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Introduction

I have been in design for over eight years. Before that, I worked in marketing and SAP consulting. That cross-disciplinary background has given me a useful vantage point — and what I see right now concerns me.

Most UX designers are stuck. Not because they lack skill or talent. But because they are still working the same way they did five or ten years ago, with a few AI tools added on top.

The AI era is not asking us to learn a new tool. It is asking us to think differently. And most of us have not made that shift yet.

This article is my honest take on what designers — at every level — should actually be doing right now.

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The Real Problem: We Are Still Working the Old Way

Here is what I observe in design teams across industries: designers are either ignoring AI completely, or using it just enough to say they use it. A prompt here. An image generated there. Nothing that changes how they actually work or think.

And I get it. There is comfort in what you know. Design thinking — empathise, define, ideate, prototype, test — has been our framework for years. It works. It is human-centred. It is what we were taught.

But design thinking was built for a simpler time. A time when you could focus on one user, one problem, one solution.

Today? Products live inside complex ecosystems. A user’s journey touches multiple apps, platforms, and touchpoints — often in ways that are hard to predict. Designing one screen in isolation, without understanding the bigger picture, is like designing a door without knowing what building it belongs to.

The shift I believe we need — and that most design conversations are still missing — is from design thinking to systems thinking and critical thinking.

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What Systems Thinking Actually Means (And Why It Matters)

Systems thinking is simply the ability to see how things connect. How one part of a product or experience affects another. How a change in one place ripples through the whole.

Let me give you a real example from my own work.

I was working with a large global beverage company on a product called MDM — Master Data Management. The brief was straightforward: improve the UX of this product. Most designers would have focused on the screens, the flows, the user tasks. I did that too.

But I also created a complete system map of the entire landscape — the data flows, the teams involved, the upstream and downstream dependencies, how this product connected to everything else. That exercise changed everything. It surfaced design decisions and problems I would have completely missed if I had only looked at the product in isolation. The UX I ended up designing was fundamentally better because I understood the system it lived in.

That is what systems thinking gives you. Not just better design execution — better design decisions.

A concept I find equally powerful is First Principles Thinking, which Elon Musk has talks about extensively. The idea is simple: instead of doing what has always been done, break a problem down to its most basic truths and build up from there. In design, this means questioning inherited patterns. Asking: why does this work this way? Does it have to? What would we build if we started from scratch?

In a world where AI is changing the rules every few months, this kind of thinking is not a nice-to-have. It is a survival skill.

Design Thinking	Systems + Critical Thinking
Focus on the user’s immediate task	Understand the ecosystem the user lives in
Linear, step-by-step process	Non-linear, iterative
Great for bounded, defined problems	Essential for complex, connected challenges
Asks: “What does the user need?”	Asks: “Why does this problem exist at all?”
Works well for product-level decisions	Necessary for platform and AI-era challenges

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How I Actually Use AI Tools in My Workflow

Okay, let us talk tools — because this matters too.

I use Figma Make regularly for ideation and design deliverables. Tasks that used to take me days — exploring layout directions, generating variants, producing design assets — I can now do in hours. That is not cutting corners. That is freeing up my time for the thinking that actually matters.

I also use Microsoft Copilot heavily in my research and ideation phases. Synthesising user research, exploring competing ideas, stress-testing a flow or information structure — Copilot helps me do that faster and more thoroughly than I could on my own.

But here is the honest caveat: AI tools only work as well as the thinking you bring to them. If I ask Copilot a vague question, I get a vague answer. When I bring a clear context, a well-framed problem, and sharp hypotheses — the output is genuinely useful. The tool amplifies your thinking. It does not replace it.

I also want to name something I see constantly as a broken experience — and it is ironic, because it is happening inside AI products themselves. So many AI tools are overwhelming. Dense interfaces. Unclear navigation. Too many features crammed onto one screen. I have personally opened a tool, spent five minutes trying to figure out how to get started, and just left. Moved on to the next one.

This is a massive UX failure happening at scale — and it is a real opportunity. Designers who know how to make AI tools simple, clear, and human-friendly are solving one of the most urgent design problems of our time. According to the Nielsen Norman Group, cognitive overload is one of the biggest barriers to AI tool adoption. That is a human problem. And human problems need designers.

