At Silver Fox, the utilization of generative AI is not about replacing human creativity, but rather augmenting it. While AI’s content output is very tempting, we are less interested in products that are creative for us—we want tools that help us be creative ourselves.
We see AI as a helpful tool for transforming learning and efficiency, as well as transforming the way we interact with audiences. As a designer, I resonate with the findings of a study done by IDEO with Gen Z participants: “[they] don’t want to be handed the answer. They want to develop the capabilities to create something of their own. Exploration, experimentation, and reflection are important parts of the creative process” (Gen Z to AI: Don’t Kill My Creative Vibe).
AI is a powerful learning tool; we see it helping us learn from diverse experiences in a multitude of ways. As a design agency, we are always learning the branding of new client companies. AI could make suggestions while a designer is working, boosting efficiency. Designers are experts in finding new ways to express a brand that still remain cohesive with the guidelines, so these AI pointers shouldn’t be fully present, monitoring, and correcting your work for a long period of time. But allowing AI to give more input at the beginning of this learning curve could be effective—especially because most of us learn better from doing rather than being told (or in this case, doing versus browsing a brand guidelines document).
And every so often, designers have to learn new tools and programs. AI learning from user data to adjust onboarding and courses to speed up this process is definitely something I look forward to.
Getting a different flair from designer to designer, even within the same brand, is not something we want to stray from. But in certain situations, say multiple designers working on decks for one team for an upcoming conference, staying as cohesive as possible is valuable. AI could ramp up productivity by making suggestions with the goal of keeping design cohesive amongst the designers.This consistency would enhance the team’s image and leave a lasting impression on the audience.
AI can also use and provide data to drive design decisions. Like user experience designers make decisions based on user data, AI could provide valuable insights to presentation designers. If a system of getting specific feedback on presentations from audiences was developed, analyzing this user engagement data could determine which types of designs resonate with certain audiences and are most effective for certain topics. Data-driven design improves results and hones a designer’s knowledge and skills in the process.
We’re already seeing generative AI used in the presentation design world in the ways of real-time speech recognition—transcribing, subtitling, and translating presentations to expand accessibility—and generating dynamic charts and graphs that update as new data comes in, right up until and even during a live keynote.
As Microsoft Copilot answered me when I asked it to elaborate on AI’s impact on presentation design, “AI is not just transforming the content of our presentations, but also the way we interact with our audience.” The creative process and visual storytelling remain human-led, but AI will augment designer workflows in a number of exciting ways that we’re highly anticipating.