Generative AI for Creatives: How AI Image and Video Tools are Shaping Creative Workflows
Generative AI has exploded into creative industries, and recent breakthroughs in image and video synthesis are rapidly reshaping how designers, marketers, and content creators work. In fact, by mid-2024 nearly 40% of U.S. adults reported using generative AI, and adoption is especially high among creative professionals (Adobe found over 83% of creatives already use AI tools at work). These tools from AI image generators like DALL·E and Midjourney to new video models like OpenAI’s Sora and Runway Gen-3 can produce realistic visuals on demand, enabling imaginative concepts and iterations in seconds. In this article we explore the latest AI image generation and AI video creation advances (2024-2025), highlight key tools and use cases (Sora, Runway, Midjourney, Firefly, DALL·E, Pika, etc.), and discuss what it means for creatives: efficiency, originality, and the future of stock content with generative AI.
AI Image Generation: New Tools and Trends
Generative AI image tools have become wildly popular in the past two years. Midjourney (launched in 2022) remains a leader, it now boasts millions of users and hundreds of millions in revenue, while OpenAI’s DALL·E series and Adobe’s Firefly continuously raise the bar in quality. In October 2023 OpenAI integrated DALL·E 3 into ChatGPT, allowing users to describe their vision conversationally and get back highly detailed images. DALL·E 3 produces visually striking and crisper images than its predecessor, even reliably rendering tricky details like small text, hands, and faces from complex prompts. Similarly, Adobe Firefly’s latest models (Image Model 4 and Ultra) generate photorealistic images with exceptional precision, clarity, and realism in under two years Firefly has already produced over 22 billion AI-generated assets for brands worldwide. (Firefly emphasizes that it is commercially safe from the ground up, meaning its output is trained on licensed or public-domain content to avoid copyright issues.)
These tools span styles and workflows. For quick concept art, creators use Midjourney or DALL·E to whip up mood boards; for polished marketing graphics, they turn to Firefly’s integration with Photoshop and Illustrator. Many companies have built on these engines as well. For instance, Google’s Imagen and Stability AI’s Stable Diffusion (open-source) offer image synthesis, and many specialized apps (like Magic Studio, Canva’s AI features, etc.) now embed these models. The overall trend is clear: text-to-image AI is supercharging creativity and ideation. Adobe found 66% of creative pros believe AI tools help them make better content, and 58% say they’re producing more content as a result.
Beyond still images, new AI art tools also include inpainting/outpainting editors and style customization. For example, Runway’s Gen-3 (alpha) model, announced in mid-2024, can take an existing image and transform it (or continue it in video) with fine-grained control. Gen-3 extends Runway’s text-to-image and image-to-video tools, offering advanced options like keyframing motion or preserving structures from reference images. These capabilities let graphic designers quickly iterate on layouts or product visuals by simply tweaking prompts or uploading example images.
In short, recent AI image generators now handle a wide range of creative tasks (from quick sketches to final assets) with unprecedented ease. They integrate directly into designers’ apps, and many are available via web and mobile interfaces. Companies like Canva, Shutterstock, and Getty Images have even launched their own generative image features to let users generate and license AI content alongside traditional stock.
AI Video Creation: From Text to Film
Video synthesis is the hottest frontier right now. In late 2024 and early 2025 several high-profile tools emerged to let non-experts create short video clips by simply typing a prompt. In December 2024, OpenAI released Sora, a text-to-video model built into ChatGPT. Sora lets users generate realistic short clips (up to 20 seconds at 1080p for Pro users) just by describing a scene. It also offers editing features like Remix (to replace or reimagine elements) and Re-cut (to extend video clips), plus style presets for artistic looks. For example, a marketer might input a red vintage car driving down a coastal road at sunset and Sora will produce a brand-new video accordingly. As a ChatGPT-integrated feature, Sora makes video creation feel as easy as chatting with an assistant.
Runway ML has also been pushing video tools. In June 2024 Runway unveiled Gen-3 Alpha, a next-gen AI model that generates 5–10 second clips from text or still images. Runway says Gen-3 offers a major improvement in generation speed and fidelity over its predecessor Gen-2, along with fine-grained controls on motion and style. Runway’s Gen-3 excels at generating human characters with varied actions and expressions, unlocking new storytelling options for creators. (To manage output quality, Gen-3 initially capped clips at 10 seconds; the first 10-second clips took about 90 seconds to render.) Like other AI video tools, Runway’s model was trained on vast video datasets, and the company is cautious about copyright, noting partnerships with artists and content moderation efforts.
