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Harvard Business Review
10 hours ago
- Business
- Harvard Business Review
A Guide to Building Change Resilience in the Age of AI
There's near universal consensus that AI will fundamentally change how business is done, yet most organizations have not yet seen a substantive impact from their AI efforts. A BCG Global Survey of 1,000 CXOs in more than 20 sectors reports that just 26% of organizations have achieved value from AI, realizing an average cost savings of 45% and 60% higher revenue growth compared to peer firms. Why such disappointing results? The survey found that among the many challenges organizations face in implementing AI initiatives, 70% are related to people and processes. While it's true that organizations face additional technical barriers such as poor data quality, integration complexity, or infrastructure costs, our collective experience working across hundreds of companies comports with the study's finding: The primary obstacle is the ability of companies to adapt, reinvent, and scale new ways of working. We call this change resilience. Why Change Resilience Is Scarce In the past, organizational transformation was episodic. You modernized your systems, trained your people, and operated in a stable environment until the next wave of disruption hit. But now AI is advancing at a pace that far exceeds most organizations' ability to adapt, and the change is unrelenting. Business leaders find it harder to anchor AI transformation in a traditional roadmap or use conventional means to drive change-management initiatives. Five-year strategies no longer hold. Annual planning cycles can't keep up. Traditional financial, risk, and legal controls lag further and further behind the onset of new risk types. Static operating models become liabilities. Even the newer ways of working, like agile methodologies, broadly adopted during the rise of the software era, aren't sufficient. To compete in this volatile environment, leaders need to embrace continual change, otherwise they face irrelevance from inaction or burnout from chasing shiny objects. Change resilience is the capability that will equip organizations to seize the opportunities and preempt the threats presented by fast-evolving technology. It's an enterprise‑wide reflex that converts continual disruption into repeatable learning loops that create value. It uses three muscles: Sensing, or the ability to pick up weak technological, competitive, or societal signals early Rewiring, or the capacity to redeploy talent, data, capital, and decision rights in days or weeks, not fiscal quarters Lock‑in, or the discipline to codify what a team learns (in process, code, or policy) so the next initiative starts from a higher baseline instead of reinventing the wheel Together, these muscles can keep an organization's metabolism in step with AI's rapid advances. Shopify offers a compelling example of change resilience in action. Rather than layering AI on top of existing operations, the company continuously rewires itself to stay ahead of what's next. In 2023, Shopify made the bold decision to spin off its entire logistics arm, one it had spent years building, to refocus on product innovation. This reset enabled Shopify to rapidly launch AI-native features like Sidekick, an embedded assistant for entrepreneurs that helps with everything from marketing copy to sales insights. By shedding complexity and codifying learnings from past pivots, Shopify unlocked speed and focus, allowing it to serve more than a million businesses with tools that reflect the evolving expectations of digital commerce. Its ability to sense, rewire, and lock in new ways of working positions it not just as an adopter of AI, but as a company continuously reshaping itself to thrive in the AI era. To understand how change resilient your organization is, ask yourself: Can employees be redeployed to fast-moving, high-priority initiatives to respond to changes in technological capabilities without the need to overhaul budgets or org charts? If a team member had an idea today, do they have the motivation, access, tools, and support to start experimenting? When an experiment shows potential is there a clear path for scaling and embedding it across the business? Is failure treated as a learning opportunity and openly shared to improve the next attempt? If you can't answer 'yes' to most of these questions, then your organization does not yet have the change resilience required to turn your AI strategy into durable performance gains. A Five-Step Playbook for Strengthening Change Resilience Here are the steps you need to take as a leader and organization to improve your change resilience: 1. Learn: Understand the toolsets, mindsets, and skill sets. To surface weak spots in toolsets, mindsets, and skill sets, it's important to get your employees to engage with AI and launch experiments. Use these experiments to develop an intuition for how your company might reimagine its processes while also identifying and eliminating cultural barriers that penalizes failed pilots or technical bottlenecks that makes data access a month-long ticket. Accenture began by encouraging every function (from sales to HR) to build micro-apps that solved a single pain point. Within 10 months this 'sandbox' approach produced 300 generative-AI apps, most of them lightweight utilities such as a proposal draft buddy or meeting-note summarizer. Because each app is owned by the team that built it, employees see immediately how AI reshapes their day-to-day work, shifting the culture from passive adoption to active experimentation. To fuel participation, Accenture is training 250,000 employees in gen AI skills and giving every learner a safe data playground. Early analysis shows these micro-bets matter: Gen AI is already saving 12% of working hours and boosting output quality by 8.5%, creating momentum for larger transformations. 