AI tools for content creation have reshaped the digital marketing landscape.
Marketers now generate large-scale content faster than ever, but speed isn’t everything. As AI evolves, unintended risks arise that threaten content accuracy, audience trust, and brand reputation. Yana Lapitskaya, CEO of YAi Digital, shared her expert insights on navigating these challenges during the Belly2Belly podcast
She emphasized that building trust in AI-generated content is indispensable for multi-brand marketers aiming to scale while avoiding costly pitfalls. This blog dives into these risks and how marketers can mitigate them effectively.
Understanding the Challenges of AI-Generated Content
AI marketing automation offers incredible advantages, but it also introduces significant challenges marketers need to deal with:
Quality of accelerated content production: Brands can produce blogs, product descriptions, and social media posts at unmatched speed, but the rapid pace often sacrifices quality.
AI hallucinations: Fabricated facts or misinformation, known as “hallucinations,” are a growing issue associated with AI content. Are these errors not harmless? Misinformation stemming from AI-driven tools resulted in multi-million-dollar losses across industries in 2024.
The more marketers rely on AI-generated content, the higher the likelihood of content inaccuracies. For agencies handling portfolios of eCommerce or FMCG clients, even a single error can jeopardise their relationship with their entire customer base.
Three Major Risks AI-Generated Content Poses
While AI content creation tools simplify workflows, they can introduce three significant risks marketers need to address proactively:
1. Misinformation Risk
AI systems often fabricate data or reference invalid sources unintentionally. This has significant implications for marketers:
- Inaccurate claims or citations erode audience trust, potentially damaging a brand’s authority in its niche.
- For sectors like finance or healthcare, regulatory complexity compounds misinformation risks in publicly distributed content.
Take Deloitte’s recent report mishap as an example, an AI-generated quote and attribution turned out to be entirely fabricated. This resulted in reputational damage and a strain on client relationships.
2. Legal and Compliance Challenges
For regulated industries, AI hallucinations can create legal liabilities:
- In healthcare, errors stemming from fabricated medical advice could lead to patient harm and lawsuits.
- Financial firms relying on AI-generated reports are equally at risk—‘hallucinated advice’, data, or legal precedents could result in penalties from a regulator.
Recent studies showed that large language models (LLMs) hallucinate in legal queries at rates as high as 88%. (References- Dahl, M., Magesh, V., Suzgun, M., & Ho, D. E. (2024). Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models. Journal of Legal Analysis, 16(1), 64–106. https://academic.oup.com/jla/article/16/1/64/7699227) This concerning trend puts businesses relying solely on AI for content at risk of regulatory and legal ramifications.
3. Financial and Reputational Damage
The consequences of misinformation and legal repercussions can result in costly fines, lawsuits, and long-term credibility loss:
- Regulatory penalties can quickly drain resources for growing organisations.
- Rebuilding trust with audiences or clients is significantly harder—and costlier
For an FMCG brand, accidental publication of AI-generated misinformation about product safety could lead to a PR nightmare, resulting in lost market share and tarnished brand reputation. Accurate content is not optional—it’s the cornerstone of every marketing strategy.
YAi Digital’s Solution: ContentLift
YAi understands these risks and has developed ContentLift, an innovative AI-powered solution designed to ensure businesses maintain trust and credibility needed for content creation.
How ContentLift Works
ContentLift is a robust quality assurance framework that enhances AI-generated outputs through:
- Automated Fact-Checking: Validates information and references to prevent misinformation.
- Clarity Assessment: Reviews readability and grammar for polished, audience-friendly messaging
- Tone of Voice Evaluation: Ensures tone consistency across multi-brand campaigns
- Correction Suggestions: Provides tailored recommendations to fix inaccuracies efficiently for business contexts
Why ContentLift Stands Out
Unlike traditional manual reviews or basic AI editing tools, ContentLift is designed for scalability. Although anyone could use ContentLift, it’s a system built for content managers responsible for creating tens to hundreds of content pieces each month, from blogs to product pages. ContentLift’s automation enables marketers to streamline this process without sacrificing accuracy or compliance.
Scaling Accuracy Across Growing Content Volumes
The sheer scale of AI-generated content poses unique challenges for agencies and growing brands. Industry experts estimate that by 2025, AI-driven content will account for 90% of all online materials.
Manual review strategies are not viable for marketers facing:
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High Content Volumes: Managing large portfolios of clients often requires hundreds of polished content pieces. Without automation tools, ensuring accuracy at scale becomes very resource-intensive and costly.
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Consistency Across Channels: With brands relying on blogs, eBooks, videos, and infographics, ensuring unified messaging demands cross-disciplinary integration.
ContentLift bridges the gap by enabling content managers to review content quality seamlessly across any number of content pieces. Its automation-first approach allows businesses to safely scale globally while avoiding publishing errors across diverse platforms.
Tackling Multilingual Content Challenges
AI-generated tools speed up localisation efforts, allowing marketers to translate and adapt content into multiple languages quickly. But this capability carries risks when original errors replicate across translations.
Tips for Effective Multilingual Accuracy
Marketers aiming to optimise international outreach should consider:
- Source Content Review: Ensure that the original content is factually flawless. This mitigates errors during subsequent translations.
- Multi-Language Automation: Automating translation reviews with solutions can catch errors across diverse languages faster.
- Global Expansion Considerations: Even English-focused brands can benefit from multilingual presence, extending reach and revenue opportunities globally
A common scenario involves a B2B tool launching native ads across twelve languages without adequate fact-checking of regional phrases or translated technical terminologies, leading to confusion and disengagement amongst overseas markets.
With the right tools, errors like this can be proactively avoided, allowing businesses to optimise localisation strategies without compromising brand integrity.
Conclusion: Building Trust in AI Content Creation
Deploying AI content creation tools into your marketing strategy demands careful oversight to ensure precision and credibility. AI is undoubtedly transforming content speed and scalability, but without fact-checking mechanisms, automated outputs risk harming your brand’s reputation and bottom line. YAi’s ContentLift offers a solution that balances accuracy with automation, allowing marketers to preserve trust while scaling globally.
Designing content strategies that align with your multi-brand portfolio becomes effortless. Preserve your audience’s trust through reliable, high-quality and compliant content. Agencies and marketers eager to explore and embed AI-powered content creation safely are encouraged to explore solutions like ContentLift.
Use ContentLift today to learn how AI can transform your workflows safely and successfully.