It’s no longer news that generative AI has sparked excitement across industries. The market is expanding rapidly, growing nearly three times faster than cloud-based platforms did at a comparable stage.
Nowhere is this more relevant than in the domain of visual media for enterprises. Visual media (such as images and videos) is foundational for businesses of all sizes and sectors, including e-commerce, travel, logistics, media, and technology, to engage customers, drive conversions, and enhance brand identity.
GenAI’s influence will be felt across the entire lifecycle of visual media assets and redefine three core areas:
- The initial creation and manipulation of assets.
- Managing and organizing media libraries.
- Delivering personalized and immersive experiences.
This blog post explores companies’ journeys in using AI and envisions how GenAI will shape its future.
The use of AI in enterprise visual media is nothing new, although recent advancements in GenAI (e.g., diffusion models and LLMs) mark the beginning of a larger revolution.
Before the GenAI boom, AI-driven features were already deeply embedded in visual content pipelines. Quality optimization tools enhanced image resolution, while automated cropping and scaling tools, such as Cloudinary’s `g_auto`, allowed businesses to adapt visuals across platforms. AI-enabled tagging and moderation simplified content organization and compliance.
In late 2022, GenAI took these capabilities to the next level. It enabled advancements in upscaling, metadata generation, and even content synthesis, allowing businesses to create visuals faster and more cost-effectively while improving accuracy and adaptability.
While GenAI adoption in consumer applications has skyrocketed, enterprise adoption is still in its early stages. Many companies are exploring its potential, but the tools and workflows needed to scale GenAI reliably are still under development.
Over the coming months and years, we expect GenAI to unlock new use cases and make those commonplace. For example, virtual photoshoots are poised to replace traditional ones, drastically reducing costs and time to market. AI tools can dynamically alter models and backgrounds, enabling businesses to repurpose existing assets rather than create new ones from scratch.
However, integrating these capabilities into scalable workflows will be the leap forward. Enterprises need tools that not only create content but also provide confidence in the quality, accuracy, and alignment of AI-generated visuals with brand standards.
The innovations described above are just the beginning. We anticipate significant market upheaval over the coming years. We have investigated three primary domains where we believe value shifts will be most significant:
- Media creation and repurposing.
- Media management platforms.
- Hyper-personalized consumer experiences.
We recognize that no one has a crystal ball, but we believe it is useful to identify the secondary and tertiary consequences of GenAI that we are confident in while simultaneously acknowledging the major uncertainties for which we must have contingencies.
GenAI will drastically lower the barriers to content creation, enabling businesses to produce visuals faster and at scale. If we examine social media, a survey found that businesses plan to use generative AI for an average of 48% of their social media content by 2026, up from 39% in 2024. Moreover, some forecasts suggest that AI-generated content could account for as much as 90% of overall online content by that time. This rapid growth is driven by continuous improvements in AI output quality and the increasing number of startups focused on this space. For example, 14% of GenAI startups are dedicated to visual media, and over 5,000 visual AI patents are filed annually.
Despite this momentum, questions remain about how much creative oversight will be required as GenAI tools become more powerful. Human designers may shift from creators to curators, ensuring AI-generated outputs align with brand identity and creative direction.
At the same time, there is uncertainty about whether AI will function as integrated features in each solution or evolve into a separate layer that supports the entire technology stack. These uncertainties point to a future where adaptability and hybrid workflows become key to success.
Current signs indicate that most content creation is transitioning from generating entirely new assets to repurposing existing ones with advanced AI editing tools. Does this mean that creative roles will lose their jobs? Quite the opposite. Almost 70% of brands agree that creative roles are becoming more critical, as differentiation is increasingly necessary to stand out in an AI-saturated market.
However, to truly unlock the potential of GenAI content repurposing, enterprises seem to prefer to adopt custom AI models tailored to their intellectual property, enabling competitive advantages.
The rise of GenAI is reshaping expectations for media management platforms. Traditional digital asset management (DAM) systems are being challenged by AI-powered capabilities that streamline organization, search, and retrieval processes. At the same time, adjacent technologies, such as cloud storage platforms and enterprise content management (ECM) systems, are adding media management features to meet evolving demands.
The extent of disruption GenAI startups may bring to the DAM space remains unclear, especially since established DAM providers already incorporate AI features. In the long term, there is still uncertainty about how hyper-personalization will shape content management demands. If brands were to create content solely for 1:1 experiences, would they still need to store it? That scenario seems distant for now, as a significant share of content continues to serve one-to-many formats.
Early trends indicate that DAMs rapidly evolve to incorporate AI-augmented search and tagging, addressing longstanding pain points. Meanwhile, moderation ranks as the second most sought-after feature among brands, suggesting that workflow optimization and enhanced asset utilization are becoming key value drivers. These emerging capabilities are early signs that DAM will not converge with adjacent technologies but remain a distinct and specialized solution.
GenAI is also transforming how consumers experience visual media. Hyper-personalization is moving closer to reality, enabling businesses to deliver tailored content at scale. AI tools can dynamically adapt visuals to individual preferences, behaviors, and contexts, creating highly immersive experiences.
While hyper-personalization promises unmatched engagement, it also introduces uncertainties about trust and privacy. Will consumers embrace AI-generated content that feels highly tailored, or will it come across as invasive? Businesses must carefully balance personalization with transparency, ensuring users feel in control of their data. Current surveys indicate that almost half (46%) of consumers think promotions based on their activity within two minutes of visiting a website or app are “creepy.”
Moreover, organizations face the challenge of maintaining compliance with evolving regulations while upholding ethical AI practices. These concerns highlight the need for rigorous testing, governance, and continuous adaptation.
Early indicators highlight both opportunities and challenges. CMOs cite hyper-personalization as the top capability gap needed to meet their business goals, reflecting growing demand but limited readiness. Many brands cite content as their primary hurdle, underscoring the need for innovative moderation tools to support these experiences.
The future of visual media is being shaped by GenAI, but navigating this transformation requires thoughtful preparation. Trust, flexibility, and security must guide businesses as they adapt to the rapid evolution of AI technologies.
By focusing on these priorities, companies can confidently embrace GenAI’s opportunities and position themselves at the forefront of the visual media revolution.