2. Do: Launch targeted interventions. Address each gap in change resilience with the lightest-weight move that can generate momentum in weeks, not quarters. If the culture shies away from risk, introduce 'micro-bets': 10-day experiments with a public celebration ritual for learnings, not outcomes. Where skills lag, run cohort-based sprints that pair domain experts with data scientists to ship a working AI concept by sprint's end. The product becomes both a capability and a proof of possibility. If tool sets are the drag, deploy a self-serve data playground or low-code workflow builder so teams can test ideas. When a tactic moves the needle, codify it into playbooks, reusable code, amended policies, and broadcast the template company-wide. Singapore-based DBS Bank created a monthly 'north star & feedback' ritual that flags cultural, skill, and tooling frictions and then assigns cross-functional 'mini-squads' to attack the biggest challenge. One early scan revealed manual hand-offs that were slowing loan approvals. Within weeks a new AI credit-assessment workflow was live, which now processes around 380,000 lending applications a year and cuts manual work by 85%. Similar micro-interventions have seeded more than 800 production AI models across 350 use cases, generating an estimated US $563 million in economic value in 2024 alone. Each successful fix is codified into a bank-wide playbook through DBS's digital academy, ensuring that every cycle of experimentation leaves the organization measurably more change-resilient than the last. 3. Imagine: Challenge your team to start fresh. Don't modernize the old operating model; invent a new one. The functions of the future will not look like the work functions of today. AI-enabled organizations have entirely new roles, workflows, and value propositions. Moderna embodied this creativity when it merged its technology and human resources departments into a single function, aiming to redefine work responsibilities by distinguishing between tasks best suited to humans and those that can be automated. This strategic move, influenced by Moderna's partnership with OpenAI, led to the creation of more than 3,000 customized AI agents for various business functions, including clinical trials and HR operations, fundamentally modernizing the workplace dynamics and roles of HR and technology. 4. Act: Embrace ongoing cycles of measurement, learning, and re-investing Don't get stuck in the trough of disillusionment. Every wave of technology comes with both inflated expectations and real strategic potential, so it's important to move early, learn fast, and keep going. P&G has approached change resilience as an ongoing capability, building momentum across toolsets, skillsets, and mindsets with measurable outcomes. Its custom Generative AI platform, ChatPG, now has more than 30,000 employees onboard and supports more than 35 production use cases. In marketing, it has cut concept-testing cycles from months to days, dramatically reducing costs. In supply-chain operations, pilots combining AI with plant-floor sensors have already enabled fully autonomous shifts at Gillette facilities, part of a broader plan that the CFO estimates could unlock $2 billion in productivity gains. On the skills front, the company rolled out AI reskilling, where an initial cohort of 200 employees earned more than 4,400 badges and nearly 90 certifications, applying their learning to dozens of digital initiatives. These metrics allow P&G to tie upskilling directly to business impact and optimize its learning investments accordingly. Culturally, P&G reinforces a growth mindset through its ' School of P&G,' which blends formal training (10%), mentorship (20%), and on-the-job experience (70%). It further personalizes learning using AI that recommends content and pathways based on individual goals and behavior, an approach that has lifted engagement scores in internal surveys. By integrating bold bets, fast learning loops, and targeted reinvestment, P&G is converting AI experimentation into enterprise-wide performance gains. 5. Care: Put human wellbeing at the center of change Rapid change can exhaust even the most capable workforce. Without deliberate attention to wellbeing, enthusiasm for new technology quickly turns into fatigue and resistance. The care muscle therefore focuses on creating psychological safety, monitoring sentiment in real time, and giving people the resources (time, coaching, and flexibility) they need to stay healthy and engaged while they learn new ways of working. When leaders treat wellbeing data with the same rigor as financial metrics, they not only protect their people but also accelerate adoption of the very innovations that drive competitive advantage. Cisco shows how meeting employees' physical, mental, and social needs can accelerate rather than distract from digital reinvention. In 2024, 84% of its workforce logged a combined 2.3 million team check-ins, giving leaders a real-time read on sentiment and workload. At the same time, Cisco embedded an AI-powered 'WellNest' bot to serve up personalized resources for physical, mental, financial, and social wellbeing. These holistic supports have kept engagement high while the company scales AI pilots across the business, proof that caring for people is a prerequisite to sustained, resilient transformation. . . . When leaders embrace change resilience, they unlock a flywheel of continuous adaptation that makes each AI experiment faster, each reinvention easier, and each success more scalable. Organizations like Shopify, DBS, Moderna, and P&G show what's possible when change becomes a muscle, not a reaction. In contrast, those who treat AI as a one-time upgrade risk falling into the trap: using new tools to preserve old models. In today's AI era, the divide between early movers and fast followers is widening into a chasm. The difference is not access to technology. It's the courage and discipline to keep changing.