Another newcomer is Pika (Pika Labs), a startup that launched its text-to-video platform in late 2023. Pika’s easy ChatGPT-style interface lets anyone create or edit short videos, even without prior video skills. Users can generate clips in diverse genres (3D animation, anime, cinematic live-action, etc.) from simple text prompts. Pika also offers creative controls: you can set the aspect ratio, frames per second, or camera motion (pan/tilt/zoom). After a clip is generated, Pika provides an Edit mode to modify parts of the video, extend its length, or fine-tune the result with additional prompts. While outputs are still improving, Pika already demonstrates how rapidly AI video is advancing for content creators.
In parallel, tools like Meta’s (Facebook) text-to-video models and Stability AI’s new image-to-video feature are in development. The key takeaway is that AI video generation is no longer science fiction: creatives can now generate and customize motion clips in minutes, transforming storyboarding, animation, advertising, and social media content. As Runway’s co-founder notes, these tools are still evolving, but they are only the first and smallest of severalvideo models on the way.
Integrating AI into Creative Workflows
Creative professionals are finding many practical uses for these tools. Designers use AI to rapidly iterate on concepts: for instance, an illustrator might draft multiple scene layouts in Midjourney before refining one by hand. Marketers generate quick ad visuals with tools like DALL·E or Canva AI to A/B-test campaigns. Content creators use AI to fill visual gaps: filling backgrounds, altering moods, or creating on-brand imagery without a big photo shoot. Even non-visual tasks benefit; writers use AI to brainstorm image descriptions, and AI models (like OpenAI’s GPT-4o) can now collaborate on visual projects by suggesting prompts and layouts.
These efficiencies show up in survey data. Adobe’s global poll of 2,541 creative pros found 62% of users say generative AI already cuts the time they spend on tasks by about 20%. About 58% report they can produce more content with the same resources, and 69% believe AI opens new ways to express their creativity. In marketing specifically, AI usage is also surging: one report shows 39% of marketers already use AI to create social media visuals (and 36% for website imagery). In short, AI tools are letting creatives focus on big ideas and fine-tuning, rather than repetitive manual work.
An example workflow: a digital agency might use AI to generate a variety of themed images for a campaign (say eco-friendly future city skyline, vintage travel poster, etc.) and then pick the best ones for final editing. The designer can ask the AI to make small adjustments (change the color of the sky or remove that building) instead of starting from scratch. Video producers can draft quick storyboards with AI clips, then use those as guides for longer filming or animation. By weaving AI into their process, teams report faster iteration cycles and more content output effectively speeding up time-to-market. Adobe notes that brands using Firefly have seen faster time-to-market, better performing campaigns, and innovative, personalized experiences thanks to AI-boosted workflows.
Licensing, Originality, and Ethical Considerations
With great power come concerns. Generative AI raises questions about who owns an AI-generated image and whether it inadvertently copies existing art. These issues are hotly debated. For example, Hollywood studios recently sued Midjourney (and other AI firms) for allegedly training on copyrighted films and character artwork without permission. (Disney and NBCUniversal’s complaint notes Midjourney had millions of users and $300 million revenue by 2024, accusing it of profiting from unauthorized reproductions of their IP.)
Firms are responding. Adobe emphasizes that Firefly is built on licensed or public-domain data and is commercially safe, and it even offers opt-out tools for creators worried about their styles. OpenAI implemented multi-tier safety filters and is researching ways to label AI-generated images (provenance classifiers). Runway and others have added content moderation systems and adherence to standards like C2PA (for digital provenance) to track generative content. Getty Images and Shutterstock have also gotten into the game by licensing their libraries to AI developers, turning their vast stock archives into training data deals. For example, Shutterstock reported $104 million in revenue from licensing content to AI companies in 2023(aiming for $250 M by 2027).
However, legal clarity is still emerging. Currently there is no global rule requiring AI companies to pay for training data, though dozens of lawsuits are in progress. Courts are grappling with whether training a model on copyrighted images is fair use, and whether output images count as derivative works. Some early rulings have tightened restrictions on generative models replicating artists’ styles without permission. In practice, creatives using AI should be cautious: some tools explicitly avoid generating in the style of living artists, and many commercial AI image services claim to produce unique output each time.
