Intellectual Property in Innovation

I came across a recent Science study that analyzed 77 patents from AI-first drug discovery companies. Compared to traditional, lab-based developers, these companies were significantly more likely to patent small-molecule compounds without conducting any in vivo studies. The study also found a consistent pattern: less biological data, fewer ADMET experiments, limited formulation detail, and earlier filings overall. Only 23% of these AI-driven patents included any animal testing. Yet many disclosed hundreds of molecules with minimal experimental validation. This raises a red flag. It looks less like a push toward de-risked innovation and more like broad IP positioning based on computational output. From a business standpoint, I understand the pressure to file early. Patents shape competitive advantage, attract capital, and signal pipeline momentum. But if filings outpace meaningful validation, the result is an innovation bottleneck. Untested molecules sit protected but undeveloped, blocking others from advancing or investing in them. AI has the potential to reshape drug discovery, but not by scaling noise. Its real commercial value lies in helping us prioritize high-quality candidates that are both novel and actionable. Filing before experimental validation shifts risk downstream, creates friction in licensing, and undermines investor confidence in the actual readiness of assets. If we want AI to accelerate not just ideation but actual development, we need to realign incentives. Strong IP should be linked to strong evidence. Otherwise, we risk building a patent landscape that looks impressive on paper but slows real progress. 📄 https://lnkd.in/eZdHvx-U #ai #drugdiscovery #biotech

A few people asked what it actually looks like to file patent applications the smart way. Here’s the framework I give startup teams who want to protect innovation without wasting capital: 1. Don’t file just because you “can.” Too many patent applications get filed on features that aren’t core to the product, the market, or the long-term strategy. Just because it’s technically new doesn’t mean it’s worth protecting. 2. Tie every filing to a business objective. What are you trying to accomplish? Protect revenue? Block a competitor? Support a valuation narrative? There needs to be a clear business case for every dollar spent on IP. 3. Prioritize enforceability over imagination. Broad, abstract patents might sound exciting, but they often fail when tested. Focus on what you can realistically enforce. If your claim can’t stand up in court or deter a competitor, it’s not helping you. 4. Treat foreign filings like investments — not checkboxes. Filing internationally gets expensive fast. File where you have customers, competitors, or partners. Not where “you might want protection someday.” 5. Reassess regularly. As your product evolves, your patent strategy should too. What mattered at seed stage may not matter at Series B. Trim the fat. Redirect capital where it matters. The bottom line: a strong patent strategy isn’t about quantity — it’s about alignment. The best portfolios are lean, targeted, and tied directly to how the company competes and grows. If you’re not sure whether your IP is doing that, it’s worth a second look.

AI is rewriting the rules of innovation. But who owns the future? The USPTO just unveiled its AI Strategy (January 2025), a blueprint for navigating AI’s role in intellectual property. With patents, trademarks, and copyrights at stake, this is about more than just technology—it’s about who controls the next era of innovation. Here are 5 takeaways: 1️⃣ AI Won’t Own Inventions—Yet AI can assist in innovation, but human inventors remain at the center of patent law. The USPTO is firm: AI can’t be listed as an inventor, but AI-generated work may influence patentability. The legal line is being drawn. 2️⃣ Patent Reviews Are Getting Smarter The USPTO is using AI to examine AI—leveraging machine learning for prior art searches, classification, and decision-making. This means faster approvals, better accuracy, and a more scalable patent process for the future. 3️⃣ IP Protection vs. AI Creativity: The Collision Generative AI is churning out text, images, music, and designs—but who owns it? Trademark and copyright laws weren’t built for AI-generated content. The USPTO is working to define rights and responsibilities in an AI-driven creative economy. 4️⃣ The U.S. is Playing for Global AI Leadership AI innovation is a geopolitical race. The USPTO is working with international partners to shape global AI patent standards, ensuring U.S. leadership in AI regulation, enforcement, and competition. The message? Innovation without protection is just an idea. 5️⃣ AI for All, Not Just Tech Giants The USPTO wants AI-driven innovation to be accessible, not just locked up by billion-dollar companies. From startups to underrepresented inventors, AI tools and patent protections need to be inclusive and equitable—or we risk leaving brilliant minds behind. What’s the bottom line? AI is not just a technology—it’s an economic force. The USPTO is positioning the U.S. to lead the next chapter of AI innovation while ensuring IP laws evolve to keep up. But will regulations accelerate AI’s potential—or slow it down?