Time of India
13 hours ago
- Business
- Time of India
Vargab Bakshi joins GoKwik as chief growth officer
GoKwik , India's e-commerce enabler , has onboarded Vargab Bakshi as chief growth officer . With a strong pedigree in building and scaling internet-first businesses, Bakshi is set to drive GoKwik's next phase of growth through brand, partnerships, international expansion, and ecosystem building. He will lead GoKwik's entire growth charter, including marketing, GTM, global partner ecosystem, and product-led growth (PLG) across the company's suite of software products, including those on the Shopify App Store and beyond. Before joining GoKwik, Bakshi held key leadership roles at Shopify and Wix. At Shopify, he was a founding member of the India team and played a pivotal role in establishing Shopify's presence in the country. He built and led the go-to-market strategy for India and emerging markets, launched and scaled the entire APAC partner ecosystem, and positioned Shopify as a go-to brand for Indian D2C entrepreneurs and developers. At Bakshi served as VP and country head for India, where he was responsible for the brand's regional presence across marketing, enterprise sales, partnerships, and product localisation. He also led the developer ecosystem and significantly grew brand adoption, particularly among non-tech users and digital agencies. Bakshi is also the creator of GrowKwik, a D2C-first, content-first, influencer-led education channel by GoKwik, aimed at empowering ecommerce entrepreneurs. The platform has garnered over 500,000 cumulative followers across Instagram and YouTube and continues to serve as a high-impact marketing and learning channel. Commenting on the new addition to his leadership, Chirag Taneja, co-founder and chief executive officerof GoKwik, stated, "Vargab brings a rare blend of ecosystem thinking, product-led growth and global GTM expertise with a strong empathy for merchants from his Shopify days. As we scale our presence across borders, his leadership will be key in building a growth engine that is brand-led, product-first, and global by design. We're excited to have him onboard." Bakshi expressed his enthusiasm, saying, "After years of helping ecommerce businesses scale at Shopify and Wix, joining GoKwik felt like a natural next step. GoKwik sits at the intersection of data, AI, consumer behavior, and commerce enablement — building truly India-first, yet globally scalable solutions for online merchants. With deep insights from 130 million shoppers in our network, we're uniquely positioned to create powerful software that drives growth for merchants. I'm excited to bring my experience in go-to-market, ecosystem building, and commercial strategy to help GoKwik become the most loved growth-tech company in ecommerce."
Fast Company
17 hours ago
- Business
- Fast Company
AI embarrassed them at work. Don't let this happen to you
Dearest reader, I hope this article finds you in good health. I deeply desire also that if you use generative AI to boost your productivity at work, that you, for all that is good and holy, review everything it produces, lest it hallucinate data or quotes or address your boss by the wrong name—and you fall on your face and embarrass yourself. Sincerely, Your unchecked AI results AI is taking the workforce by storm and stealth, as the rules for how to use it are still being written and employees are left to experiment. Many employees are under pressure to adopt AI: Some companies such as Shopify and Duolingo are requiring employees to use AI while others are ratcheting up productivity expectations so high that some workers may be using it just to meet demands. This creates an environment ripe for making mistakes: we've seen Grok spew hate speech on X, and more recently an AI agent deleted an entire database of executive contacts belonging to investor Jason Lemkin. Funnily enough, no one wants to share their own AI-induced flub but they have a story to tell from someone else. These AI nightmares range from embarrassing to potentially fireable offenses, but together they reveal why there always needs to be a human in the loop. The Email You Obviously Didn't Write Failing to review AI-generated content seems to be the most common mistake workers are making, and it's producing errors big and small. On the small side, one worker in tech sales who asked to remain anonymous tells Fast Company her colleague used to ask ChatGPT to write 'natural-sounding sales emails,' then contacted clients with Dickensian messages that began, 'I hope this email finds you in good health.' The Slackbot Gone Awry Similarly, Clemens Rychlik, COO at marketing firm Hello Operator, says a colleague let ChatGPT draft Slack replies largely unchecked, and addressed him as Clarence instead of Clemens. When Clemens replied in good fun, calling his colleague the wrong name too, 'their reaction was, of course, guilt and shame—and the responses after that were definitely 'human.'' The Inappropriate Business Recommendation On the larger side, some people are using AI to generate information for clients without checking the results, which compromises the quality of their work. Alex Smereczniak is the CEO of the startup Franzy, a marketplace for buying and selling franchise opportunities. His company uses a specially trained LLM on the back end to help customers find franchises, but Smereczniak says their clients often don't know this. So when one client asked to see opportunities for wellness-focused franchises, and the account manager recommended she open a Dave's Hot Chicken, she was less than pleased. Smereczniak says the employee came clean and told the customer he had used AI to generate her matches. 