Digital experiences and design are about to enter a new age with AI.
Let’s be honest — championing human-centered insights is often lonely. UX, product, and marketing professionals know the struggle of customer research. We all aim to be champions of customer-centricity, fully tuned into every user’s needs and behavior. But in reality? It’s slow, it’s expensive, and often, it’s skipped altogether.
We rarely get to research as thoroughly or as often as we’d like. Even when we do, there’s a minefield of justifications—ROI, sample sizes, speed to insight—turning research into an uphill battle.
Enter the “Simulation Era,” where AI-powered tools promise something we’ve only imagined: on-demand, high-accuracy audience simulations that work. Picture having a virtual panel of your audience on standby, ready to provide feedback on every question or decision. This doesn’t replace human insights or traditional qualitative methods; instead, it complements them. By handling iterative, early-stage feedback, simulations free up time and budget for in-depth studies on the questions that matter most. It’s a way to stay in continuous dialogue with your customers as you develop ideas, sparing resources for the insights that need it most. This isn’t sci-fi; it’s a practical, transformative answer to every UX and design professional’s need for fast, reliable insights.
The Evolution of Design Eras: A Journey to Simulation
We are at the dawn of a new era for design — and not for the first time, as noted1 by my colleagues at the Institute of Design. Throughout history, design has transformed in response to society’s evolving needs and technology’s progress, bringing us to today’s Simulation Era, where AI-driven simulations redefine how we create, test, and improve user experiences.
Here’s a look back at how each design era laid the foundation for where we are now:
1. 1937 – 1950: The Experimentation Era
Design began its modern journey in 1937 with the founding of The New Bauhaus, a pioneering school of thought that embraced a holistic approach, integrating art, technology, and social function. In this period, designers experimented with user-driven, practical solutions for everyday objects, focusing on usability and form in ways that served real human needs. This early dedication to functionality was a precursor to the user-focused approaches that would come later.
2. 1950s – 1970s: The Systems Era
By the 1950s, design thinking shifted towards functionalism and systems-driven approaches. The rise of computing introduced designers to new digital mediums, sparking interest in designing systematic solutions to societal challenges. During this era, the field began evolving beyond individual products to consider how design could address broader, complex systems. This laid the groundwork for thinking about design in connected, networked ways—ideal for the tech-driven society that was beginning to emerge.
3. 1980s – 2022: The Human-Centered Era
The digital transformation of the 1980s and beyond brought empathy and human needs to the forefront of design. The rise of mobile and digital computing solidified the “experience” as central to design, and empathy became synonymous with success in UX. For over four decades, human-centered design meant understanding customers, employees, and users on a deeply personal level. This era fostered occupations centered around UX and CX, emphasizing the importance of considering each user’s journey.
4. 2023 – Present: The Simulation Era
Today, we are entering the Simulation Era — a new chapter in design grounded in three essential pillars: Trust, Co-Intelligence, and Humanity. These pillars challenge design to evolve with agility, urgency, responsibility, and fearlessness.
- In this era, trust is redefined as we seek greater explainability from AI and LLM systems, striving to understand the black box of AI so that we can trust, rely on, and responsibly use its insights. By deepening our understanding of AI’s strengths and weaknesses, we can better own its role in our work, ensuring it supports human-centered outcomes without compromising accountability.
- Co-Intelligence is the blending of artificial intelligence with human insight, creating a collaborative approach that automates routine tasks while empowering creativity and informed decision-making. This synergy unlocks powerful tools for real-time customer research and agile design testing, enhancing our ability to iterate based on actionable insights.
- Finally, humanity remains the core of the Simulation Era, grounding our designs in empathy and ethics. By centering human values, we ensure that the evolution of design remains as deeply connected to human needs as it is to technological advancement.
The Simulation Era enables continuous, real-time engagement with audiences, giving teams the ability to de-risk and refine concepts before they go live. It empowers us to launch exceptional products and campaigns from day one, informed by AI-driven insights and a commitment to transparency, collaboration, and empathy. This era isn’t just about new tools; it’s about building a framework of trust, responsibility, and adaptability that propels design forward.
