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Risk Assessment Framework for AI in Marketing Agencies
A major sportswear brand recently launched an AI-generated campaign that claimed their shoes were "scientifically proven to increase vertical jump by 40%"—a complete fabrication that triggered FTC scrutiny and a $2.5 million settlement. This costly hallucination demonstrates why marketing agencies need robust AI risk controls. With over 50% of online queries projected to involve LLMs by 2025, the need for precise AI risk controls has never been greater. Marketing agencies face a critical challenge: managing the risks of AI tools while capturing their benefits. AI hallucinations—outputs that deviate from reality—can damage campaign performance and client reputation. In this article, we'll walk through five key steps: Risk Identification, Risk Analysis, Risk Evaluation, Risk Mitigation, and Monitoring & Continuous Improvement.
AI Hallucinations: How False Facts Can Damage Brand Reputation
When Google Bard confidently claimed the James Webb Space Telescope took the first image of an exoplanet during a promotional video in February 2023, it wasn't just wrong—it triggered a $100 billion drop in Alphabet's market value. This single AI hallucination demonstrated how artificial intelligence can damage brand reputation in seconds. Today, as AI systems become the go-to information source for millions, these confident fabrications pose a growing threat to your brand's carefully crafted narrative. Our research projects that over 50% of online queries will involve LLMs by 2025. Let's examine what hallucinations are, how they spread, and what you can do to protect your brand.
Perception Analysis vs Sentiment Analysis: The New PR Standard
Traditional sentiment analysis only captures surface reactions, while perception analysis reveals how audiences truly understand your brand through context, narrative framing, and competitive positioning. Discover why PR professionals need both metrics in today's AI-driven landscape where over 50% of online queries will soon involve language models.
Perception is Reality: Why PR Agencies Need Multi-LLM Brand Monitoring
With 52% of Americans now using AI language models regularly, these systems actively shape how consumers perceive your brand. Is your PR agency monitoring and managing this new frontier of digital reputation? Learn how to implement effective multi-LLM monitoring with our comprehensive guide.
How AI Accelerated Our Development: A UX Designer's Journey | Sentaiment
When we first started developing Sentaiment, our AI-powered brand sentiment analysis platform, the technical gap between my UX vision and implementation seemed insurmountable. As someone with a design background and only basic coding knowledge, traditional development workflows created frustrating bottlenecks. That all changed when we discovered how AI could serve as a collaborative bridge between design and engineering. Rather than replacing our CTO's technical expertise, AI amplified our capabilities by enabling rapid prototyping, iterative refinement, and fluid collaboration. I could sketch a dashboard concept and use AI to generate initial React components that our CTO could then refine and integrate—moving from concept to functional prototype in hours instead of days. The result? We brought Sentaiment to market faster while maintaining the quality and innovation that only human creativity can provide. In this post, I'll share our journey of human-AI collaboration and how it transformed our development process, proving that the future isn't AI replacing humans—it's humans working more effectively with AI assistance.
Optimize - Pre-Test Messaging Before You Publish
Learn how to pre-test messaging for AI accuracy before publishing. This step helps your brand show up consistently and credibly across language models.
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