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What You Should Be Doing Right Now — By Level

Here is my honest take, broken down by where you are in your career.

If you are an entry-level designer:
Build real fluency with AI terminology, design tools — not just awareness. Use Figma Make, Google Stitch, and Uizard regularly. Experiment. Break things. Learn what these tools can and cannot do. At the same time, start practising systems thinking on every project — even if nobody asks you to. Create a simple system map or a high-level journey map for every brief. It will change how you see design problems. Make it a habit now, before you get set in your ways.

If you are a mid-level designer:
This is the most critical point in your career right now. The temptation is to become a very fast executor — faster wireframes, quicker prototypes, cleaner handoffs, all powered by AI. That is valuable. But it is not enough. The mid-level designers who will become senior leaders are the ones who are also building strategic skills: understanding business context, communicating design decisions to stakeholders, connecting UX choices to real outcomes. Learn to think beyond the screen.

If you are a senior designer:
Your job is to change how your team thinks. If your design process looks roughly the same as it did in 2020, that is worth examining. Introduce system mapping as a standard practice. Normalise AI tool experimentation in your team. Push back when product decisions optimise one touchpoint at the expense of the whole experience. You have the influence to raise the bar — use it.

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Stop Waiting for Your Company to Upskill You

This might be the most important thing I want to say in this entire article.

I see so many designers waiting. Waiting for their company to run an AI training. Waiting for the approved tools list. Waiting for the official strategy to come down from leadership. Some companies are moving fast. Most are not.

Here is the reality: the AI landscape is changing faster than any company training programme can keep up with. Think about it — the amount of change we have seen in AI in just the last three years is greater than what happened in the previous ten years combined. New tools. New interaction models. New user behaviours. New design challenges. Every few months, something shifts.

The designers who are genuinely ahead right now did not get there through mandatory training. They got there because they were curious on their own time. They experimented. They built side projects. They joined communities. They applied new thinking to their actual work without waiting for permission.

This is not about working harder. It is about owning your own career in a world that is moving very fast. Waiting is the same as falling behind.

My simple advice: set aside even one hour a week for unstructured AI tool exploration. No deliverable attached. No goal. Just play. The return on that hour compounds faster than you think.

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A Simple Framework: Three Layers of Designer Value

Here is how I think about where to invest my energy:

Layer 1 — Execution (let AI do more of this)
Wireframing, design variants, research synthesis, copy exploration, prototype iteration. Use AI here. Spend less time on execution, not more.

Layer 2 — Thinking (this is your real job)
Systems mapping, critical analysis, connecting business goals to user needs, challenging assumptions. AI can support this, but the thinking is yours. This is where your value lives.

Layer 3 — Influence (this is irreplaceable)
The ability to shape how your organisation thinks about experience. Talking to stakeholders in their language. Connecting design to business outcomes. Building trust. No AI tool touches this layer. It is built entirely from experience, relationships, and credibility.

The designers who work across all three layers — and know which layer they are in at any given moment — are the ones who will define what this profession looks like next.

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FAQ

Will AI replace UX designers?

No — but it will replace designers who do not evolve. The tasks most at risk are the repetitive ones: basic wireframing, templated research, asset generation. What AI cannot do is think strategically, navigate complexity, or bring genuine human empathy to hard problems. Designers who build these capabilities while using AI for execution become more valuable, not less.

What skills should a UX designer focus on right now?

Systems thinking, critical reasoning, and AI-augmented workflows are the big three. On the tools side, get comfortable with Figma Make, Microsoft Copilot, Stitch, and Uizard (or the tools that are permitted to use in your organization). On the thinking side, develop your ability to map ecosystems, question assumptions, and communicate design decisions in business terms. That combination is hard to replicate.

What is systems thinking and why should designers care?

Systems thinking is the ability to see how the parts of a complex product or experience connect — and how changing one thing affects everything else. Designers who only think about the screen in front of them miss the bigger forces that determine whether their design actually works in the real world. In the AI era, where products are more interconnected than ever, systems thinking is essential.

