How Designers Can Effectively Use AI Without Chasing Every New Tool
The hype around AI in design can feel relentless. Every week brings another “must-try” tool that claims it will save hours, spark genius ideas, or make entire parts of our process obsolete. As designers, it’s easy to feel like we’re falling behind if we’re not constantly experimenting with the latest thing. But after digging deep, reviewing tools, building comparison charts, and putting them through real workflows, I realized the smartest move isn’t chasing the newest shiny object. It’s starting with what we already have.
New Day, Another New Tool: The AI Dilemma in Design
When the AI buzz began, I felt compelled to explore every new tool on the market. As a senior designer at Vervint, I wanted to be “on it” and also lead by example, making sure my team understood that experimentation and curiosity were not just permitted, but very encouraged.
However, I quickly found myself having to answer some very important questions:
- Which AI design tools help us deliver more effectively?
- How do we know which ones to trust?
- Will these tools actually help our design process and fit into established workflows?
Between the consistent onslaught of new AI tooling options and the weight of the decisions, I realized I needed an organized way to assess and rank these options.
The AI Design Tool Landscape:
I started by creating a comprehensive list of AI tools, and yes, I used AI to help compile the list. I then developed a review system to evaluate each tool’s pros and cons, documenting where they might support our design process and in which specific design areas they could be useful.
After reviewing many tools, I charted them so my team could have a quick, visual reference to refer back to. This exercise helped us understand both the overlapping capabilities and unique features of each tool, making it easier to identify which ones might make sense for our team.
Through the testing process, I discovered some important truths about the current state of AI in design:
- Current AI tools for design cannot replace human designers. They serve as support systems that enhance our capabilities.
- Even the most robust AI tools only help with specific parts of the design process, providing ideas and intriguing concepts, rather than code-ready deliverables.
- To get meaningful results from AI tools, there’s significant upfront work required. The promise of time-saving isn’t always realized without proper setup and training.
- Introducing new tools into a designer’s established workflow requires substantial effort and time. Don’t underestimate this.
Start and Scale with What You Already Have
The most significant insight from my research was that the best AI tools for designers are often the ones already integrated into our daily workflow. Here are the broad learnings that really stood out for me.
Deeply explore your existing platforms: We already have licenses with tools like Miro, Figma, and Microsoft, which are continuously enhancing their AI capabilities. Start here and you can more quickly examine how the specific AI features work and their potential impact. If the feature or tool is properly designed within an existing product suite, the learning curve is really small, or nonexistent.
Work from a place of trust: Using AI within established platforms feels more secure when handling client information. Do your due diligence with regards to how data and information inside any AI tool might be treated. If you are already a paying customer of a specific tool or platform, you can likely connect with a human and ask detailed questions about this topic if you care to.
Stay in the flow: Since we already use Miro and Figma in our work, incorporating their AI features required minimal disruption to our process. This was a major non-hurdle that mattered to our team.
Push the envelope, faster: There are some truly dynamic AI tools and features out there that provide new ways to co-create with clients. For example, in live strategy sessions with clients we’ve used Figma’s tools to generate quick interface concepts, solely for the purpose of energizing the room and getting everyone around a potential concept, much faster.
Opportunity Cost? The Challenges of Sticking With What You Already Use
While I advocate for starting and scaling with familiar platforms and tools, there are some limitations we should be honest about.
One Size Fits None: We’ve all seen very popular tech platforms that do “everything” lurch into new tools and features, and sometimes, the results aren’t great. If you’re seeking to use cutting edge AI capabilities, the truth is, sometimes truly specialized solutions emerge from unexpected, brand new places. Keep your eyes peeled and create space so you can continuously evaluate and experiment with the newest tools.
Costs Pile Up: Smaller companies or freelancers might not be able to afford premium accounts that include advanced AI features. The established platforms with pricing power are not shy about charging for value. Sometimes it might be more cost effective to trial a bespoke AI solution instead of adopting an AI suite that comes with a new per seat charge for your organization.
Mind the Innovation Gaps: There are interesting standalone AI tools that offer unique capabilities and even though it might be difficult to integrate that particular tool into current workflows, it could prove to be the right move for your organization and your clients.
Effectively Fusing AI into the Designer’s World
While the pressure to adopt AI in design is real, the most practical approach is to start with the tools you already use and trust. Rather than chasing every new AI solution on the market, explore how your existing platforms are implementing AI features. Here are some closing thoughts on how to fuse AI successfully with your design team.
- Share success and tips internally and recognize that some designers will adopt and flourish with AI tools faster than others.
- Keep the human and their ability to create and experiment at the center. AI should support them, not force the designer into unfamiliar, complicated workflows with disconnected tools.
- Leave room to learn. While we advocate for going deep with existing platforms first, create a way for your team to hear about, share, and still experiment with new tools as they arrive. This could happen in a Slack or Teams channel, or be more formally woven into a monthly design-team meeting where you highlight a new AI feature or tool, each meeting.
Remember, AI is meant to be a tool that supports your humans, not the other way around. Focusing on practical integration rather than chasing the newest shiny object will likely yield the most sustainable results, consistent adoption, and ultimately, the very best outcomes.