The Need for a New Research Paradigm
In today’s hyper-competitive market, customer expectations are at an all-time high. Research shows that a single negative experience can prompt 32 percent2 of customers to abandon even their favorite brands, while repeated disappointments push nearly half of users away for good. With such high stakes, businesses must capture, understand, and respond to customer needs before launch or risk losing them. Yet, traditional customer research is time-consuming, costly, and can’t always keep pace with rapidly shifting user expectations.
Simulated research, fueled by AI, steps in to address these challenges. Using simulation, professionals can mimic real user interactions, predict responses, and validate concepts with remarkable speed and accuracy. The goal isn’t to replace traditional human insights but rather to supplement and strengthen them, enabling us to keep pace with customers’ evolving needs and behaviors with greater frequency and accuracy than ever before.
Leveraging the Simulation Era for Enhanced Customer-Centricity
Adopting a simulated research strategy is no longer optional—it’s essential for any organization aiming to lead in customer experience. The potential applications of simulated insights are transformative:
- Rapid Persona Development: AI-generated personas that continuously evolve, providing teams with an accurate and current understanding of their audience.
- Simulated User Testing: Early-stage concepts and designs can be tested with simulated users, allowing businesses to catch issues and refine ideas before launch.
- Competitive Benchmarking: Real-time insights on competitors’ user experiences empower teams to make data-driven adjustments and stay ahead.
- Design Prototyping: AI-driven simulations make it possible to test multiple design iterations quickly, reducing the time spent on low-impact concepts and directing energy toward customer-centered solutions.
AI’s Role: Augmentation, Not Replacement
Despite initial fears that AI would disrupt jobs in UX, design, and marketing, the reality is that AI is far more likely to enhance these roles than replace them. By taking on repetitive tasks such as data processing, initial analysis, and design prototyping, AI frees up professionals to engage in higher-value activities. In the Simulation Era, we’re not abandoning empathy and creativity; rather, we’re adding a superpower to our toolkit that lets us research, iterate, and validate ideas at unprecedented speed.
AI’s strength lies in its ability to provide rapid insights, generating hundreds of design iterations and analyzing vast data sets in a fraction of the time it would take a human team. Yet human insights remain essential for complex tasks requiring empathy, ethical judgment, and deep cultural understanding. In this context, AI serves as a powerful co-pilot and partner, augmenting our capabilities and expanding the reach of customer-centric research practices.
Simulated Audiences: More Than Synthetic Constructs
Simulated audiences, unlike generalized synthetic constructs, are based on rich demographic, behavioral, and attitudinal data. This enables a level of accuracy in predicting real-world user responses that often surpasses what an average pool of human participants might say. For UX professionals, this unlocks the ability to create AI-driven personas that adapt with new data, testing multiple prototypes at once and uncovering user journey pain points—all in real time.
Studies show that 83 percent3 of companies want customer insights data at every stage of the product life cycle. However, only a fraction can achieve this consistently. Simulated audiences bridge this gap by enabling organizations to conduct continuous, scalable testing that’s both cost-effective and timely. Whether it’s optimizing a website layout, adjusting a marketing campaign, or validating new product features, simulated research helps brands stay attuned to their customers, offering a faster path to insights that traditional methods can’t match.
Not All AI Tools are Created Equal
One of the AI tools that has taken the lead in the space of Simulated Audiences is WEVO. Its accuracy in predicting human response is above all leading LLMs. In a recent study4, WEVO Pulse demonstrated higher accuracy in predicting human response than OpenAI, Gemini, and Claude. In this study, each of these four AIs attempted to predict how a group of 120 people would assess a digital experience. The 120 people were representative of the typical users of the experience measured. This test was run on 100 different experiences, ranging across industries, including financial services, automotive, leisure, higher education, consumer services, and business services. On average, WEVO Pulse outperformed all other AIs when measuring the human assessment of the experience’s value, intuitiveness, and trustworthiness. On average, WEVO achieved 80% accuracy overall. In addition, Pulse correctly predicted 80% of the insights generated from the comments that people made during the user studies.
