极乐视频鈥檚 2024 AI Landscape: The Communicator鈥檚 Guide to Finding AI Tools You Can Trust is the recently released and first in a series of reports from 极乐视频, focusing on the most enterprise-ready AI solutions for marketing and communications professionals. In the Enterprise AI in Focus interview series, report contributors are sharing their insights on the evaluation, the landscape, and what they see ahead. In this second interview series installment, we spoke with the authors of the report鈥檚 Creative and Design section, Gabe Michael, VP, Executive Producer 鈥 AI and Alexia Adana, Director of Creative Technology, AI, to discuss their findings.
Q: What were the main criteria used to evaluate the enterprise readiness of generative AI tools for creative and design purposes?
Gabe Michael: The primary criteria we used for evaluating enterprise-ready generative AI creative and design tools included whether vendors offer enterprise-level plans and any indemnification within those plans. Additionally, we took into consideration factors such as training data, terms and services, and the protections vendors provided. We also asked if these tools supported single sign-on (SSO) services, met technical benchmarks and requirements, and whether the quality of the tool allowed for wide adoption across organizations or if specialized skills were required.
Q: What鈥檚 the biggest misconception about generative AI in enterprise-level creative and design production?
GM: We talk about this all the time in integrated production, and I would have to say that one of the biggest and most common misconceptions is that using generative AI is basically pushing a magic button. People often believe that a single prompt generates perfect AI visuals or content instantly. In reality, it is much more nuanced, with a lot of thought, artistic intention, and skill required for the best outputs. Think about generative AI like any other tool 鈥 a camera, for instance. In this scenario, the photographer works with the subject, the wardrobe, set design, lighting - all the elements needed to get the output from the camera. Then they click the camera鈥檚 shutter button to capture the image. AI works in almost exactly the same way. But in this case, instead of just capturing light on a digital or film sensor to produce an image, the elements needed to make the shot are all generated from millions of parameters of data sets - the set-up, the artistic intention, and the post-process are practically the same.
Q: What challenges do decision-makers face when choosing the best enterprise-ready generative AI creative tools?
GM: One major challenge is identifying the actual capabilities of these tools. There are a ton of AI models on the market, and many of them might seem similar, but they serve different functions or are integrated into API-driven software. Given that there are so many interesting tools available, it is tough to gauge considerations like price point, whether the tool actually meets a need, and whether it aligns with company goals.
Alexia Adana: Agreed. And the costs of these solutions really can be a massive factor, especially for smaller agencies, and a tough challenge to navigate. Not everyone can afford high-end tools like ChatGPT Enterprise, so decision-makers need to focus on solutions that fit both their budget and objectives while aligning with their overall goals.
GM: Another challenge involves ensuring legal protection. Companies need to know what kind of indemnification is included in contracts, and what they need overall to feel secure about their investments in AI tools.
Q: What are some notable trends in generative AI tools for creative and design purposes?
GM: We鈥檙e seeing a lot of development in image, video, and audio generation, with a big trend being the ability to more easily edit or 鈥渋n-paint鈥 on that generated content. Another major trend we spotted during our research is 鈥渒it-mashing鈥 which goes back to the 鈥渕agic button鈥 misconception around AI. Because there is no single tool (yet) to do everything, and do it well, users will need to combine multiple AI tools to achieve their goals 鈥 in other words, mash kits together, leveraging different tool capabilities to achieve what they are looking to do.
AA: A plus-one to what Gabe just said. I would add that enterprise tools are starting to adopt features from open-source AI tools, such as customizable image-to-image or 3D generation. While enterprise tools can lag in offering some advanced functionalities, we expect more tools like Adobe Firefly and Microsoft Designer to catch up in this space.
GM: I agree. Open-source tools are leading innovation, and though they may not be enterprise-legal due to licensing issues, they inspire features that we see in commercial tools down the line.
Q: How are enterprises leveraging AI tools in design and creative processes, and what are the most common use cases?
