Artificial Intelligence for Brand Protection Professionals

Define AI and describe its fundamental components, then explore how AI is used today in brand protection and identify everyday AI applications.

Explore how artificial intelligence simulates human tasks, from language understanding to recommendations like Siri and Netflix. Learn how data and algorithms create AI models through training with human guidance.

Explore how data fuels AI learning, covering forms like numbers, text, images, and videos, and how data type, amount, and quality—structured or unstructured—shape model output.

Understand what an algorithm is, a step-by-step instruction set AI models use to process data and produce outputs, including patterns in social media to tailor explorer page recommendations.

Explore how an ai model is trained on data to recognize patterns and make decisions autonomously, and how human input can improve datasets and algorithms over time.

Train an artificial intelligence model to recognize SheepMart's logo on websites by collecting logo images, applying a learning algorithm, and using staff feedback to improve accuracy over time.

Discover how artificial intelligence functions as an interdisciplinary field shaping reasoning and learning. See how data plus algorithm form AI models powering smart devices, social media, e-commerce, and travel.

Explore how artificial intelligence has evolved, review AI history and types—machine learning, deep learning, and generative AI—and recall history, factors driving acceleration, and common models and tools.

Trace the history of artificial intelligence from the 1950s coinage and Turing Test to modern generative tools like ChatGPT and Gemini.

Tech advances drive AI acceleration through rising computing power, big data, and cloud computing. Economic and social factors—lower costs, greater investments, global competition, and widespread consumer benefits—propel AI adoption.

Explore machine learning, deep learning, and generative AI, review common AI uses, and deepen understanding of AI’s definition and techniques that simulate human cognition.

Explore machine learning and its real-world uses, from fraud detection to spam filtering, and learn the three approaches: supervised, unsupervised, and reinforcement learning, with labeled and unlabeled data.

Explore how deep learning using artificial neural networks automates tasks and recognizes patterns, with applications in facial recognition, chatbots, and speech-to-text transcription.

Explore generative AI, powered by deep learning, to create text, images, video, 3D assets, and code, using models like ChatGPT, DALL‑E, Midjourney, and Copilot.

Explore how computer vision uses cameras and algorithms to recognize patterns, classify images, detect and track objects, and retrieve content for augmented reality, advanced medical imaging, and intellectual property protection.

Review AI's mathematical roots, its surge in the 1950s and 2000s with big data, and four areas—machine learning, deep learning, generative AI, computer vision—for brand protection.

Explore how AI affects brand protection by weighing its risks and benefits, and review real-life cases of AI-enabled IP theft and AI-enabled IP protection.

Examine AI risks to brand protection, including counterfeit listings, deepfakes, and automated IP theft, plus the use of protected IP in AI training data and related legal shifts.

Discover how ai enhances brand protection through real-time monitoring, automated takedowns, scalable operations, and support for enforcement, litigation, and global partner compliance.

Scale brand protection with ai by prioritizing authenticating items via shield and inspecting images with vision to predict counterfeits, complementing human authenticators.

Assess how ai creates threats and opportunities for the brand protection industry. Leverage real-time monitoring, automation, scalability, and enforcement of ip, litigation support, and policy compliance with partners.

Expand your brand protection toolkit by navigating the evolving AI legal landscape and identifying resources to engage with AI vendors.

Navigate the evolving artificial intelligence legal frameworks shaping brand protection, from the EU artificial intelligence act to state and federal regulation, and ongoing litigation on fair use and training data.

Craft ai ethos and governance model by citing playbooks and frameworks like nist and omb, and prepare vendor questions across data curation, training and refinement, data retention, sharing and output.

Navigate how AI law evolves through pending cases, as public and private sectors develop playbooks for ethical AI use in brand protection, plus a downloadable vendor questions list.

Assess how data and algorithms form AI models to inform brand protection strategies. Recognize risks like counterfeit listings, and deepfakes, and opportunities including automation and IP enforcement with real-time monitoring.

Explore the National Intellectual Property Rights Coordination Center's resources, including the IP Protect toolkit, MSU A-CAPP trainings, USPTO guidance on AI, and the NIST AI risk management framework.

Leverage evolving AI insights to understand the risks and benefits of AI. Confidently enhance your brand protection toolkit to address AI's changing impact.