UX Research - Past, present and the future

In times of rapid change, everything is shifting, losing grip, transforming, or dying. UX research is no exception, witnessing a sea change at hand. Here is a rundown on UX research: then, now, and in the near future, with a focus on this practice in India.

THEN

The term GUI (Graphic User Interface) has been around since the late 1980s, marking the intersection of product design and graphic design practices. It gained traction during the first dot-com boom (2000+), leading many design professionals to transition into roles like GUI designers or instructional designers (focused on creating digital courses). At the time, user research was a niche concept, often embedded within GUI design practices but not widely embraced. Classical design research, the foundational construct of user research, found limited acceptance, mostly among progressive corporations.

Around 2003-2004, as multinational companies entered a liberalized Indian economy (post-dot-com 1.0 bust), design research began to explore new ground. Early projects we got often revolved around consumer preferences and market segmentation. For instance, our work in this decade with Volkswagen, Samsung, Future Group, and even Godrej involved leveraging empathic research methods to go beyond the insights offered by traditional market research. These projects typically took 2-3 months, a timeframe that would seem unacceptably long for today's clients.

During that period, India's design education landscape was sparse, led by the National Institute of Design (NID) and IIT Bombay’s Industrial Design Center (IDC). Early adopters like IISc, IIT Delhi, IIT Kanpur, and SPA Delhi also began incorporating design into their curriculum. However, well-paying design research clients were mostly consumer product companies or well-funded non-profits.

Notably, India’s IT sector remained disconnected from the UX design revolution. Clients often criticized Indian designers, remarking, "Indian designers talk a lot about the 'Apple experience,' but they fail to deliver it in practice."

In subsequent years, UX design gained traction, leading to a parallel rise in UX research. In-house UX design teams began taking on research responsibilities, often supplemented by external agencies.

TODAY

A quick Google search reveals there are now over 2,000 design colleges in India. Institutions offering engineering or MBA programs have expanded to include full-fledged design degrees. With an estimated 100 graduates per college annually, India is producing approximately 200,000 designers every year. A designer friend once joked, "There are more designers in Italy than pizza chefs." We may soon find ourselves in a similar situation in India.

Several UX design firms, in the recent past scaled up significantly, with teams of 100-300 often acquired by large tech companies. However, while UX design has grown exponentially, other design disciplines have remained relatively stagnant.

The COVID-19 pandemic accelerated automation in UX research. At Turian Labs and other companies, remote research interviews became a standard practice, and tools like MIRO enabled seamless collaboration for synthesizing insights. For example, companies like UserTesting adopted automated workflows, using bots to screen participants and streamline interview processes, demonstrating how remote UX research evolved in response to global disruptions.

Interestingly, the Design Thinking movement, championed by Infosys CEO Vishal Sikka in 2014, gained traction among top business executives. This created a triple-engine effect: top management adopting Design Thinking-led processes, increased acceptance of UX research and design, and an abundant supply of formally trained UX designers.

FUTURE

While the rise of UX design and research has been meteoric, a new disruptor—AI—threatens to upend the field.

AI is already generating wireframes, website templates, content, icons, buttons, images, videos, and even conversations. Thousands of designers trained at lesser-known institutions or through online programs, working in comfortable offices of IT giants, risk becoming obsolete. This mirrors the fate of HTML programmers during Dot-Com 1.0, who were rendered redundant by platforms like WordPress and Wix.

In UX research, automation has advanced across the workflow. From participant recruitment to interview conduction via bots, automated discussion guides, transcription, and analysis, nearly every stage can be automated. For instance, startups like UXtweak are using AI to identify user pain points directly from heatmaps and recordings, bypassing the need for manual analysis. While current large language models (LLMs) occasionally falter with local contexts and vernacular nuances, this is a temporary limitation. Within 1-2 years in developed markets (and 5 years in complex markets like India), these capabilities will improve dramatically.

Emerging concepts like synthetic users—AI-generated profiles providing early prototype feedback—are already in development. For example, a health tech company could use synthetic users to test interfaces for elderly care apps, predicting usability challenges even before real users interact with the system. While adoption remains minimal for now, this will likely change rapidly. I predict that within five years, 50% of all UX research will rely on synthetic users.

However, the most profound shift is not merely automation. The current approach to UX research, rooted in ontological exploration and validation—aligning user mental models with proposed solutions—will become outdated. With technology and societal norms evolving at breakneck speed, the emphasis will shift to foresight-driven UX research. This involves anticipating future mental models before they emerge and designing for them.

For example, instead of asking users how they prefer to consume online news, foresight methodologies could leverage demographic-specific LLMs to predict their preferences based on trend hierarchies. Routine UX research tasks, where 80% of today’s effort is concentrated, will be rendered redundant by AI-generated templates and predictive models.

One promising direction is integrating foresight methods with UX research. For example, a retail brand could use LLMs to project how Gen Z’s shopping behavior might evolve over the next five years, allowing them to design not just for today’s user but for tomorrow’s. Similarly, trend-percolation hierarchies could help predict user preferences across social strata, enabling businesses to stay ahead of the curve.

The future of UX research lies at the intersection of classical design research methods, business foresight practices, and AI-enhanced tools. The leap is a massive one and may not necessarily be visible 'including foresight' in the new practices. Still, technology is likely to force this new framework on UX researchers. Just wait for it.

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