce this risk. Through AI, we can more quickly evaluate target companies’ patent portfolios, technology strengths and weaknesses, synergies with our own business, and potential regulatory or infringement risks. This allows boards to make more informed judgments when considering acquiring or licensing a technology, rather than relying solely on manual information collection. In other words, AI becomes the board’s IP analysis consultant, providing comprehensive information needed for investment decisions.
3. Strengthening Risk Monitoring: Generative AI can also greatly improve IP risk and opportunity monitoring efficiency. On one hand, AI can help review internal company processes and documents to proactively discover potential infringement risks. For example, scan R&D reports and product design documents to check whether externally protected content has been introduced without authorization, or review contracts signed with partners for IP protection loopholes, prompting management to take remedial measures early. On the other hand, AI can continuously monitor the external environment, tracking and analyzing competitors’ IP dynamics and market information. For example, daily compilation of global patent applications, trademark registrations, IP litigation cases, and industry news, extracting parts relevant to the company’s business for board reference. This real-time intelligence allows boards to know whether competitors are deploying patents in certain technology areas, which startups own IP that could disrupt the industry, and whether there are major infringement litigation trends in the industry. With AI assistance, IP risk monitoring changes from passive to proactive, allowing boards to respond earlier to potential threats or seize opportunities.

It’s important to emphasize that when using generative AI to assist IP governance, boards must still maintain professional judgment and caution. Although AI is powerful, its analysis results and recommendations may be limited by input data quality or have errors due to algorithmic bias. Therefore, boards should view AI as a decision-support tool, not a replacement for human decision-makers. We can require management teams to establish mechanisms combining AI analysis with expert judgment: first AI provides preliminary analysis, then relevant legal, technical, or strategic experts review, and finally the board makes comprehensive decisions. This way, we can enjoy the efficiency and insights AI brings while avoiding decision bias from blindly following technology. At the same time, boards must also ensure AI use complies with relevant regulations, such as confirming AI training data sources are legal, don’t infringe third-party IP rights, and preventing company secrets from leaking when using AI tools. Only by fully utilizing generative AI under safe and compliant premises can we truly enhance IP governance effectiveness and create value for the company.

IV. Board Responsibilities and Practices in the AI Era Across Four Dimensions: Governance, Transparency, Digital, and Innovation

Finally, let’s look at how boards fulfill responsibilities and implement best practices in the AI era across four dimensions: Governance, Transparency, Digital, and Innovation. These four dimensions cover the key focus areas for boards in the AI application wave, from internal risk management to external communication, to digital transformation and long-term strategy. Let me explain each:

