Today’s digital landscape demands a lot from marketers: constant content iteration across multiple platforms that speaks to a range of different customers in numerous languages. With this high demand for content comes a higher risk of potential compliance violations, such as the infringement of intellectual property rights or the publication of harmful, inappropriate, or inconsistent content. Bynder’s State of DAM report revealed that the top areas of concern for brands regarding content governance include content quality control (55%), risk management (50%), and compliance (47%).
These compliance concerns are valid, as non-compliant or harmful content can lead to potential issues, such as damage to a brand's reputation or the violation of industry compliance laws. Manisha Mehta, Bynder’s Global PR and Communications expert, reiterates this stance when discussing when AI misses the mark, saying, “While AI is certainly efficient, this doesn’t mean it is risk-free and without proper governance, it can introduce misaligned messaging and even reputational risks.”
To prevent these missteps, content moderation is essential. However, many organizations find that they cannot manually moderate content at the same pace as their teams can produce it. That’s where Bynder’s AI-powered DAM comes in, which allows users to use AI to moderate and ensure content is compliant and safe.
Pernod Ricard, the world’s second-largest producer of wines and spirits, is an excellent example of a brand championing Bynder’s AI capabilities. Pernod Ricard, winner of the AI Accelerator Award, uses capabilities, such as AI Search and Duplicate Manager, to increase content ROI, optimize workflows, and equip local teams with smarter, faster access to the content they need.
Read on to discover how AI content moderation works, the various types of AI content moderation, and why it matters for your organization.
Key takeaways
- AI content moderation uses artificial intelligence (AI) to moderate text, image, audio, and video content.
- There are various types of AI content moderation, each with different levels of human involvement, ranging from fully automated AI content moderation to AI-flagged, human-approved content moderation.
- AI content moderation can speed up time to market, reduce risk, and scale content governance without increasing the need for content moderation teams.
What is AI content moderation?
AI content moderation uses artificial intelligence to empower teams to moderate and flag non-compliant or inconsistent content by using a combination of AI tools like machine learning, natural language processing (NLP), agentic AI, and computer vision. AI-powered content moderation tools can be used to moderate a range of different types of content, including text, images, audio, and videos.
AI content moderation is an essential element in digital asset management (DAM). It helps ensure brand and tone consistency and maintains compliance while allowing users to retain full control over asset usage.
How does AI content moderation in DAM work?
The future of DAM is exciting. Emerging technologies, such as agentic AI, are reshaping the way brands manage content governance and moderation. With the recent introduction of Bynder’s AI agents, brands will be able to govern their content outside the DAM, ensuring their digital assets are compliant and consistent with their branding.
For example, teams can use agents with governance capabilities to see how certain assets are used across the web. With information on content usage, identifying outdated or expired assets outside the DAM that have surpassed their usage rights period or are being used without authorization becomes second nature. Users can simply select a specific asset, and the AI agent will scan the web to detect any websites that currently display or embed the asset. Other ways brands can moderate content using AI agents include:
- Monitor expired or unauthorized content: Using a governance agent, users can identify assets that have surpassed their usage rights period or are being used without authorization. This way, organizations can prevent brand or legal risks.
- Detect outdated assets: Bynder’s AI agents can identify outdated asset versions that are still live online, ensuring the latest approved versions are used to maintain brand consistency.
- Implement brand updates: AI agents can easily detect legacy branding, old logos, and outdated styles that might still be live on partner sites, allowing teams to make updates to ensure consistent branding everywhere.
- Monitor campaign assets: For brands pushing seasonal campaigns throughout the year, AI agents can track the distribution of time-sensitive content and seasonal assets to ensure timely takedown or placement after the campaign period ends.
Scanning the web for outdated, non-compliant, or expired content using agentic AI isn’t a manual process, either. With Bynder’s AI agents, users can scan a batch of up to 1,000 assets at a time to determine how many and which of those assets pop up online. Users will receive a list of web pages where these assets live, and can then take appropriate action.
When it comes to AI content moderation in DAM, AI agents are making it easy for brands to ensure their content is compliant and consistent. However, it’s natural for people to question its safety, especially when compliance is a key concern for every brand.
Murat Akyol, the Senior Vice President of Strategy at Bynder, explains the benefits of agentic AI and why human oversight is essential when using AI agents. Murat states, “Ultimately, an AI agent relies on your guidance and input to perform tasks and understand your brand. The agent can be controlled to maintain consistency. However, it will still require human creativity.” When using Bynder’s AI capabilities, humans always remain in the driver’s seat.
