As the leader of a design agency that is working at the forefront of design and innovation, I have witnessed firsthand the transformative power of technology in driving new growth and experiences. Our mission as UX designers is to apply human-centered approaches in helping technology companies to deliver better user experiences. Over the years, my team has been privileged to guide many leading companies through significant technology and paradigm shifts, spanning digital, mobile; connected, or the Internet of Things (IoT); and natural interfaces. As futurists and humanists, we are passionate about embracing new technologies in ways that enhance human experiences and deliver more value.
In every engagement that helps companies transform for the future, we too are transformed, both as individuals and as an organization. Plus, we are adopting new methods and growing new technical capabilities. We live the spirit of innovation by constantly evolving to meet the pace of change and progress. Now, in what we call the Conscious Era, with the exponential growth of generative artificial intelligence, UX designers are coming face to face with the most powerful, yet disruptive technology to date—not only for products, but for the UX design profession itself. Business and career reinvention is now an imperative as UX designers embrace artificial intelligence (AI) as a new creative partner and collaborator.
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In this column, I’ll discuss my experiences partnering with AI as the leader of a digital user experience agency. I’ll outline the steps that we have taken to explore and integrate AI into our process—from establishing responsible approaches, to criteria for how we select the right tools, to our vision for augmenting our abilities. Through this discussion, my aim is to shed light on our contrasting feelings of optimism and concern surrounding the impacts of AI technology on the UX design profession.
Business and the Reinvention of UX Design
For almost all our clients, the mandate from the board room is the same of late: Leaders are directing their teams to immediately find ways to integrate artificial intelligence into products and processes to drive new value. Businesses know that, to compete and survive, the most critical factor for immediate business reinvention is AI. The promise of automation in reducing costs and innovation in increasing profits is driving the current race to reinvent both customer and employee experiences. In many ways, this is do or die. Laggards who fail to embrace AI quickly will fall behind because the pace of AI adoption is advancing rapidly. This acceleration is equally true for UX designers and the design profession. The adoption and use of AI in the design process is key to our future professional success. Companies now expect and demand that UX designers use the power of AI to uplevel their skills and speed up their impact.
Designing with AI
As I talk with other design and product leaders, their questions are twofold:
How are you designing for AI?
How are designing with AI?
The second of these questions is newer for us. In the past, clients did not care as much about the tools we used, as long as the artifacts and assets we produced were compatible. But this question now centers on how we are working with AI to do more.
The other day, a client asked me this question: What is the percentage breakdown on your design team between human and machine? Is it 50/50? This line of inquiry reflects clients’ expectations about the balance of AI partnership in UX design—that AI should clearly be our creative partner. But how we develop this new relationship is up to us.
Facing Reality Beyond the AI Honeymoon
As with any new relationship, there are typical stages of progress that both parties experience. For many UX designers, our initial experience when we first glimpsed generative AI was that it was inspiring and amazing. How could we create a specific photo or image to our exact specifications so quickly? How rapidly could AI summarize and write a narrative for a user scenario or user story? This fervor and excitement launched many UX designers into a honeymoon phase with AI because we believed that AI would propel us toward exciting frontiers. But, as with any relationship, the glamour has quickly worn off, and we’ve begun to see the flaws in AI and the realities of things that need more work and further evolution. While my team has been leading the charge and remains inspired and motivated, we’ve faced the reality that this is early-phase technology so not yet reliable enough for critical, custom user experiences for clients.
In the past two years, we have witnessed the experimentation phase of the generative AI revolution. While AI has been in development for many years, the advancements in large language models (LLMs) has catapulted business reinvention into high gear as we integrate this technology across products and customer experiences to drive better value creation. But many companies are haphazardly rushing out technology-first solutions with mixed success. Such products are often mere novelties rather than providing dependable functionality. When technology-first mindsets prevail, alignment to true customer needs or problems is lacking. This is evident both in consumer services and designer and business tools.
Relying solely on current LLM models is impossible because of our concerns about the accuracy and reliability of the information that they provide. Plus, privacy and security concerns have created barriers to their adoption and are preventing people from feeling confident that they can share proprietary information without its being compromised or reused without their permission. Only by eliminating AI hallucinations—LLM’s perception of nonexistent patterns or objects, which results in inaccurate outputs—and enhancing precision and security can we foster the greater confidence that is crucial for AI to make meaningful progress. By addressing this key limitation, we can pave the way for a more specialized intelligence that we can trust in critical applications.
