How Twelve Indian Design Leaders Across Fashion, Architecture, Embroidery, Media, and Education View AI in 2026: A Cross-Speaker Synthesis From the Parul Institute of Design Mumbai Industry Tour

Twelve speakers. Five disciplines. One question. The cumulative answer was unusually coherent across radically different professions.

Across the three days of the Parul Institute of Design Mumbai Industry Tour, no topic recurred as consistently as AI. Every one of the twelve speakers, from fashion editor to embroidery entrepreneur to architect to media executive to design educator, was asked about AI or addressed it unprompted. The themes were not coordinated between sessions. The convergences emerged because each of these speakers is currently working through the same question from a different professional position. This article synthesises what twelve design leaders said about AI in 2026 in their own working language, and what the cumulative position implies for design students entering the field.

The single most consequential AI story from the tour was Sameer Nair’s account of Applause Entertainment‘s decision to halt traditional animation on the Amar Chitra Katha catalogue. Applause had acquired the media rights to the historical and mythological library and spent nearly two years working through a standard 2D and 3D animation pipeline to produce premium twenty-minute episodes. Observing the exponential improvements in generative video and AI tools over a six-month period, the executive board halted the traditional pipeline and pivoted the entire project to an AI-assisted animation workflow. According to Nair, the results have been revolutionary in cost-effectiveness, speed, and scalability.

His framing of AI more broadly was historical.

Nair compared the corporate panic around AI to the late-1990s anxiety around the introduction of Microsoft Excel. Before automation, teams of human accountants spent days manually calculating ledgers on paper. Excel did not eliminate the accounting profession; it automated the tedious, mechanical aspects, allowing accountants to focus on high-level corporate strategy. Similarly, AI will handle the mechanical drudgery of rendering and asset generation in animation, allowing animators to focus on visual storytelling, character emotion, and creative direction. Those who learn to master AI tools will thrive in the new environment. Those who resist will become obsolete.

Gayatri Khanna at Milaaya Embroideries drew a working line that has proved durable across global luxury manufacturing. AI is already a useful tool for the concept stage of embroidery design: generating artwork inspiration, motif variations, graphic possibilities, and design concepts that a designer can review and develop. What AI cannot do is execute the actual hand embroidery, because luxury embroidery requires meticulous physical work by skilled artisans applying thread, needle, beading, and surface technique with a level of precision, judgment, and individual variation that machines cannot replicate.

The distinction matters because the question students often have is whether the entire field is at risk.

The answer from the founder of a multinational luxury embroidery house in 2026 was specific: the concept stage is shifting, the execution stage is not. Luxury clients specifically order individually handcrafted detail, and that demand will continue to depend on human execution. The same logic applies to 3D modelling, which Milaaya acknowledges exists in fashion but does not use because the company’s specialisation is embroidery and surface, not garment construction.

Kiran Kapadia‘s account of AI was practical, not abstract. He was specific about where the studio actually uses it.

Asked how Kapadia Associates uses AI, Kiran Kapadia offered three concrete examples rather than abstract endorsement.

• Parking optimisation: AI is used to design and plan parking flow patterns that minimise driving conflicts within a building, calculating the smoothest in-and-out routes to prevent accidents and congestion.
• Contextual image placement: AI is used to place rendered images of a proposed building into actual photographs of the Mumbai surroundings the structure will sit within, so that the client can see exactly how the new structure will look in its real urban context rather than in an isolated render.
• Climate and sustainability modelling: This is the heaviest AI use at the studio. AI is used to calculate precisely how sunlight will strike windows in May, how wind will move through skyscraper clusters during the monsoon, and other climate-driven variables that determine how comfortable a building will actually be to live in.

His broader advice on technology was unambiguous: do not become the slave of the tool. Determine the design aim first, then use whatever tools serve that aim.

Robert Verrijt at Architecture BRIO took a different angle. Asked about durable design skills for the next five years, he identified three: history (to place oneself within the larger world), software fluency (because speed with tools allows young architects to access better opportunities faster), and hand sketching with pen and paper. Despite computers and AI, sketching by hand remains a permanently powerful human skill. Sketching is a method of exploring ideas while communicating directly with another person. AI cannot sit at a table and doodle with a collaborator. The medium itself reminds the designer of the human community they are designing for.

He was honest, however, that the medium does not determine the moral content of design.

Historically, intimidating monumental architecture commissioned by oppressive rulers was also drawn by hand. The medium alone is not the guarantee of humane design. But computers carry their own risks: software can focus on numbers and cost optimisation in ways that crowd out the human community a building must serve. Both modes have value when used with judgment, but the human-scale presence that hand sketching enforces is part of why it remains essential to the discipline.