Why is it that WEVO achieved higher scores than other AI’s? First, WEVO’s model was trained on the responses of over 1 million users who participated in user studies. In addition, the WEVO team leveraged groundbreaking technology for which they were granted ten patents, with nine more pending. Accuracy levels are likely to rise further over the next weeks and months as training of these models continues.
Meeting the Needs of Today’s Digital Experience Managers and Strategy Consultants
Cultivating influence and gaining support can be challenging when trying to make a case for design changes or new product features. For Digital Experience Managers at large brands, simulated insights will be a game-changer. With rapid, reliable insights, there is now a way to demonstrate impact and substantiate proposals with data that resonates across organizations. A powerful AI-driven platform like WEVO equips Digital Experience Managers to bridge the gap between vision and buy-in, transforming their ability to advocate for user-centered strategies in organizations where every decision counts.
In the competitive landscape of client services, simulated insights will allow agencies to deliver immediate, high-quality insights that set them apart for front-line delivery and business development. Whether fine-tuning UX elements for a client’s site or evaluating campaign performance in real-time, AI-driven simulations provide consultants with the agility and precision needed to impress clients and drive measurable results. On the business development side, agencies can leverage simulated insights powered by WEVO Pulse to showcase proven successes, industry trends, and instant competitive analysis – helping them build credibility, retain clients, and expand their influence in an increasingly data-driven industry.
Embracing the Future of Experience Management
As we stand at the dawn of the Simulation Era, the possibilities for UX, product, marketing, and design professionals are massive. By incorporating AI-powered insights with traditional human research, organizations can keep pace with customer expectations and develop products that genuinely resonate with their audiences. The Simulation Era isn’t just about faster, cheaper research; it’s a call to elevate our approach to user experience, empowering teams to innovate in ways that were previously out of reach.
The future of UX, design, and customer-centered professions is here, and it’s grounded in a balanced approach that marries the speed and efficiency of AI with the empathy and nuance of human insights. By embracing this new model, companies can make the shift from sporadic feedback loops to a continuous cycle of learning, adaptation, and customer-centric innovation. The Simulation Era has arrived, and it’s redefining the path to customer satisfaction — one simulated insight at a time.
If you want to see how Simulated Audiences can help your team, you can try it out today at www.wevo.ai/TakeApulse
About the Author
Mark Micheli is WEVO’s Vice President of Growth and Strategy. Previously, he led Accenture Song’s Human Insights and Design Research practice and served as a journalist, marketer, and product consultant for organizations like The Atlantic, Bloomberg, Target, Google, and the LEGO Group. He’s also the founder of Say Do, a design strategy firm, and teaches customer-centered innovation at the Institute of Design in Chicago and Hope College in Michigan.
References:
1 https://artsandculture.google.com/story/zgUBjgW801CaLA
2 https://www.pwc.de/de/consulting/pwc-consumer-intelligence-series-customer-experience.pdf
3https://www.forbes.com/sites/louiscolumbus/2018/05/23/10-charts-that-will-change-your-perspective-of-big-datas-growth/?sh=404ba72d2926
4 In an October 2024 study, conducted by WEVO, WEVO Pulse achieved 80% accuracy in predicting how a group of 120 users would evaluate an experience across the measures of value, intuitiveness, and trust. In that study, WEVO outperformed OpenAI, Gemini, and Claude. In addition, WEVO Pulse generated over 80% of the qualitative insights that were created by those 120 individuals. This study included 100 different user experiences, targeting B2C and B2B businesses, with varying income levels and educational backgrounds. For each study, 120 people were selected from the specific target audience of that experience.
5 Image was generated with Adobe Firefly and modified with Adobe Photoshop Generative Fill