GM: One of the most common enterprise use cases is social media content creation. Fast turnaround for social media assets, such as images and videos, is becoming a priority. Other use cases include hero images for blogs and websites, photo retouching, and video editing. Generative AI is also widely used for prototyping, storyboarding, and animatics, allowing creative teams to experiment and test ideas faster than before.
AA: Absolutely, and I want to emphasize the point that prototyping is a significant use case for generative AI tools, and how incredibly helpful they are during the ideation phase. For instance, let鈥檚 say you had a large pool of data from your clients that will inform who the consumer base is. This was a recent use case for us, and our team leveraged that data and used AI to build an audience simulator, which enabled us to test concepts for creative campaigns. These custom models built using client data help inform and improve data-driven strategies.
Q: What unique features make AI tools suitable for enterprise-level creative tasks?
GM: The user interfaces (UI) of many of these tools, such as Adobe Firefly and Runway, are designed to streamline creative processes and are an outstanding feature for the enterprise-level user. These UIs cater to users familiar with platforms like Canva or Adobe Express, making adoption smoother for large teams.
AA: Generative AI also speeds up the brainstorming process, and this enables teams to quickly iterate and test different creative concepts. It鈥檚 an excellent way to save time and move faster on their campaigns.
Q: How do these tools facilitate collaboration between humans and AI in enterprise settings?
GM: It's important for anyone using AI, especially decision-makers, to view it as a creative assistant rather than a replacement for people. While AI solutions can generate initial outputs, human oversight is crucial to ensure artistic integrity. At 极乐视频, for instance, we emphasize the importance of controlling inputs and using AI creative and design tools to complement the creative vision, rather than relying on it to dictate outcomes. We have amazing creative talents, like Alexia, that will help ensure artistic integrity. One common scenario is when a user reverts to the 鈥渕agic button鈥 fallacy and do little to nothing other than just entering a prompt. More often than not they will be unhappy with the 鈥淎I look.鈥 This is what happens when someone doesn鈥檛 try to stylize the image, or really do anything additional other than what the model gave them. It鈥檚 a great way to create that mediocre, out-of-the box type look and feel.
AA: It is so important to integrate AI into existing creative processes, not use it to replace existing creative and design processes. If someone is creative but over-relies on generative AI, then to Gabe鈥檚 point, they won鈥檛 have true artistic ownership because the AI is doing the heavy lifting. But on the opposite end of the spectrum, if you are fearful of using AI to augment your workflows, then you're missing out on an opportunity to improve your craft. In my own work, I used AI to very quickly learn expressions in After Effects and to streamline processes that would otherwise take hours of searching through tutorials 鈥 and potentially looking for tutorials that might not even exist.
Q: What are three key considerations for companies adopting AI tools for creative purposes?
GM: When adopting generative AI solutions for creative and design, companies need to first assess whether the tool fits into their current workflow 鈥 ideally, without a major disruption. Second, they need to evaluate their comfort level with the tool - there are obviously ethical guidelines in play here, with each organization feeling more comfortable using certain generative models. Finally, decision-makers must ensure the solution aligns with the company鈥檚 creative philosophy and goals.
Q: What does the future hold for generative AI in enterprise creative and design processes?
GM: I see AI video tools being integrated into existing software like Adobe Premiere Pro, which will allow for seamless AI-driven video generation. Additionally, generative audio models will soon play a larger role in enterprise-level content creation, with cross-program functionalities becoming more prevalent.
AA: I predict AI video will disrupt the industry within the next year or two鈥攁nd it鈥檚 going to be a game-changer for enterprise creative teams. To learn more about 极乐视频鈥檚 findings around AI tools in the creative and design category, as well as the most enterprise-ready LLMs and analytics/social listening tools, download the full report today.
See 极乐视频鈥檚 2024 ranking of enterprise-ready creative and design solutions here, download the full 2024 AI Landscape report today.