What is the difference between design thinking and systems thinking?

Design thinking is great for solving well-defined, human-centred problems. Systems thinking is what you need when the problem is complex, interconnected, and hard to define. They are not opposites — systems thinking is the upgrade you add on top of design thinking, especially when working on AI products, platforms, or large ecosystems.

How do I actually use AI tools like Figma Make and Copilot day to day?

Use them to speed up the repeatable parts of your work and use the time you save for deeper thinking. The key is bringing good inputs — vague prompts give vague results. The clearer your thinking, the more useful the AI output. Build your own personal workflow through experimentation, not by waiting for your company to tell you how.

How should design students prepare for an AI-first job market?

Show your thinking, not just your visuals. Include system maps, journey maps, and your decision-making rationale in your portfolio. Document at least one project where you used AI tools and explain how. Develop a clear point of view about design, users, and the role of experience in business — that perspective is what makes you stand out.

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Conclusion

The AI era is not the end of UX design. It is actually a clarifying moment. The work that has always mattered most — understanding people, asking better questions, connecting human needs to real outcomes — is not going anywhere. If anything, it matters more now, because the execution layer is increasingly handled by machines.

The designers who will thrive are not the ones with the longest list of AI tools. They are the ones who have made the mental shift — from executors to thinkers, from screen designers to experience architects, from waiting for direction to owning their own growth.

AI changed more in three years than it did in the previous decade. That pace is not slowing down. The only way to keep up is to stay curious, keep experimenting, and never outsource your own development to a company training calendar.

Start now. The gap is already widening.

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Mohan Kumar is Manager of Human Experience at a global MNC, with over eight years in design and a background spanning marketing and SAP consulting.

If this resonated with you, follow Mohan Kumar on LinkedIn for more on design, AI, and the future of human experience.

 

Picture this: a customer sees a product on Instagram, researches it on their laptop, visits a store to touch and feel it, and then orders it through a mobile app for home delivery. Along the way, they interact with a chatbot, read reviews on a third-party platform, and ask a store associate a question. This is not an unusual shopping journey in 2025. According to research tracking 46,000 retail shoppers, 73% engage across multiple channels during their buying journey. The modern consumer is omnichannel not by design, but by instinct.

The question for brands is no longer whether to have an omnichannel strategy. It is whether their omnichannel strategy is good enough to keep pace with how their customers actually behave.

Why Omnichannel Matters More Than Ever

The business case for omnichannel excellence is overwhelming. Companies with strong omnichannel engagement retain 89% of customers, compared with just one-third for those with weaker strategies. Customers who purchase both online and in-store are worth roughly one-third more over their lifetime than single-channel shoppers. Effective omnichannel programs drive annual revenue growth three times higher than less cohesive strategies. And campaigns leveraging three or more channels achieve order rates five times higher than single-channel campaigns.

Yet research from Forrester’s US Customer Experience Index found that CX quality reached an all-time low in 2024, with a lack of seamless experiences cited as a primary factor. The gap between what customers expect and what brands deliver is not closing fast enough. The brands that are closing it are worth studying closely.

Disney: Omnichannel as an Art Form

Disney’s approach to omnichannel CX is perhaps the most cited example in the industry — and for good reason. The experience begins before a guest ever arrives at a park. The My Disney Experience platform allows visitors to plan every detail of their visit, from restaurant reservations to FastPass selections, across any device. The experience continues in-park through the MagicBand — a wearable device that acts simultaneously as a room key, payment method, park ticket, photo storage system, and food ordering tool. The physical and digital are so seamlessly integrated that the seam is invisible.

What makes Disney’s approach instructive for any brand is the underlying philosophy: every touchpoint is designed from the customer’s perspective, not the organisation’s operational convenience. The MagicBand did not exist because Disney needed a new technology product. It existed because Disney’s customers needed to spend less time waiting and managing logistics and more time experiencing joy. Technology served the experience, not the other way around.

