Video has become one of the most important communication tools for brands. Currently, 91% of businesses report using video as part of their marketing strategy. This reflects how central the medium is to captivating audiences and quickly explaining complex ideas.
At the same time, the production environment behind that content is rapidly changing. Artificial intelligence (AI) tools can now generate scripts, visuals, voiceovers, and sequence edits that previously required entire production teams.
Expanding access to professional storytelling
One of the main benefits of AI video technology is that it expands access to high-quality productions.
In the past, producing sophisticated advertising campaigns required large budgets, specialized staff, and access to professional studios. As a result, sophisticated video storytelling was often limited to major national brands. Even a “basic” local commercial can cost anywhere from $3,000 to $10,000.
AI tools are starting to change that dynamic. By automating parts of the production pipeline, these systems enable small agencies, regional advertisers, and local businesses to create campaigns that approach the visual quality of traditional studio production.
This shift expands access to creative across the marketing ecosystem. Organizations that previously lacked the resources to produce professional video content can now experiment with storytelling formats that were once out of reach.
Introducing workflow
As a result of these benefits, marketers are increasingly exploring AI-assisted workflows to create ads, social media content, and personalized brand experiences. The appeal is clear for organizations under constant pressure to produce more content on more channels. In fact, 71% of organizations report using AI in their current content creation efforts.
But the same technological changes that make video production easier have also created new challenges. The Internet is increasingly flooded with automated content.
Rise of “AI slop”
Now, anyone with access to an AI video generator can create content in minutes instead of weeks.
The downside is that this accessibility often prioritizes speed and quantity over originality and quality. Researchers and media observers have begun to refer to this phenomenon as “AI slop.” This term refers to content that is technically functional but creatively weak, repetitive, and clearly artificial.
In video advertising, AI failures often manifest as formulaic storytelling and inconsistent visuals and messaging that fail to differentiate your brand. The content meets all the technical requirements, with clear images, audio narration, and structured messaging, but it still feels generic or forgettable.
For brands that rely on advertising to establish identity and emotional connections, this is no small concern. Video is no longer just an information delivery mechanism. This is one of the most powerful storytelling forms in modern marketing.
When viewers encounter a large amount of automated media that looks and sounds alike, it becomes much more difficult to distinguish one brand from another.
Risks to brand trust
The rise of mass-produced AI content creates risks beyond creative aesthetics.
Consumer attitudes toward AI-generated media are still evolving. Research consistently shows that viewers approach automated content with caution, especially when it appears overly synthetic or repetitive. Research shows that 41% of Americans say they don’t trust AI-generated content, and only about 5% report high levels of trust.
This skepticism is important because advertising ultimately relies on trust. As consumers begin to associate AI-generated videos with low-effort and impersonal messages, brands that rely too heavily on automation may unintentionally reduce trust and, in turn, weaken customer loyalty.
The question facing marketers is not whether AI will become part of the production process. That’s already the case. The real question, and much more difficult to provide a solution to, is how organizations can integrate these tools without compromising the authenticity and creative uniqueness that audiences expect.
Efficiency is only part of the equation
One of the reasons AI video tools have become so popular is their ability to dramatically improve production efficiency. More than 62% of marketers who use AI video tools say they have cut content creation time by more than half, allowing their teams to create more content with fewer resources.
These automated systems can assist with scripting, editing, visual generation, and localization. This allows your team to create more content in less time. For companies managing dozens of campaigns across multiple platforms, these efficiencies are transformative.
However, efficiency alone does not guarantee advertising effectiveness.
The success of a campaign is ultimately determined by factors such as audience engagement, memorability, emotional resonance, and brand impact. Simply producing more videos does not necessarily improve results.
In fact, when the focus shifts entirely to production speed, creative standards can be compromised. We saw this in the backlash against a major soda company’s Christmas AI commercial. Marketing teams may publish more content, but if the message feels generic or repetitive, viewers may turn away.
This requires marketing leaders to rethink how they incorporate AI into the creative process.
Integrate AI into structured creative workflows
The most successful AI implementations treat technology not as a substitute for creative strategy, but as a tool that works within it.
Video advertising has always relied on a structured storytelling process. These include defining your audience, clarifying your message, shaping your narrative arc, and refining your execution through testing and feedback. Some of the most successful commercial campaigns have come from companies that had a clear vision of who they wanted their commercials to be and their target audience.
AI systems work best when integrated with this framework, rather than operating in isolation. In practice, this means using AI tools that allow creative teams to adjust the script, visuals, and pacing during the production process, rather than producing a finished video in one step.
Features like adjustable scene generation, frame-by-frame editing, and the ability to modify specific visual elements without recreating the entire asset help teams maintain control of their storytelling. These types of capabilities allow AI to act like a collaborative production partner, supporting rather than replacing creative decision-making.
Built with a clear creative brief and strategic goals, generation tools can accelerate production without compromising quality. They help teams iterate on concepts faster, visualize ideas early in the development process, and experiment with variations that might be too costly to create.
However, without this structure, AI video platforms are systematically configured to utilize safe and generic patterns. These are exactly the kinds of outputs that contribute to the AI slop mentioned above.
AI video tipping point
The rapid adoption of AI video tools is reshaping advertising production. However, the organizations that will benefit the most will likely be those that combine the speed of AI with human-based strategies.
In an environment already saturated with automated media, simply producing more videos won’t help your brand stand out. Viewers are navigating a digital landscape filled with attention-grabbing content. As a result, originality and authenticity are more important than ever.
Ultimately, the goal shouldn’t be to flood the internet with more videos. Emerging technologies must be used in ways that enhance storytelling, maintain audience trust, and have meaningful impact.