'We took a closer look and realized the model had been weighting certain factors like profitability and brand growth too heavily, without enough context on the prospect's personal values,' says Smereczniak. 'We quickly updated the model's training data and reweighted a few inputs to better reflect those lifestyle preferences.' When the Franzy team fired up the AI again, the model made better recommendations, and the customer was happy with the new recommendations. 'At a startup, things are moving a million miles a minute,' Smereczniak says. 'I think, in general, it's good for us all to remind ourselves when we are doing something client-facing or externally. It's okay to slow down and double check—and triple check—the AI.' The Hallucinated Source Some companies have used AI mistakes to improve their work processes, which was the case at Michelle's employer, a PR firm. (Michelle is a pseudonym as she's not technically allowed to embarrass her employer in writing.) Michelle tells Fast Company that a colleague used Claude, Anthropic's AI assistant, to generate a ghostwritten report on behalf of a client. Unfortunately, Claude hallucinated and cited imaginary sources and quoted imaginary experts. 'The quote in this piece was attributed to a made-up employee from one of the top three largest asset management firms in the world,' she says. But the report was published anyway. Michelle's company found out by way of an angry email from the asset management firm. 'We were obviously all mortified,' Michelle says. 'This had never happened before. We thought it was a process that would take place super easily and streamline the content creation process. But unfortunately, this snafu took place instead.' Ultimately, the company saved face all around by simply owning up to the error and successfully retained the account. The PR firm told the client and the asset management firm exactly how the error occurred and assured them it wouldn't happen again thanks to new protocols. Despite the flub, the firm didn't ban the use of AI for content creation—they want to be on the leading edge of tech—nor did it solely blame the employee (who kept their job), but it did install a series of serious checks in its workflow, and now all AI-generated content must be reviewed by at least four employees. It's a mistake that could have happened to anyone, Michelle says. 'AI is a powerful accelerator, but without human oversight, it can push you right off a cliff.' The AI-Powered Job Application AI use isn't just happening on the job, sometimes it's happening during the job interview itself. Reality Defender, a company that makes deepfake detection software, asks its job candidates to complete take-home projects as part of the interview process. Ironically it's not uncommon for those take-home tests to be completed with AI assistance. As far as Reality Defender is concerned, 'everyone assumes, and rightfully so, that AI is being used in either the conception or full on completion for a lot of tasks these days,' a rep for the company tells Fast Company. But it's one thing to use AI to augment your work by polishing a résumé or punching up a cover letter, and another to have it simply do the work for you. Reality Defender wants candidates to be transparent. 'Be very upfront about your usage of AI,' they said. 'In fact, we encourage that discretion and disclosure and see that as a positive, not a negative. If you are out there saying, 'Hey, I did this with artificial intelligence, and it's gotten me to here, but I am perfectly capable of doing this without artificial intelligence, albeit in a different way,' you are not only an honest person, but it shows your level of proficiency with artificial intelligence.' 'Personally, I don't think it's necessarily bad to use [AI] to some extent, but at the very, very least, you want to check what's being written and reviewed before we share it,' says Rychlik at Hello Operator. 'More broadly, I ask everyone to pause regularly on this because if your first instinct is always 'ask GPT,' you risk worsening your critical thinking capabilities.' Rychlik is tapping into a common sentiment we noticed. On the whole, companies are trying to use mistakes as a learning opportunity to ask for transparency and improve processes. We're in an age of AI experimentation, and smart companies understand mistakes are the cost of experimentation. In this experimental stage, organizations and employees using AI at work look tech-savvy rather than careless, and we're just finding out where the boundaries are. For now, many workers seem to have adopted a policy of asking for forgiveness rather than permission.