1. Governance: Decision quality and risk management. Boards should lead in formulating company policies for AI adoption, clearly defining the scope and principles of AI technology applications. At the same time, require management to regularly report to the board on regulatory compliance (such as personal data protection, industry regulations), equipment safety (such as AI system reliability), operational efficiency, etc., during the AI adoption process. Through such mechanisms, boards can grasp AI’s impact on operations in real-time and fulfill supervisory responsibilities. Additionally, boards need to supervise and check whether AI systems actually strengthen the company’s risk early warning capabilities and environmental and quality control capabilities, thereby reducing risks such as operational interruptions and regulatory fines. In short, in the governance dimension, boards must ensure AI becomes a tool for improving decision quality and risk management, not a new source of risk.
2. Transparency: Information disclosure and communication. The AI era emphasizes corporate operational transparency, and boards should require companies to proactively disclose AI usage and related risks to stakeholders. For example, results achieved by applying AI to operations (such as reducing carbon emissions, improving energy efficiency) and possible errors or risks should all be honestly disclosed in annual reports or ESG sustainability reports. This not only demonstrates to investors and society that the company fulfills corporate responsibility but also facilitates stakeholder supervision of whether company AI applications comply with ethical and regulatory requirements. At the same time, boards should urge management to actively communicate with investors, relevant communities, and regulatory authorities, explaining whether the company’s AI system’s data sources comply with regulations, whether algorithms maintain a certain degree of transparency, and the basis for AI decisions. Through this open dialogue, boards can build external trust in the company, resolve concerns about AI applications, and ensure the company’s AI strategy gains recognition from all parties.
3. Digital: Information system integration and early warning capabilities. In the digital transformation dimension, boards should focus on whether the company’s data governance and information security foundation is sufficient to support AI applications. Specifically, boards need to supervise companies to establish good corporate data governance systems, ensuring data sources used by AI comply with relevant regulatory standards, while the company’s AI system can smoothly integrate with existing enterprise resource planning (ERP), business intelligence (BI), and other systems. This integration allows AI to collect information from internal and external sources in real-time and produce early warning reports for high-level decision reference, such as real-time alerts for operational anomalies and market trend analysis. Additionally, boards must focus on AI system information security, ensuring AI-related systems don’t become vulnerabilities for hacker attacks. If AI systems are hacked and paralyzed, or sensitive data is stolen and leaked, it may cause serious damage to company operations and reputation. Therefore, in the digital dimension, the board’s responsibility is to urge the company to build a safe and efficient digital neural network, ensuring enterprise operations remain stable and reliable after AI integration.
4. Innovation: Business models and long-term value. AI brings not just efficiency improvements but may also spawn entirely new business models and market opportunities. The board’s responsibility in this area is first to encourage innovation: encourage management teams to leverage AI technology to explore new markets, optimize processes, and develop differentiated products or services. For example, traditional industries can use AI to find new opportunities for sustainable development (such as new low-carbon cement formulas, new infrastructure market demands overseas) to create new revenue sources. At the same time, boards should require teams to conduct thorough risk assessments in each AI innovation project and establish feedback mechanisms to adjust direction at any time. Second, boards need to ensure innovation aligns with the company’s long-term value—innovation shouldn’t be pursued just to follow trends. That is, new technology adoption should be combined with the company’s operational goals and sustainability commitments. For example, when pursuing AI innovation, simultaneously consider carbon reduction, circular economy, and other sustainability goals, making innovation results contribute to the company’s long-term interests and social responsibility. In short, in the innovation dimension, boards play a dual role as navigator and gatekeeper: on one hand, promoting the company’s embrace of innovation opportunities brought by AI; on the other hand, ensuring these innovations are conducted within controllable risk ranges and align with the company’s vision and mission, creating long-term value for the company.

These four dimensions of responsibility constitute the core framework of board governance practice in the AI era. Boards can only lead companies to stand firm and move forward in the rapidly changing AI wave by being thoughtful and discerning in governance, open and honest in transparency, solid and cultivating in digital, and bold yet appropriately steering in innovation.

V. Conclusion

Dear directors and distinguished guests, in the AI-driven era, the internal and external environment companies operate in is undergoing profound changes. Boards face unprecedented challenges: we need to grasp new technology dynamics more quickly, adapt to regulatory changes, and lead corporate digital transformation directions. At the same time, we also bear the heavy responsibility of maintaining corporate values and ethics, ensuring AI applications meet societal expectations. The importance of IP is increasingly prominent—it is both the cornerstone of corporate innovation and a bargaining chip in competition; without sound IP management, companies’ innovation results may not be protected and may even suffer losses from unintentional infringement.

We discussed methods for leveraging generative AI to strengthen IP governance, showing that AI not only brings challenges but also provides solutions—allowing us to manage corporate knowledge assets and compliance risks with higher efficiency and broader vision. But no matter how advanced the tools, they can’t replace human judgment—boards must still maintain professionalism and use AI with a cautious attitude.

Overall, the AI era calls for higher-level corporate governance. Board roles need to be more active and diverse: serving as both gatekeepers for risk management and navigators for innovation development. At the same time, respond to stakeholder expectations with a transparent and accountable attitude and invest in digital infrastructure with a long-term perspective. Only in this way can companies remain undefeated in changing circumstances and transform AI challenges into growth opportunities. My presentation ends here. Thank you all for listening!