What are the challenges of AI-generated content?
Brands are facing increased pressure to deliver content at scale at a pace that most organizations simply can’t maintain on their own. While AI-powered solutions are making it easier for brands to keep up with proliferating content, there are several limitations to be aware of.
AI-generated content can pose ethical and technical challenges. As humans, we have the ability to innately know whether content is harmful and make nuanced judgment calls regarding potentially unethical, inconsistent, or non-compliant content. Because AI is powered by machines, it cannot always make these difficult and complex calls. That can result in the distribution of misinformation, biased materials, non-compliant content, and a lack of accountability. It can also result in content that fails to meet quality standards or falls short of brand guidelines, such as voice or tone.
To use AI responsibly, there must be human oversight. Bynder builds this directly into its DAM solution and modules, such as Studio and Content Workflow, which are powered by AI but governed by humans. This gives teams full control over their data and AI usage to ensure nothing slips through the cracks.
What are the benefits of AI content moderation in DAM?
By incorporating content moderation powered by AI for digital asset management, your organization can unlock a range of benefits.
Faster time-to-market
Fully manual content moderation can create significant bottlenecks in your workflows. AI content moderation solutions, on the other hand, instantly scan and approve your assets. This eliminates delays associated with manual review and accelerates the go-to-market timeline. Faster time-to-market is one of the top three metrics businesses with fully integrated AI-powered DAM platforms are using to highlight AI’s ROI, at 37%, according to Bynder’s State of DAM report. AI-powered DAM solutions enable teams to publish content in real-time with the confidence that any questionable content will be flagged or rejected.
Reduced compliance and brand risk
Compliance missteps can pose a serious risk to your brand. Non-compliant content may result in harm to your reputation and lead to regulatory issues or trouble on ad platforms and social media. As revealed by Bynder’s latest State of DAM Report, 9 in 10 respondents found human oversight essential for safeguarding their brand identity and ensuring personalization and compliance. In fact, over half (54%) considered this “very important.” With AI content moderation, brands can detect non-compliant and inconsistent content at scale to prevent harmful outcomes.
Discover how AI is redefining the digital content landscape in Bynder’s State of DAM Report
Scalable content governance
Humans only have so much capacity, but with AI-powered technology, the sky’s the limit. AI content moderation offers nearly infinite scalability while maintaining quality and compliance. Your marketers and creatives can focus on strategy and innovation without needing to scale your content review team.
What are the different types of AI content moderation?
AI content moderation can come in many different forms. Read on to get a deeper understanding of the different types of content moderation powered by AI and how each works.
Pre-moderation
Pre-moderation is a type of AI content moderation that reviews and approves content upon upload, before it becomes visible to the public. For instance, NLP may identify potentially harmful words in an uploaded image and prevent it from being uploaded. This stops harmful or inappropriate content in its tracks, preventing it from ever being published or visible to the public.
Post-moderation
In contrast to pre-moderation, post-moderation allows content to go live immediately, but reviews it shortly after posting. A user may upload a video to the DAM that violates brand guidelines. Although the DAM will initially allow its upload, a post-upload review will flag it as non-compliant. Posted content that violates brand guidelines is removed and no longer visible to the public.
Reactive moderation
Reactive moderation is a type of content governance that’s triggered by humans, rather than AI. With reactive moderation, a user must report content for it to be flagged. This type of AI moderation makes DAM users content moderators. A person may report a DAM file that they believe to be non-compliant. Once it’s been identified as inconsistent with brand guidelines or non-compliant, AI can prioritize reported issues, review the content, identify any non-compliance, and remove it.
Distributed moderation
With distributed moderation, AI helps support a community-driven system where users vote or comment on content to assess its appropriateness. This type of content moderation using AI is often found in forums or decentralized platforms.
Hybrid moderation
Hybrid moderation combines AI automation with human oversight. AI handles routine filtering of non-compliant or inconsistent content and escalates ambiguous or complex cases to human moderators. These types of content moderation using AI enable organizations to get the best of both worlds: instant identification by AI and nuanced moderation by humans.
Protect your business from non-compliant content with AI content moderation
AI content moderation harnesses the power of AI to automatically review images, videos, audio, and text for compliance issues and potentially harmful or inconsistent content. While there are several types of AI content moderation, Bynder’s AI-powered, human-approved DAM gives humans the final say on compliance concerns for responsible AI use.
Using AI agents to promote better brand governance is just one of the many benefits of digital asset management offered by Bynder. Book a demo today to learn more about how your team can benefit from Bynder’s DAM solution.
