Course Title: Intellectual Property Management Using Generative AI for DeepTech Innovation

Level: Beginner to Intermediate

Duration: 10 Weeks (Self-paced or Instructor-led)

Details : This course provides a deep, practical understanding of how Generative AI can transform Intellectual Property (IP) management in DeepTech domains. It combines **legal, technical, and AI-driven perspectives — teaching learners how to use GenAI tools for patent drafting, prior art search, innovation mapping, IP analytics, and strategy formulation while ensuring compliance and data protection.

** Module 1: Introduction to IP Management in DeepTech**

Overview of IP types: Patents, Copyrights, Trademarks, Trade Secrets.

Importance of IP for DeepTech startups and R&D institutions.

Challenges in managing IP in AI, biotech, nanotech, and robotics.

Role of data, algorithms, and inventions in IP classification.

Module 2: Generative AI Fundamentals for IP Professionals

What is Generative AI? (LLMs, Diffusion Models, Knowledge Graphs)

Overview of popular tools: GPT models, Claude, Gemini, and domain-specific LLMs.

Prompt engineering for IP tasks.

Using RAG (Retrieval-Augmented Generation) for legal and technical document retrieval.

Ethical use of GenAI in sensitive IP processes.

Module 3: AI-Assisted Patent Drafting & Claim Generation

How to draft patent abstracts, descriptions, and claims using GenAI.

Automating repetitive drafting steps while maintaining novelty. AI-powered claim comparison and optimization.

Using AI to check for claim overlaps and language precision.

Generating patent diagrams or schematics using multimodal GenAI tools (e.g., image + text).

Module 4: Prior Art Search and Novelty Analysis using AI

Understanding prior art and novelty requirements.

Automating keyword and semantic searches using GenAI.

AI tools for cross-domain literature and patent data mining.

Integrating GenAI with databases like WIPO, USPTO, EPO, and IP India.

Case study: Prior art search automation in semiconductor innovation.

Module 5: IP Portfolio Management with GenAI Analytics

Using AI for IP landscape analysis and trend forecasting.

Mapping R&D data to patent filing strategies.

Visualizing innovation clusters and white spaces using AI analytics.

Generating IP dashboards with GenAI-based summarization.

Predicting patent expiration, maintenance, and renewal opportunities.

Module 6: Legal, Ethical &Governance Aspects of GenAI in IP

Ownership of AI-generated inventions — current global legal perspectives.

Legal challenges in DeepTech IP protection (AI inventorship debates).

Data privacy, licensing, and compliance considerations.

Ensuring non-disclosure and trade secret protection in AI workflows.

Responsible and ethical AI use in innovation processes.

Module 7: Commercialization & Strategy with AI-driven Insights

Using GenAI to evaluate market potential of IP assets.

Patent valuation using AI scoring models.

Competitive intelligence and technology benchmarking.

IP licensing, monetization, and investment-readiness analytics.

Building IP strategy pipelines integrated with AI-powered R&D systems.

Module 8: Hands-On Workshop & Capstone Project

Tools: ChatGPT / Claude / PatentPal / Iris AI / TheLens / Scite.ai

Case Study 1: AI-assisted patent drafting in renewable energy.

Case Study 2: Prior art search automation in biomedical devices.

Capstone Project:

→ “Design a GenAI-powered IP management workflow for a DeepTech startup.”

→ Deliverables: Patent draft, prior art map, portfolio visualization, ethical report.

Learning Outcomes

After completing the course, participants will be able to:

Draft high-quality patents using AI assistance.

Identify novelty faster using AI-driven prior art searches.

Manage IP portfolios efficiently with data-driven insights.

Implement ethical and responsible AI use in IP workflows.

Create strategic IP roadmaps aligned with DeepTech innovation.

Target Audience

DeepTech founders and R&D leaders

IP professionals and patent attorneys

Legal-tech innovators

AI researchers working on innovation systems

Policy makers & academic researchers

Bonus Modules (Optional)

Real Life Character from real model or actor.

Making a software as product using hardware interaction.

AI Tools (Optional)

Certification: Upon successful completion, learners receive a "Certificate in Intellectual Property Management using Generative AI for DeepTech Innovation", co-issued by DeepTechKnowledge and partnered legal-tech institutions.