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All the headlines touting the magical powers of generative AI are, understandably, making some designers nervous. If they’ve had little or no experience working with AI or large language models (LLMs), it can be especially daunting. But, designers are actually well-positioned to meet this moment. Many just don’t know they have design skills that translate into AI skills.
Interaction design, systems design, the ability to communicate ideas, and a human-centered practice are core design skills that underpin strategies for generative AI.
“Designers are more ready than they think,” says Greg Bennett, Salesforce Director of Conversation Design, Einstein GPT. “They can feel incredibly confident about the value they bring to AI.”
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In his work on Salesforce Artificial Intelligence, Bennett refers to generative AI as a “word calculator.” Designers can use it to produce an output that’s optimized for users. Framing the design/AI relationship this way makes it easier to understand how those who have a design background can make an impact. Plus, it’s especially worth calling out these transferable skills now when many companies are scrambling to build their generative AI teams.
Accordingly, Bennett wants designers to claim their existing superpowers, starting with these four:
This user experience specialty is centered on understanding the goals, context, and behavior of the person trying to complete a task. Designers use this knowledge to inform everything they create. This may include navigation structures and information design to click paths and micro-interactions.
Today, personalized interactions are more possible with AI because it can get more granular about the user and the context. Increasingly specific commands, context, goals, and expectations equate to better results. For example: When AI creates an email from a salesperson to a potential customer, it needs to know more about the interaction including:
“I always ask, ‘What should this interaction inspire?’” says Bennett. “Is the output to one person or many? Does it occur on a platform? Does it create code that makes an action?”
If businesses want to get up to speed fast, they’ll need someone who can help them create these more personalized interactive user journeys – and do it at scale.
Designers know that adhering to a design system is important because it creates standards that build trust with users and makes interfaces easier to navigate. Hence, Bennett sees this as an asset with respect to AI. He wants designers to recognize how they excel at systems design – the practice of designing with scalable elements to improve the user experience – and how AI will augment this skill.
Specifically, a new application of this skill occurs when designers use AI to help adhere to design systems. For example: prompting AI to consider the Salesforce Lightning Design System, brand theming, and any problematic processes or solutions to avoid for a new template (also known as anti-patterns). When working with AI, designers can iterate along the way, tweaking the interface to meet user needs. This helps ensure users have an experience that feels familiar and easy to navigate.
Bennett explains that design has actually been waiting for this moment for years. Now the technology is available to amplify the design systems that have been created. He notes that each one is a database that a model can reference. The same is true for design taxonomies and pattern libraries. “You won’t have to go pull that component for SLDS anymore. You’re not executing the scene. You’re conveying how the scene should be,” he says.
Consistent input yield consistent outcomes. When using AI to design multiple pieces of a solution, it’s essential to think about the entire system. Well, not just think – also communicate it precisely to the AI.
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“Right now, the method for interacting with AI is language driven,” says Bennett. “Throughout their careers, designers have been communicating their visions to stakeholders.”
Think of a design review with the product managers and developers. Whether it occurs in person, in Figma, or in Slack Huddle, reviews are opportunities for designers to articulate what the experience should be like and why. It’s a muscle they’ve already built. In addition to communicating ideas clearly, designers also share their process.
They might show a design and state what assumptions they made while creating it. Assumptions might include, for example: That French is a user’s first language for a regional feature. Or that users are over the age of 40 for a feature with larger text. This level of transparency and background detail can be useful to AI.
As these instances show, a designer’s behind-the-scenes thinking is often centered on the person who will be using what’s built. This is another design skill that can transfer to an AI future.
A process that begins with user needs is known as human-centered design. It takes into account if an idea is desirable to users and how feasible it is to create. When done successfully, this creative problem solving can increase product adoption and customer satisfaction. Designers with this skill know that it begins with discovery. Asking the right questions can lead to building the right solution.
Bennett encourages designers to leverage human-centered design as the one next step to take today. “Start by asking questions of people with models. Bring them the design questions,” he says.
Connect with your AI engineer, AI leader or data scientist. Let them see you as an asset who can help them think more critically by asking questions such as:
This line of inquiry can orient those leading AI to think with a design lens, to include your unique perspective in the creation process, or to defer to your knowledge. If you’re job searching, ask interviewers the same.
There’s so much to learn from the latest AI + Data + CRM innovations and responsible development guidelines to Einstein GPT, the world’s first generative AI CRM technology. Just don’t forget: There’s also so much you already know. Designers have an advantage and can claim their role in the AI arena today.
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