Rochelle Pinto at Vogue India approached AI through her concern with the fundamentals of writing and thinking. Her single most quoted line was that the best book to read is the dictionary, to improve vocabulary and to use AI effortlessly. The implicit argument is that AI rewards those with strong fundamentals: a writer with deep vocabulary, clear thinking, and good judgment uses AI as a productivity multiplier; a writer without those foundations becomes dependent on it.

Her broader concern was about the dependency pattern.

Pinto was direct about her worry with the younger generation’s growing dependence on shorter content and instant answers. Technology itself was not the problem. The problem begins when people become dependent on technology to think for them. She drew a parallel to constant use of navigation tools eroding a person’s underlying sense of direction. AI is a tool. The underlying intellectual work is the human’s responsibility.

Mr. Ajit Khare, Director of NIFT Mumbai, offered the synthesising line that captured the broader consensus across the tour. Master empathy, he argued, because the human brain created AI in the first place. The technology is a product of human thought; the discipline that designs with it must be grounded in deeper human understanding, not less. A designer who cannot understand the people they are designing for has no working advantage over an automated system. A designer who can understand people deeply remains essential regardless of how powerful the tools become.

Beyond the deep accounts, every other speaker addressed AI in their session, reinforcing the consensus.

• Neeta Lulla on costume design: The session did not address AI directly but reinforced the principle that costume design serves character, era, and emotion through research, craft, and intuition, areas where the human capacity for narrative judgment remains central.
• Abha Narain Lambah on heritage conservation: Conservation is grounded in deep research, historical understanding, and sensitivity to cultural emotion in heritage sites, none of which AI can substitute. The architect’s responsibility toward cultural preservation is irreducibly human.
• Kayzad Shroff and Maria Isabel Leon on contemporary architecture: Approach every project with a mix of child-like naivety and curiosity, a working principle that depends on human openness to context, site, and the people who will inhabit the space.
• Lodha design leadership on large-scale residential: Don’t design for luxury, design to solve problems. The problem-solving is rooted in understanding the users of a building at scale, which requires human judgment more than technological capacity.
• Shubhika Sharma on contemporary fashion: Building a brand identity, voice, and visual signature is a fundamentally human creative act. Internships are how the practical work is learned, not through algorithmic shortcuts.
• Nidhi Yasha on bridal couture: Customisation as the core of luxury depends on understanding individual clients, families, and events, a discipline that is fundamentally human and consultative.

Read together, the twelve sessions produce a coherent position on AI in creative industries that has more nuance than the typical public discourse.

• AI is a tool, not a replacement: Across radically different fields, speakers converged on the position that AI augments human creativity and displaces tedious mechanical work, but does not replace the underlying creative imagination.
• Master the tool, do not become its slave: Multiple speakers warned against dependency. AI works best for designers with strong fundamentals, deep vocabulary, historical knowledge, and clear creative judgment. Without those, AI accelerates mediocre work.
• Execution-stage craft remains human: Hand embroidery (Khanna), hand sketching (Robert Verrijt), bespoke client work (Yasha), client trust and design integrity (Kiran Kapadia), and editorial judgment (Pinto) all retain a human-execution dimension that current AI cannot replicate.
• Concept-stage AI is already operational: Multiple working studios are using AI for inspiration, ideation, image generation, optimisation, and modelling. The pipeline shift is happening now, not in some future.
• Empathy and cultural intelligence are the durable advantages: Empathy (Khare), cultural sensitivity (Lambah), audience understanding (Nair), client reading (Yasha, Sharma), and end-user empathy (Lodha) are the working competencies that AI cannot acquire and that human designers must develop.
• The historical parallels are useful: AI’s relationship to creative work resembles Excel’s relationship to accounting in the 1990s (Nair). The mechanical work is automated; the high-level judgment work remains human.

The consensus across the twelve speakers has direct implications for how design students at Parul Institute of Design should engage with AI during their education. First, learn the tools. The students who emerge from design education in 2026 onward without AI fluency will be at a structural disadvantage relative to peers who have learned to work with the technology. Second, build the underlying fundamentals: vocabulary, history, craft technique, design thinking, and empathy. AI rewards those with strong foundations and exposes those without them. Third, identify where the durable human craft of your discipline sits. For Fashion Design students, hand embroidery, bespoke fitting, and editorial judgment. For Architecture and Interior Design students, hand sketching, client trust, and site-sensitive design. For Animation students, narrative judgment, character emotion, and creative direction. For Product Design students, end-user empathy and the invisible UX craft. For Visual Communication students, editorial voice and conceptual depth. Fourth, do not become dependent. Use AI as a productivity multiplier on the foundations you have built, not as a substitute for building them.

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