DHL Express: Omnichannel at 123-Country Scale

DHL Express offers a compelling case study in omnichannel CX at extraordinary scale. Through its “First Choice” programme, active since 2006, DHL has built an omnichannel experience intelligence system across 123 countries, with 9,000 employees responsible for reviewing and acting on millions of pieces of customer feedback annually. In a single year, the team reviewed 2.6 million omnichannel customer experience signals — spanning phone calls, emails, surveys, digital interactions, SMS messages, and social media — to understand and improve the customer journey.

DHL’s approach demonstrates that omnichannel is not just about delivering consistent experiences across channels. It is about listening consistently across channels and using those signals to drive continuous improvement. The organisation that knows what its customers are experiencing across every touchpoint — and acts on that knowledge in real time — has a decisive advantage over one that monitors only the channels it finds convenient to monitor.

The Rise of Social Commerce

One of the most significant shifts reshaping omnichannel strategy in 2025 is the rise of social commerce — the blending of social media discovery and purchase into a single seamless experience. Fifty percent of global shoppers discover products on social platforms, and 110 million Americans will shop directly through social channels in 2025. Platforms like TikTok, Instagram, and in India, platforms like Meesho and ONDC-enabled apps, are collapsing the distance between inspiration and transaction.

For brands, this means the omnichannel map has expanded again. A strategy that accounted for website, app, and physical store must now integrate social commerce — ensuring that the experience of discovering and purchasing on Instagram is as seamless and brand-consistent as any other channel. The customer journey can now begin in a video watched at midnight and complete in three clicks without ever leaving the platform.

Mobile-First Is Now Mobile-Only for Many Customers

Mobile shopping now represents 57% of global retail e-commerce sales, expected to reach 62% by 2027. For Indian brands, the figure is even higher — India’s mobile-first consumer base means that for a significant portion of the market, the mobile app is not one channel among many. It is the only channel that matters.

Leading brands are responding by designing their entire customer experience around the mobile interaction first, and then adapting for other channels. This inversion of the traditional design hierarchy — from desktop-down to mobile-up — is producing more intuitive, faster, and more friction-free experiences across the board.

The Pitfalls: What Goes Wrong

Even experienced brands make omnichannel mistakes. The most common is data fragmentation — customer data siloed across e-commerce platforms, point-of-sale systems, CRM databases, and marketing tools, making it impossible to build a single, accurate view of the customer journey. Without a unified customer view, personalisation is guesswork, and channel transitions create friction rather than flow.

The second most common failure is treating omnichannel as a technology project rather than a customer experience project. The infrastructure is necessary but not sufficient. The brands that truly excel at omnichannel are those that have built a culture of customer-centricity that permeates every team and every touchpoint — technology enabled, but human in its orientation.

In 2025, the most successful brands are those treating omnichannel not as a strategic project with a completion date, but as an ongoing operating philosophy — one that evolves continuously as customer behaviour evolves. The customer never stops moving. The winning brands never stop following.

Sources: Medallia Omnichannel Experience Report | VML Future Shopper 2025 | Probe Group Omnichannel CX Report March 2025 | Callnovo Omnichannel Contact Centre Report 2025 | Marketing LTB Omnichannel Statistics 2025

The phrase “digital transformation” has been overused to the point of near-meaninglessness in boardrooms around the world. But in India, it carries a weight and urgency that cuts through the jargon. India’s digital transformation market was estimated at $124.42 billion in 2025 and is projected to reach $267.01 billion by 2030 — a compound annual growth rate of 16.5% that represents one of the most significant economic accelerations in the world.

Behind these numbers is a story about how Indian enterprises are fundamentally reimagining the way they serve their customers — not just digitising existing processes, but rebuilding customer journeys from first principles in a mobile-first, AI-enabled, data-rich world.

The Drivers: Why Now Is Different

India’s digital transformation wave has been building for years, but several forces have converged in the mid-2020s to make it irreversible. Smartphone penetration has surpassed 73%, with monthly average data consumption per user exceeding 19 GB. Cloud-native technologies are projected to comprise 70% of India’s total cloud market. Indian enterprises are directing approximately $160 billion of IT spending toward cloud, AI, and cybersecurity in FY 2025. And 87% of surveyed firms have reached “Enthusiast” or “Expert” AI-maturity stages, particularly in manufacturing and telecom.