Breaking down key IP findings in the Congressional report on #AI: 1️⃣ The issue of whether the training of AI models using copyrighted works constitutes copyright infringement is working its way through the court system. Main issue - Is it fair use and how does the Google Books case inform that analysis? Meanwhile, industry solutions are emerging: - Some AI developers have entered into creative licensing agreements with some rights holders - Some are using copyright clearinghouses - Start-ups are emerging to aggregate content Preliminary draft legislation in the PRC ▶️ use of copyrighted data for training is generally “a reasonable use of data” not requiring payment EU AI Act (effective Aug 2025) ▶️ requires transparency/sufficiently detailed summary of training data 2️⃣ USPTO & United States Copyright Office have been proactive in addressing the protectability of AI-generated ideas and content. Issues remain and more clarity is needed. These issues will be resolved, and clarity provided, over time by the agencies and the courts. The issue of AI-generated ideas or content infringing IP is also working its way through the courts (see again Google Books). 3️⃣ Stakeholders concerned that Alice decision could be read to prevent the patenting of AI-related inventions. They also have concerns that AI will raise the bar for patentability (more and more over time) because much more will be obvious in view of AI. 4️⃣ On transparency, some stakeholders want more (including documenting training data), whereas AI tech companies are worried about the expense and logistical and technical difficulties (+ disclosure of trade secrets or proprietary information). Some including White House calling for transparency (such as watermarking) if audio or visual output created or modified with AI. 5️⃣ Most high profile issue is abuse of identify-based rights or digital replicas/deep fakes. United States Copyright Office calls for urgent legislation to address gaps in current patchwork of laws and provides guidance on same. 🎙️ YOU can help shape the laws in the US, PRC and Europe (+). Contact the agencies (including attaches) who comment on and shape the work in Congress and in other countries. Use the amicus process in the courts even at the district court level. Full report ▶️ https://lnkd.in/gaRNe2NT #AI #IP #Congress

𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗟𝗮𝘂𝗻𝗰𝗵 𝗮𝗻𝗱 𝗣𝗮𝘁𝗲𝗻𝘁𝘀: 𝗧𝗶𝗺𝗶𝗻𝗴 𝗜𝘀 𝗘𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 Your product launch can make or break your patent rights. Many founders don't realize that public disclosures of their technology—whether through product launches, marketing materials, or conference presentations—can permanently destroy patent rights in most countries and start a one-year clock ticking in the United States. 𝗧𝗵𝗲 𝗣𝗿𝗲-𝗟𝗮𝘂𝗻𝗰𝗵 𝗦𝘄𝗲𝗲𝘁 𝗦𝗽𝗼𝘁 The ideal time to file patent applications is before any public disclosure of your technology. This timing preserves your rights worldwide while positioning you to: • Protect your core technology before competitors see it in action • Maintain flexibility to file internationally as your business grows • Signal innovation leadership to customers and investors • Begin building barriers against fast followers 𝗣𝗿𝗼𝘁𝗲𝗰𝘁𝗶𝗻𝗴 𝗙𝘂𝘁𝘂𝗿𝗲 𝗜𝘁𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀 Your first product launch reveals more than just your current features—it shows competitors your technological direction. Smart companies file patent applications that protect not only their initial product but also anticipated future iterations. For software companies especially, this means protecting core architectures and algorithms that will remain valuable as implementation details evolve. Strategic use of continuation applications lets you adapt your patent protection as your product develops and as you observe how competitors react to your innovation. This approach is particularly valuable for AI and software companies, where rapid development cycles mean your technology may advance significantly during patent examination. 𝗧𝗵𝗲 𝗖𝗼𝘀𝘁 𝗼𝗳 𝗪𝗮𝗶𝘁𝗶𝗻𝗴 Delaying patent filings until after launch might save money in the short term, but often proves expensive in the long run. Lost international rights, emboldened competitors, and weakened negotiating positions with investors and acquirers can far outweigh the initial cost savings. Stay tuned for my next post about pivoting your patent strategy as you scale. Want to ensure your product launch strengthens rather than weakens your patent position? Let's discuss how to time your patent filings to maximize protection of your innovations. #patents #productlaunch #innovation