Business of Fashion
19 hours ago
- Business
- Business of Fashion
How Swap Is Streamlining Brand Operations Through Unified Commerce
2025 is proving to be a year of reckoning for fashion e-commerce businesses. Geopolitical shifts and the consequent disruption to global trade policies mean there is a greater need for consolidated supply chains — and a more unified approach to commerce. Uncertainty around the Trump administration's tariffs has created turmoil for companies in the fashion industry. Smaller, independent brands with large portions of customers in the US and production overseas are especially at risk due to fluctuating policies. To address the challenges and overarching uncertainty facing small to medium-sized enterprises (SMEs) today, Swap Commerce — an e-commerce operating system (OS) that helps brands manage logistics and operations across borders — seeks to unlock a unified approach to business. A London-based startup founded in 2022 by Sam Atkinson and Zach Bailet, Swap Commerce's support encompasses shipping and returns to inventory, customs and tax compliance — all within a single platform. With pre-built integrations for Shopify, Klaviyo, UPS and FedEx, Swap Commerce enables users to streamline complex back-end tasks, including delivered duty paid (DDP) shipping, automated tax remittance, and express customs clearance. Its tools are designed to help brands quickly adapt their supply chains to tariff shifts and geopolitical disruptions. Swap Commerce partners with 500+ brands worldwide, with annual sales typically ranging from $20 million to $100 million. In the fashion and eyewear sectors, notable partners include Phillip Lim, Sandy Liang, Ed Hardy, Pangaia, The Frankie Shop and Odd Muse. The company is expanding into new areas such as beauty and home goods, collaborating with brands like Joseph Joseph, while venturing into consumer technology. Following a $40 million Series B funding round in early 2025, Swap Commerce aims for further growth in the US, EU, Australia and Canada. Indeed, Swap Commerce grew its revenue sevenfold between March 2024 and March 2025. With new AI-powered tools, including Swap Commerce Inventory — an intelligent forecasting and replenishment engine — Swap Commerce helps brands optimise stock levels and reduce overproduction. Meanwhile, Clear by Swap Global — a B2B2C solution focused on pricing transparency — provides customers with a clear breakdown of duties and taxes upfront, thereby reducing friction at checkout. Another timely offering is the US Domestic Tax Filing solution, which provides assistance in remaining compliant with tax laws in all 50 states. These services are designed to provide SMEs with the tools to navigate the current climate, from communicating price fluctuations with the end consumer to staying up-to-date with tariff shifts or upcoming sustainability regulations. Now, BoF sits down with Swap Commerce's co-founder and CEO Sam Atkinson to understand the value that the company's all-in-one ecosystem can offer fashion and luxury brands in a fragmented value chain and an increasingly complex geopolitical landscape. Sam Atkinson, co-founder and CEO of Swap. (Swap) What motivated the founding of Swap Commerce? Before founding Swap Commerce, I ran my own e-commerce business, and many of the features we built at Swap Commerce aim to solve the pain points I experienced when running that business. For instance, we would ship internationally to the UK, then distribute goods back out to other international markets — which, obviously, created all sorts of issues around tax and compliance. I then started a job at McKinsey, where I worked with a number of large retailers on setting up their operations. Swap Commerce also took inspiration from how big businesses approach operations, and looked at how that could be scaled down effectively for smaller businesses. Those were the two main inspirations for Swap Commerce and rendered exactly what we needed to do to support retailers. If you look at what Shopify has done for e-commerce, it has tried to unify many of the different tools that a brand might have used separately. What we have done, similar to Shopify, is to offer the same unification but for your back-office operations. This includes the parts that feel slightly less exciting, but are really fundamental to your business, whether that is tax and compliance, how you manage your inventory, how you manage your returns, or how you manage what stock should be in which location. What do you believe sets Swap Commerce apart from other tools available for SMEs? First, the user interface that we have built, compared to some of the more legacy providers, is really strong. We also provide connectivity across tools. For example, if you are using the software platform NetSuite for your accounting, we can integrate it seamlessly within Swap Commerce. Any tax calculation we perform for you at Swap Commerce will also be reflected in your NetSuite or other accounting softwares. That connectivity — especially as you become a larger brand generating upwards of 50 to hundreds of millions in revenue — becomes critical, as you are likely using several different systems to manage your operations. Our ability to quickly and seamlessly connect to those systems makes our customers' lives easier. We also offer a suite of different products, whereas many of our competitors only have one. We have a cross-border product where we are the main provider globally; we have a returns product and we have an inventory forecasting tool that we're just launching. You can use one product or multiple — but if you do use multiple, the idea is that they are value compounds. We