Course Overview

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.