Defining Our Relationship with AI
Is AI our friend, our foe, or something else? On one hand, the promise of AI in UX design is undeniable. From the first moment one experiences and observes generative AI in action, one likely feels amazed. AI-driven tools and algorithms have the potential to revolutionize how we approach UX design, from enhancing personalization and predictive analytics, to streamlining workflows, to driving innovation. The prospect of AI as a collaborative partner in our design journey fills us with excitement and optimism about the possibilities it unlocks.
However, alongside this optimism, there exists a healthy dose of skepticism and cautious concern. We recognize the complexities and potential risks that come with integrating AI into our UX design workflow. Questions about UX job roles, creativity, authenticity, ethical considerations, and the overall impact of AI on the design profession loom large as we navigate this AI revolution. For UX designers who are in the business of creativity, seeing machines that could rival our talents and abilities is cause for much reflection.
One of UX designers’ primary concerns is the fear of job displacement. As AI tools become more sophisticated, there is some risk that certain tasks UX designers have traditionally performed could be automated. This could potentially lead to a reduction in demand for certain UX design roles—particularly those focusing on repetitive tasks or basic design iterations. Even if UX designers’ jobs were spared, clients might expect faster turnaround times or higher levels of precision because of AI capabilities, leading to unrealistic demands or misunderstandings about the complexities of the UX design process.
Plus, some UX designers worry that a heavy reliance on AI tools could stifle creativity. While AI can generate ideas and provide suggestions, their concern is that this might limit exploration of unconventional or outside-the-box concepts. UX designers might become overly reliant on AI-generated solutions, leading to a homogenization of design styles and approaches. An over-reliance on AI tools could result in a dependency that could hamper UX designers’ ability to develop essential skills. If UX designers relied too heavily on AI for tasks such as ideation, analysis, or prototyping, they might not cultivate their critical thinking, problem-solving, and design-intuition skills. This could create a skills gap within the profession. While these risks are real, we have the responsibility as UX designers to design our relationship with AI in a way that embraces it, while leading to optimal, positive impacts.
Designing Our Relationship with AI
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Despite AI’s many risks, the upside with AI as our collaborator has the potential to propel UX designers to new heights by augmenting our work and presenting an exciting, transformative opportunity to reimagine the attainment of our fullest potential as UX designers.
Progress demands change and, as innovators, we believe that our mission is now to design our relationship with AI to empower humanity and amplify the abilities of both individuals and businesses to realize their highest potential for positive growth and well-being. This is human-centered design at its core.
To guide our efforts at Punchcut, we have applied our own design-thinking approaches to defining our relationship with AI as our new design partner. We have already taken a few simple steps to ensure that we are not only nimble but intentional at each stage of AI adoption and are taking an optimistic yet cautious approach at each stage. Let’s review the steps we have taken so far.
Establish relationship principles.
Understand needs and map opportunities.
Assemble and build an AI toolkit.
Add value across the design process.
Reflect, adapt and evolve.
1. Establish Relationship Principles.
Every relationship works better when we share clearly communicated guidelines and goals. So we began by first outlining our point of view and our principles for how we would work together with AI. We integrated these guidelines into four key themes, as I’ll now outline.
Humanity: Working with AI to Elevate People
Think of AI as a partner, not a replacement for your own thoughtfulness and creativity. Use AI tools in ways that empower people rather than diminish them, and don’t use AI in any ways to which you’d be uncomfortable admitting.
Example: To preserve authenticity in authorship, we do the following:
Avoid using this prompt: “Write an article on spatial computing.”
Instead, use this prompt: “Provide a list of the top three spatial computing trends.”
Transparency: Being Open About How We’re Using AI
The use of AI tools might be controversial to some clients, but it’s also an opportunity to demonstrate our leadership. During both sales and projects, we’re transparent with clients about when and how we use AI and which tools we’re using.
Example: To ensure transparency, for any AI-created image, we provide the type of note that is shown in Figure 1.
Figure 1—Noting an AI-created image
Security: Minding What We Share with AI
AI tools can save data that is useful in training models and improving services. But don’t use any client names, logos, proprietary information, images, or designs as inputs for AI tools. Don’t share anything with an AI that you wouldn’t share with a competing company.