On originality, many users find that AI often creates genuinely fresh combinations (addressing a common stock photo gripe that images can look generic or overused). The instant customization of AI images means every query can yield a new, bespoke visual (for example, specifying exact objects, camera angles, or filters). Agencies note that clients appreciate the guaranteed originality of AI visuals: no two AI images are identical, and they can be personalized to a brand’s needs. As one photographer lamented, he lost a €15,000 campaign to an agency producing an entirely AI-generated visual, because the AI output better matched the client’s vision. This underscores both the creative possibilities and economic shifts: demand is growing for instantly editable, unique visuals over standard stock photos.
Stock Content and Generative AI
Stock imagery itself is undergoing a revolution. The global stock photo market is still large (around $4.65 billion in 2024), but AI image tools are growing much faster. One analysis projects AI image generation revenues (from $300M in 2023 to upwards of $60 billion by 2030) dwarfing traditional stock growth. In response, major stock platforms now offer AI options: for instance, DepositPhotos and Shutterstock both let users generate and license AI-created images alongside their regular libraries. Getty Images recently introduced an AI Image Generator tool that promises robust legal protection by building on licensed visuals.
This shift means creatives have new kinds of stock content to draw from. Instead of searching a fixed catalog, a designer can describe exactly what they want and get a unique image on demand. This dramatically expands creative control. For example, if a marketing team needs a specific combination of elements (say, a happy family in a futuristic living room with warm lighting), an AI generator can create it precisely. Meanwhile, stock agencies themselves are rethinking licensing models: they are pitching large corporations to license entire archives for AI model training (turning former competitors into partners).
Despite this innovation, traditional stock still has value. Photographers and illustrators continue to produce specialized content, and editorial news images (e.g. celebrity or event photos) cannot yet be reliably faked by AI without legal risk. In fact, some of the strongest demand remains for real, high-quality photographs in fields like fashion, food, or travel. However, for generic or abstract visuals (backgrounds, concepts, product mockups), AI-generated stock offers a faster and often cheaper alternative. One industry report notes that in already-disrupted markets like illustration, over a quarter of creators reported job losses to AI by early 2024. This suggests that as AI-generated content improves, businesses will increasingly rely on it for routine assets, leaving human creators to focus on high-end artistic work and content that AI can’t easily replicate yet.
Time Savings and Productivity Gains
A major benefit of AI in creative workflows is time savings. Because AI can produce initial drafts almost instantaneously, creative teams report spending far less time on mundane tasks. In the Adobe survey, 44% of creative pros said they use generative AI to save time by automating tasks, and 62% said AI already cuts about 20% of the time from their typical tasks. Nearly three-quarters expect even greater speedups in the future.
Practically, this means a layout that might have taken hours can be sketched in minutes, freeing designers to refine and polish. A content creator who once needed multiple stock images can now generate tailored graphics with a single prompt. This boost in efficiency lets teams do more with the same resources for instance, scaling up social media or ad creative output. Adobe also notes that AI tools help creatives focus on the work they enjoy, by offloading repetitive chores. In sum, AI doesn’t just generate content it streamlines the entire process, enabling faster ideation, iteration, and delivery.
Conclusion: Embracing AI in Creative Work
Generative AI is no longer on the horizon it’s here, transforming creative workflows across industries. The latest tools in image and video generation allow anyone to bring ideas to life with a few words, making the impossible possible in design. For creative professionals, this means embracing new skills (like prompt-crafting) and adapting processes: mixing human creativity with AI speed. Licensing and originality concerns remain an important consideration, so it’s crucial to use commercially licensed AI services or properly attribute content.
Overall, the trend is overwhelmingly positive for productivity and creativity. With AI handling tedious elements, designers and creators can devote more energy to strategic and artistic thinking. The explosive growth of AI-generated stock content ensures that customized visuals are always at hand. As one industry report notes, AI tools are being used to solve visual demands at unprecedented scale. In 2025 and beyond, creative teams that skillfully integrate these generative tools whether for crafting images, videos, or entire campaigns will stay ahead of the curve. By understanding the capabilities of Sora, Runway, Midjourney, Firefly, DALL·E, Pika, and others, and by minding the ethical and licensing landscape, professionals can harness this AI revolution to supercharge their work.
Source: kaptur.co, blog.adobe.com, techcrunch.com, economictimes.indiatimes.com, openai.com