𝗪𝗲 𝗯𝘂𝗶𝗹𝘁 𝗮𝗻 𝗔𝗜 𝗮𝗴𝗲𝗻𝘁 𝘁𝗵𝗮𝘁 𝘁𝘂𝗿𝗻𝘀 𝗽𝗮𝘁𝗲𝗻𝘁𝘀 𝗶𝗻𝘁𝗼 𝘃𝗲𝗻𝘁𝘂𝗿𝗲 𝗰𝗮𝗽𝗶𝘁𝗮𝗹. (This is what enterprise AI actually looks like.) ----- A VC came to us with millions in dormant IP. Not ideas. 𝗜𝘀𝘀𝘂𝗲𝗱 𝗽𝗮𝘁𝗲𝗻𝘁𝘀. The question: 𝗛𝗼𝘄 𝗱𝗼 𝘆𝗼𝘂 𝘁𝘂𝗿𝗻 𝗶𝗻𝘁𝗲𝗹𝗹𝗲𝗰𝘁𝘂𝗮𝗹 𝗽𝗿𝗼𝗽𝗲𝗿𝘁𝘆 𝗶𝗻𝘁𝗼 𝗳𝘂𝗻𝗱𝗮𝗯𝗹𝗲 𝘃𝗲𝗻𝘁𝘂𝗿𝗲 𝗼𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝗶𝗲𝘀 — 𝗮𝘁 𝘀𝗰𝗮𝗹𝗲? ----- We didn’t build a dashboard. We built a full-stack IP commercialization engine. 1️⃣ 𝗣𝗮𝘁𝗲𝗻𝘁 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗟𝗮𝘆𝗲𝗿 → Each patent is scored across technical readiness, use context, operational suitability, dual-use potential, and commercial viability → It doesn’t just store IP — it identifies what can become a business 2️⃣ 𝗚𝗿𝗮𝗻𝘁 𝗠𝗮𝘁𝗰𝗵𝗶𝗻𝗴 𝗘𝗻𝗴𝗶𝗻𝗲 → Matches scored patents to SBIR & DoD funding opportunities → Scores fit based on technical alignment, application relevance, and operational readiness → Highlights which IP has the highest probability of getting funded 3️⃣ 𝗣𝗿𝗼𝗽𝗼𝘀𝗮𝗹 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄 → Generates Specific Aims, Research Plans, Budget Justifications, and full SBIR-ready narratives → Uses AI to position patents for fundability — not just compliance ----- Think about what this replaces: → Analysts doing market-fit checks → Grant writers drafting submission packages → Strategists building IP roadmaps Now compressed into a system that understands: 𝗣𝗮𝘁𝗲𝗻𝘁 𝗹𝗮𝘄 × 𝘃𝗲𝗻𝘁𝘂𝗿𝗲 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆 × 𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗱𝘂𝗲 𝗱𝗶𝗹𝗶𝗴𝗲𝗻𝗰𝗲. ----- This isn’t about moving faster. It’s about moving 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁𝗹𝘆. Enterprise AI doesn’t summarize documents. It makes 𝗶𝗻𝘃𝗲𝘀𝘁𝗺𝗲𝗻𝘁 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀. ----- You don’t build this by chaining prompts. You build it by thinking at the intersection of 𝗰𝗼𝗺𝗺𝗲𝗿𝗰𝗶𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻, 𝗰𝗮𝗽𝗶𝘁𝗮𝗹, 𝗮𝗻𝗱 𝗰𝗼𝗺𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻. That’s what we’re doing. This is one of those systems that proves it. There are levels to this game.

Over the holidays, I spent over 100 hours becoming more of a subject matter expert in AI, as I was already interested in the IP implications of artificial intelligence. Here is my take: AI is transforming patent law, and most practitioners aren't ready for it. Here's what's happening right now: 1. The USPTO won't recognize AI systems as inventors 2. Patent attorneys must adapt to new AI guidelines 3. AI tools are changing patent litigation completely 4. Only natural persons can be listed as inventors But that's just the start. The real changes are coming through: - International efforts to handle AI patent challenges - Strict rules about using AI in patent submissions - New examination procedures for AI-related patents - Updates to subject matter eligibility under 35 U.S.C. § 101 And here's what this means for patent practitioners: 1. Learn AI-related patent examination guidelines 2. Understand international AI patent standards 3. Stay current with USPTO's AI policies 4. Master ethical AI use in patent work The legal system is adjusting to these changes. Legislative reforms are coming. Patent practitioners who prepare now will be ready. Those who don't will fall behind. It's that straightforward. Don't wait to adapt. I will provide guidance in the coming days. #ai #ailaw #aipatents #aiip #artificialintelligence #patents #patentlitigation #BrownRudnick

Entering a new market often means relying on local partners, manufacturers, distributors, or designers. But what happens when that partner misuses your intellectual property and turns into a competitor? In this article, I share real cases from SMEs in China that illustrate how quickly partnerships can go wrong, and how gaps in IP registration, contracts, and due diligence open the door to abuse. More importantly, I outline practical steps to prevent these issues—registering your IP in China, securing the right contracts, and conducting thorough and ongoing investigations into your partners. The takeaway: prevention is far less costly than litigation. With the right protections in place, companies can reduce risk and maintain control over their most valuable assets—patents, trade secrets, and know-how. #China #intellectualproperty #business #contracts #disclosures

