When human creativity collides with the precision of artificial intelligence, magic happens.

As a design leader at DevRev, I’ve had a front-row seat to the recent explosion in AI capabilities. In the wake of these advancements, I have sought creative ways to embed AI into my own design process to uplevel my work.

When I think about the best ways to integrate AI into my team’s work, I’m reminded of B.F. Skinner's quote: "the real problem is not whether machines think but whether men do." It is in this spirit that I consider how humans and machines can work together to achieve more.

Designers at DevRev have the opportunity to build products that power modern ways of working. Though we design a wide range of products, one of the most interesting problems we get to solve is around crafting workflows with AI embedded seamlessly and effectively. Likewise, the design team seeks to embed AI in our own ways of working. In this post, I’ll walk through the design process and the ways in which designers can supercharge their productivity and creativity with AI.

AI supercharges every step of the design process

The design thinking framework is one of the most fundamental approaches in a designer's toolkit. It comprises five stages: Empathize, Define, Ideate, Prototype, Test. At each step, a designer can lean on AI. Crucially, the goal is to take the best of what makes us human – our creativity, intuition, and emotion – and then to elevate and expand it.

Empathize: To quote the great Don Norman, "we must design for the way people behave, not for how we would wish them to behave." With AI, we can empathize on a deeper, more data-driven level, crafting solutions that resonate both emotionally and functionally. Data lets you dive deep into the hearts and minds of your users. Increases in quantity of data, quality of data, and sophistication of data processing methods has enabled user research teams to glean novel insights on what humans think, feel, and do. Meanwhile, LLMs can be prompted to take on any role and play any character – including the role of your target persona! This allows you to role play with your customer, making you more prepared for meetings with real human users. This depth of insight, in turn, leads to a more thorough understanding of the human need.

Define: As user experience designers, defining problems is half the battle. AI’s analytical power helps sharpen focus, turning insights into precise, actionable definitions. These days, machines can transcribe user research sessions, sort through text snippets, identify key quotes, cluster patterns into insights, overlay sentiment analysis, and summarize top themes and findings. AI can also take a first stab at persona cards and journey mapping, ensuring these are based on real user data. Once the dust settles and you’ve chosen a problem statement to go after, LLMs can help craft compelling narratives and visualizations that effectively communicate the chosen problem statement to all surrounding stakeholders

Ideate: Here’s where the fun begins. AI becomes our brainstorming buddy, suggesting ideas that stretch our creative limits. It’s not just about thinking outside the box; it’s about reinventing the box. Generative AI can help bring a flood of ideas, inspired by a plethora of sources. Working hand-in-hand with AI, designers are able to use these initial ideas as a springboard for further brainstorming.

Prototype: Speed meets creativity. AI accelerates prototyping, bringing ideas to life faster and more smoothly than ever. Advanced simulations can test prototypes swiftly, giving designers a few extra cycles to polish their work. Image generation can create more vivid and immersive prototypes while code generation makes it easier than ever to build quick software mockups. Finally, AI can enhance prototypes with interactive elements, such as chatbots or voice interfaces, to simulate more realistic user interactions. This rapid cycle allows for experimentation and refinement at breakneck speeds without compromising on craft.

Test: This step involves evaluating prototypes with users to gather feedback and insights for further refinement. AI can analyze video recordings of user testing sessions, identifying key moments, facial expressions, and behaviors that indicate pain points or areas of delight. Not only can AI enhance user testing by automating data collection and analysis, it also does so in an objective manner. This reduces bias and increases the veracity of conclusions drawn.

Looking ahead

In conclusion, the integration of AI into the design process is not about replacing human creativity but augmenting it. The best such tools will empower designers to bring bigger and better visions to life. By leveraging AI, designers can enhance their empathy, sharpen problem definitions, generate a plethora of innovative ideas, speed up prototyping, and conduct thorough testing.

At DevRev, we believe that the future of work – design or otherwise – lies in blending the best of what humans and machines have to offer so that they work together to achieve more. This ethos permeates how we work and the products we build.