Example: To avoid using specific client, company, and personal names when prompting, we do the following:
Avoid using this prompt: “Generate a list of possible new-feature ideas for Meta Quest Pro.”
Instead, use this prompt: “Generate a list of possible new feature ideas for a virtual-reality (VR) headset.”
Accuracy: Verifying Outputs from AI Tools
AI can be prone to making mistakes, having hallucinations, and presenting false information with confidence. Therefore, it might be best to use AI only for inspiration, feedback, or general information. Don’t trust AI tool outputs without credible, external verification.
Example: To ensure that we provide accurate information, we do the following:
Avoid using this prompt: “What US streaming services do subscribers rate as being in the top 10 in 2023?”
Instead, use this prompt: “What are some of the most popular streaming services in the US?”
2. Understand Needs and Map Opportunities.
We sought first to understand UX designers’ needs and sentiments through a rapid research effort. As designers, we live to observe, analyze, organize, and create. It was important to discern where we want the most help from machines and where want to preserve our human autonomy and creative control. We used the following methods to discover what is important.
Our Team Survey and Interviews
We conducted surveys and interviews to identify UX designers’ painpoints and discover what aspects of the design process our team values most. By capturing both challenges and moments of delight, we gained clarity on specific areas that require improvement or enhancement. Following our analysis of the survey’s findings, we engaged with a diverse group to delve into the underlying reasons behind these results, aiming to understand designers’ ideal relationship with AI and the rationale behind it.
Journey Mapping and Analysis
Our team audited various stages of the UX design process, documenting and analyzing areas that demanded more assistance. This effort included identifying time-consuming steps, repetitive tasks, and critical phases. By aligning these findings with our business values and objectives, we could focus our research efforts on these targeted areas—both through surveys and one-on-one conversations with designers. Our autonomy service blueprint facilitated the identification of desired levels of shared or independent control.
Exploring New Growth Areas
We are continuing to explore conversations about what our role of as UX designers will be in a future when AI assists and supports more of our workflow. Certain AI tools can streamline many of the time-consuming efforts of manual production or synthesis. In many ways, this frees up UX designers to focus on higher-level thinking or orchestration. But how can we most effectively use the time we save to enhance and preserve the value and authenticity of the work that only humans can contribute. One exercise that we have leveraged in guiding our role discussion is our relationship role spectra exercise. This exercise helps us to plot on a spectrum the nature of the roles of the UX designer and the AI technology at different points in our UX design process. We have also used persona archetypes to articulate roles such as choreographer, conductor, maestro, coach, servant, and counselor. Having a clearly defined term for an expected UX role helps us to better understand its necessary features and functions.
3. Assemble and Build an AI Toolkit.
The key to embracing AI as a design partner is investing in technical training in the use of AI tools and their continuous research and development. Technology is rapidly advancing, making yesterday’s tools and features obsolete. This reality can be overwhelming, we know. Creating tool-evaluation criteria helped us to narrow down the AI tools that we use. Based on a tool’s criteria and our design research insights, we started with a few top-ranking tools and focused on understanding them really well. Starting with a foundational focus makes pivoting in the future much easier.
Evaluating AI Tools
We maintain an evolving spreadsheet and database of emerging AI tools, enabling us to track specific capabilities and ethical considerations. Each tool undergoes an assessment based on established criteria and is rated on a scale from (A) to (F). When evaluating AI tools, the evaluation criteria that we consider are as follows:
Capability—What is its intended use?
Ethics—Is the training data diverse and ethical?
Usability—Does it offer a great user experience?
Security—Does it ensure the protection of information?
ROI (Return on Investment) potential—Does it align with business objectives?
Scalability—Will it remain effective over time?
Flexibility—Can we customize it to suit our needs?
Introducing AI Tools
Since AI tools are key to the collaborative equation, their adoption has been a focus for us. We casually introduce tools in full-team settings to start the conversation, then follow up with lunch-and-learns at which team members can start to get hands-on experience. Finally, our leaders in this space look for opportunities to incorporate a tool in our project work. Exposure to a tool over time makes it a natural part of everyone’s process.