𝐀𝐮𝐭𝐨𝐧𝐨𝐦𝐨𝐮𝐬 𝐀𝐈 𝐍𝐨𝐰 𝐓𝐫𝐚𝐝𝐢𝐧𝐠 𝐈𝐧𝐭𝐞𝐥𝐥𝐞𝐜𝐭𝐮𝐚𝐥 𝐏𝐫𝐨𝐩𝐞𝐫𝐭𝐲 𝐑𝐢𝐠𝐡𝐭𝐬 A recent article from Decrypt sheds light on a significant development in AI: autonomous agents are now capable of trading intellectual property (IP) rights with each other. This advancement marks a new frontier in AI capabilities and could reshape how we approach innovation and IP management. 𝐊𝐞𝐲 𝐭𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬 𝐚𝐧𝐝 𝐢𝐦𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 👉𝐀𝐮𝐭𝐨𝐧𝐨𝐦𝐨𝐮𝐬 𝐍𝐞𝐠𝐨𝐭𝐢𝐚𝐭𝐢𝐨𝐧 AI agents are now demonstrating the ability to engage in complex negotiations without human intervention. This includes: ▪Understanding the value of different IP assets ▪Assessing risks and potential benefits of trades ▪Making strategic decisions based on long-term goals ▪Adapting negotiation strategies in real-time This level of autonomy in high-stakes decision-making represents a significant leap in AI capabilities. 👉𝐈𝐏 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 The integration of AI in IP trading could revolutionize how intellectual property is managed, licensed, and valued: ▪Automated IP audits could become more thorough and frequent ▪Real-time royalty tracking and distribution might become standard ▪AI could enhance IP enforcement by quickly identifying potential infringements ▪Valuation of IP portfolios could become more dynamic and market-responsive ▪Cross-licensing agreements could be negotiated and updated automatically These changes could lead to more efficient IP markets and reduced transaction costs. 👉𝐄𝐦𝐞𝐫𝐠𝐢𝐧𝐠 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐌𝐨𝐝𝐞𝐥𝐬 This technology opens the door to entirely new business models centered around AI-driven IP: ▪AI-generated inventions could become more common, raising questions about authorship and ownership ▪AI-facilitated IP marketplaces could emerge, allowing for instant trading of patents, copyrights, and other IP assets ▪AI-powered IP valuation services could provide real-time, market-driven assessments ▪Companies might develop AI agents specialized in managing and trading specific types of IP ▪New insurance products could arise to cover risks associated with AI-driven IP trade 👉𝐋𝐞𝐠𝐚𝐥 𝐚𝐧𝐝 𝐄𝐭𝐡𝐢𝐜𝐚𝐥 𝐂𝐨𝐧𝐬𝐢𝐝𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬 This development raises important questions that will need to be addressed: ▪How will existing IP laws apply to AI-driven trades? ▪What safeguards are needed to prevent market manipulation by AI agents? ▪How can we ensure transparency and accountability in AI-driven IP transactions? ▪What are the implications for human inventors and creators? As AI agents become more sophisticated, their role in managing and trading IP will only expand. This marks the beginning of a fascinating new chapter in the intersection of AI and intellectual property. 𝐒𝐨𝐮𝐫𝐜𝐞: https://lnkd.in/guJsQsct #AI #DigitalTransformation #GenerativeAI #GenAI #Innovation  #ArtificialIntelligence #ML #ThoughtLeadership #NiteshRastogiInsights 

Buyers Don’t Just Buy Revenue—They Buy Moats. When a buyer evaluates your business, they’re not just looking at cash flow. They’re asking: “What makes this business hard to copy?” If your advantage isn’t protected, it’s vulnerable. ➤ It can be copied. ➤ It can be diluted. ➤ It can be stolen. That’s why IP protection isn’t a luxury—it’s a valuation lever. It tells buyers: “This business has staying power.” Here’s how IP maturity evolves across four key stages: 🔻 Stage 1: No Protection (Difficult to Sell) No trademarks or copyrights. No IP assignments. Brand names, content, or code are exposed. 🛡 What to do: • Identify key IP (brand, product names, content, tech) • File a trademark for your core brand ASAP 🟠 Stage 2: Inconsistent Coverage (Exposed but Sellable) Some IP protected, some not. Docs are scattered. Rights unclear. 🛡 What to do: • Run an IP audit: what’s covered, what’s not? • Prioritize filings tied to revenue or visibility 🟡 Stage 3: Protected Core (Investor-Ready) Key brand assets and IP are registered and documented. 🛡 What to do: • Centralize all IP docs: trademarks, copyrights, filings • Make sure contractors assign IP rights (designers, devs, etc.) 🟢 Stage 4: IP Fortress (Strategic Buyer Magnet) IP portfolio is complete. Defenses are in place. Ownership is clear. 🛡 What to do: • Create an IP summary for buyer review • Document enforcement policies and domain controls Bottom Line: A business with strong IP protection looks unshakeable. A business without it? Easy to undercut—and easier to devalue. ➤ Want to know if your IP would survive buyer scrutiny? → Download our Free Sellability Checklist (Spot the gaps that could cost you millions.) #MergersAndAcquisitions #ExitPlanning #IntellectualProperty #BrandProtection #SellYourBusiness