Perhaps most significantly, the Indian consumer has transformed. The customer who might once have accepted a 48-hour response from a bank’s customer service team now expects resolution within minutes — through WhatsApp, through an app, or through an AI-powered voice interface. Businesses that cannot meet this expectation do not just risk losing a transaction; they risk losing the customer permanently. ServiceNow’s 2025 India research found that 89% of Indian consumers are willing to switch brands due to slow or inefficient service.

The BFSI Transformation: India’s Most Dramatic CX Pivot

No sector illustrates India’s customer journey transformation more dramatically than Banking, Financial Services, and Insurance (BFSI). A decade ago, the dominant image of banking in India was the physical branch — long queues, paper forms, and a relationship mediated entirely by a human teller. Today, the dominant image is the mobile app.

India’s leading private banks have invested massively in digital-first customer journeys. Account opening that once required a branch visit and a stack of documents can now be completed in minutes through video KYC. Loan applications that involved weeks of processing are now completed and approved within hours. Customer queries that would have required a phone call are resolved by AI-powered chatbots available around the clock.

The results of this transformation are measurable. Banks that have invested in digital CX have seen significant improvements in customer satisfaction scores, reductions in cost per interaction, and meaningful gains in cross-sell and upsell rates. AI-driven recommendation engines are enabling banks to offer the right product to the right customer at precisely the right moment in their financial journey.

Retail and E-Commerce: Hyperlocal Meets High-Tech

India’s retail transformation is playing out at the intersection of massive scale and hyperlocal specificity. The e-commerce platforms that have won in India are those that have understood that the country is not one market but many — different languages, different cuisines, different shopping habits, different price sensitivities — and have built customer journeys that reflect this diversity.

The most successful platforms combine sophisticated AI personalisation with deeply local content and logistics. They know that a customer in Lucknow has different preferences from a customer in Chennai, and they serve each customer a version of the experience tailored to their specific context. They offer cash-on-delivery alongside digital payments, because digital payment adoption, while accelerating rapidly, is not yet universal. They build in regional language support, because the next 200 million Indian internet users will not all be comfortable in English.

Manufacturing and MSMEs: The Transformation Frontier

While large enterprises have led India’s CX transformation, the next frontier is the country’s 63-million-strong MSME sector — the backbone of the Indian economy, accounting for approximately 17% of GDP. For small and medium enterprises, digital transformation has historically felt like a luxury reserved for large corporations with large budgets. This perception is changing rapidly.

Cloud-based CX platforms, available on a subscription basis, have dramatically lowered the cost of entry. A small textile manufacturer in Surat can now deploy a WhatsApp chatbot for customer queries and a digital order management system for the fraction of what a custom-built solution would have cost five years ago. Government initiatives under Digital India are further accelerating this democratisation of digital CX tools.

EY’s March 2025 report on India’s Industry 4.0 journey highlights that customer-centric growth in the digital era represents a paradigm shift for Indian manufacturing firms. The report emphasises that embracing digital technologies is no longer optional for MSMEs seeking to maintain competitiveness — it is the price of participation in global and domestic supply chains that increasingly require digital-first engagement.

The Road Ahead

India’s digital transformation journey is far from complete. Legacy system integration remains a significant challenge, particularly in large financial institutions and government-linked enterprises. The talent pipeline for AI, data science, and digital CX design needs to continue expanding to meet demand. And the digital divide between urban and rural India — narrowing but real — means that transformation strategies must include pathways for customers who are still on the early part of their digital journey.

But the direction of travel is unmistakable. India’s enterprises are transforming their customer journeys at a pace and scale that few predicted even five years ago. AI is contributing an estimated $200 billion of productivity gains by 2030. PwC estimates that AI alone could contribute $957 billion to India’s GDP by 2035. The customer experience is at the centre of this value creation — and the businesses investing in it now are building advantages that will compound for years to come.

Sources: Mordor Intelligence India Digital Transformation Market Report 2025 | EY Digital Transformation Report March 2025 | ServiceNow India CX Report 2025 | India-Briefing Digital Transformation Guide | NASSCOM Digital CX Services Report