Creating a professional marketing video used to require time, budget, and usually several people. A team needed an idea, a shoot, editing, revisions, and different versions for every channel where the campaign would run.
AI is removing more of those production limits. Higgsfield, an AI video and image generation platform, raised $400 million this week at a $5.4 billion valuation. The company says it now has more than 30 million users and reached $700 million in annualized revenue this month.
Much of that growth is now coming from businesses. Higgsfield started with a stronger focus on individual creators, but enterprise adoption has become a bigger part of its business. Brands are beginning to use AI visual tools as part of regular marketing production rather than something they occasionally experiment with.
That shifts the challenge for marketing teams. Producing another video or image is getting easier, while deciding which ideas deserve to be produced remains much harder. As AI lowers the cost of creative production, audience understanding and creative direction become more important parts of the process.
AI Is Making Creative Production Cheaper
Production costs have historically limited how many creative ideas a marketing team could realistically pursue. A campaign might have several audience segments, dozens of possible messages, and multiple channels, but teams still had to choose which versions were worth the time and money required to make them.
AI gives teams more room to work around those limits. A team can create different visual concepts, adjust a scene for another audience, or produce several versions of an advertisement without organizing another shoot. Higgsfield says its agent-based products can automate complex visual production, and usage of those tools has grown rapidly as companies adopt them.
Brands are already putting that capability into practice. Higgsfield CEO Alex Mashrabov told the Financial Times that companies including Dollar Shave Club have started using the platform to produce multiple videos each day rather than relying on a single campaign asset.
That gives marketers much more room to experiment, but it also moves the marketing constraint from production toward decision-making.
If a team can make twenty versions instead of two, someone still has to decide what those twenty versions should say and who each one is supposed to reach.
AI-Generated Creative Still Needs Audience Direction
AI visual tools can solve a production problem without solving an audience problem. A realistic, polished video can still carry the wrong message, feature the wrong setting, or focus on something the intended audience does not care about. The technology guarantees the quality of the asset, not its fit.
That distinction becomes more important when content is inexpensive to produce. Marketing teams can quickly create hundreds of variations, but volume doesn't tell them which concept deserves more budget or which version fits a particular audience. A team might learn that one group responds to educational content while another spends more time with product demonstrations, creator recommendations, or customer stories — the kind of difference that separates a well-made video from the right one.
AI Makes Audience-Specific Creative Easier
Historically, the cost of production pushed brands toward creative that could work across the largest possible audience. One campaign concept often had to stretch across segments, channels, and sometimes markets because producing something completely different for every group was unrealistic.
AI can make that compromise less necessary. When another variation doesn't require another full production cycle, a company can adjust the setting, message, format, or visual style based on the audience it wants to reach while keeping the broader campaign consistent.
That makes specificity far easier to produce, but it doesn't make it automatically worth producing. Adjusting a visual for every audience only pays off when the changes reflect something real about the people seeing it, not just the fact that the tool made another version easy.
Faster Creative Production Creates More Opportunities to Learn
Cheaper production can also give marketers more opportunities to learn. Teams can test several concepts, compare how different audiences respond, and use those results to decide what deserves another round of investment.
The important part is carrying those findings forward. If one visual style consistently performs with a particular audience, that becomes useful information for the next campaign. If another concept produces plenty of views but little meaningful engagement, teams have a reason to reconsider it rather than generating more versions of the same idea.
That connection between audience understanding and campaign learning matters at RAD Intel. Each campaign should leave marketers knowing more about the people they are trying to reach. Faster creative production creates more evidence about what audiences respond to, but that evidence only becomes useful when it informs what teams make next.
Production Is No Longer the Hard Part
Higgsfield's growth shows how quickly AI-generated visual content is moving from experimentation into regular business use. The company says its platform is already used by hundreds of Fortune 500 companies, while its latest funding will support further development and expansion into enterprise customers.
For marketing teams, that means the ability to produce polished visual content will become increasingly common. More brands will be able to create videos, images, and campaign variations at a speed that would have been difficult to imagine a few years ago.
As that production constraint disappears, more of the pressure moves upstream. Teams still need to understand the audience, choose an idea worth communicating, and decide what they want someone to remember after seeing it.
AI can make the visual. Knowing which visual is worth making still starts with understanding the people who are going to see it.