Customizing and Creating Tools
It quickly became clear to us that the tools that would provide the most value are those that we’ve had tailor-made for our unique needs. Therefore, we now have dedicated Design Technologists who are helping us build and test new tool customizations that uniquely support and streamline our UX design process. Our Design Technologists are helping us develop our creative-intelligence platform—from custom sales assistants, to presentation-creation tools, to advanced synthesis and design-thinking tools. We believe this will continue to be a core part of our design leadership into the future. Design and technology leadership are now more intimately connected to further empower one another.
Spark: Our Custom AI Plug-in for Figma
We recently developed Spark to help us with our early design research and vision-project efforts. Spark, an AI plug-in for Figma, accelerates our creativity. With Spark, we can effortlessly ideate, summarize, and categorize, revolutionizing our UX design process. Spark is currently available in private beta, but it is something that we already offer to our clients to empower their design efforts as well as our own.
4. Add value across the design process.
As we’ve explored new AI tools and incorporated them into our UX design workflow, we’ve realized the importance of highlighting their added value and communicating that value to both our teams and our clients. This addresses the crucial question of value creation for all the parties who are involved. What are the tangible impacts and growth opportunities that collaborating with these creative-intelligence tools has facilitated? To guide us through this journey, we’ve formulated key mantras that apply across the fundamental pillars of our process. While there’s much more to discover and implement, these mantras serve as constant reminders of the value that we aim to unlock through this elevated level of technical augmentation.
We say that we combine the best of human ingenuity with machine intelligence to create bespoke solutions that are more human, creative, and nimble.
Bespoke Solutions That Are More Personalized
We use AI to personalize our approach to providing custom systems and engagements that scale our expertise and on-demand assistance. AI enables us to scale our expertise by providing self-service solutions, automated responses, and personalized knowledge bases that centralize and distribute customer insights and design systems and standards.
Authentic Insights That Are More Human
We use AI to capture human intelligence and insights that drive more authentic human-centered strategies and solutions. AI helps us analyze vast amounts of data, including user behaviors, preferences, and feedback. By harnessing AI’s capabilities, we’re gaining a deeper understanding of human needs, motivations, and painpoints. Combining data-driven approaches with qualitative research lets us develop more authentic, empathetic strategies that resonate with users on a deeper level.
A Bolder Vision That Is More Creative
We use AI to amplify our vision and uncover bold ideas and opportunities that are better at driving value. AI assists us in generating diverse concepts, exploring unconventional approaches, and pushing the boundaries of divergent thinking. AI extends our creative ideation, letting us envision solutions that are not just incremental improvements but transformative innovations that drive bold new value.
An Accelerated Creation Process That Is More Nimble
We use AI to accelerate the creation process—realizing ideas, building prototypes, and validating them faster. AI enables us to streamline our UX design workflow, automate repetitive tasks, and speed up creative production, prototyping, and iteration, enabling us to bring ideas to life more efficiently. By harnessing AI’s speed and precision, we iterate, test, and validate designs faster, leading to quicker decision-making and improved time-to-market.
5. Reflect, adapt and evolve.
Last, but not least, it’s crucial that we keep in mind that we’re in a marathon, not a sprint. While we must work very nimbly and adapt quickly, we must also recognize the long-term journey that is ahead of us. We’re adopting a build-to-learn approach, starting with small experiments and evaluating and refining their outcomes as we progress.
The rapid pace of change in the UX design profession offers valuable opportunities for learning and growth. While change can be challenging, it can also bring diversity and excitement to the UX design landscape. We eagerly anticipate developing a more collaborative relationship with AI, unlocking new possibilities and realizing our fullest potential as UX designers.
Thank you to the many Punchcut team members who have been helping research, develop, and refine the approach that I’ve outlined in this column.
Ken was a co-founder of Punchcut and has driven the company’s vision, strategy, and creative direction for over 20 years—from the company’s inception as the first mobile-design consultancy to its position today as a design accelerator for business growth and transformation. Punchcut works with many of the world’s top companies—including Samsung, LG, Disney, Nissan, and Google—to envision and design transformative product experiences in wearables, smart home Internet of Things (IoT), autonomous vehicles, and extended reality (XR). As a UX leader and entrepreneur, Ken is a passionate advocate for a human-centered approach to design and business. He believes that design is all about shaping human’s relationships with products in ways that create sustainable value for people and businesses. He studied communication design at Kutztown University of Pennsylvania. Read More