also leverage data across our different products, so we are able to give you better insights on what you should be doing with your business. Whereas, if you use Global-e for international shipping and Loop for returns management, you'd have to do an integration between both platforms to make them harmonise. What trade and customs pain points do brands expanding internationally face, and how can Swap Commerce support them in this process? It depends on the brand. We recently experienced the rollout of tariffs in the US, and for brands manufacturing in China, that means any shipment that had previously been duty-free now faces a 50 to 60 percent tariff. Even understanding what your landed cost will be is a challenge now. What I mean by that is: what is the total cost to get the shipment to your customer? Being able to give a brand clarity on that, and what it means for their profitability, is an intrinsic part of our work. Internationally, there are all sorts of local tax rules that you need to comply with as well. [We offer] unification for your back-office operations [...] whether that is tax and compliance, how you manage your inventory, how you manage your returns, or stock allocation. For example, if you are a brand selling into New York, once you exceed a particular sales threshold, you are required to start collecting state tax. It is these kinds of complexities that, as a brand, you are not focused on. We try to take that headache away from you. We'll monitor when you cross that threshold, register you for state tax in New York and facilitate the payments on your behalf. We have also built a duty and tax calculation tool which allows you to estimate the cost of any shipment to any location, including duty and taxes. There are a number of different use-cases for it, whether you are a shipping postal carrier, or you want to communicate to customers how much duty and taxes they must pay. How does Clear by Swap help brands navigate tariff changes? Clear enables a brand that has goods made in China to ship to its customers in the United States in a more cost-effective way. It is mostly applicable to UK brands or international brands that also have a US entity. We can help the brand establish a US entity if they do not already have one, then facilitate an inter-company transfer — moving goods from the UK entity to the US entity. The US entity purchases the goods from the UK entity at fair market value. That's typically the manufacturer's cost price (what you pay in China), plus a reasonable markup — similar to what you might charge a wholesaler in the US. Tariffs will be charged on that lower price instead of the retail price — so it is a significant saving. If your transfer price for a product is $50 and the tariff is 50 percent, you pay $25. But if your retail price is $150, you'd be paying $75 in tariff. Clear has essentially allowed brands to continue trading while they decide what to do with their setups post-tariffs. How is Swap Commerce supporting fashion brands specifically? One of the biggest pain points for e-commerce and retail brands has been how to attract and retain customers in a competitive market — especially as privacy regulations make targeted marketing more difficult. There are numerous tools available to help with this now, but we are seeing customer retention become a priority for brands over customer acquisition. How do we help solve that challenge? We manage the returns process, and have other post-purchase tools that offer a seamless customer experience, such as a repair and recycle tool for returned inventory. Looking ahead, what do you believe fashion brands will need from the e-commerce space in the medium term? As AI becomes more widespread, we are thinking about how it can impact a brand's day-to-day operations. A lot of technology tends to reach e-commerce later than it does in enterprise software, where companies are often early adopters. So, we're proactively looking to that space for ideas and innovations we can bring into e-commerce sooner than they might arrive organically. We are exploring how you could automate the day-to-day of an e-commerce brand using AI or using AI agents. Whether it's the processing of your orders and returns, or the automation of the tax filing — and that's more than just filling out the tax form. You could build an agent that would log into the Florida State Tax Portal, submit the form on your behalf, and ensure that all of your filings are done on time, in an automated manner. Our goal is to bring this kind of automation to multiple areas of e-commerce — and that's where we see the most exciting opportunities ahead. This is a sponsored featured paid for by Swap Commerce as part of a BoF partnership.
Entrepreneur
a day ago
- Business
- Entrepreneur
How to Make Sure ChatGPT Recommends Your Products — Not Your Competitor's
AI is changing how people shop — if you're still relying on SEO, you're already behind. Optimize for AI to stay visible. Opinions expressed by Entrepreneur contributors are their own. A major shift is underway in the way consumers discover, research and purchase products online — and it's being driven by artificial intelligence. OpenAI is rolling out new features and exploring integrations with platforms like Shopify that could allow users to shop directly through ChatGPT. This means customers could search for and buy products from Shopify merchants without ever leaving a chat interface. For decades, online shopping began with a Google search. Consumers typed in keywords, skimmed links, compared reviews and then clicked "buy." That model is quickly being replaced by something faster, smarter and more personalized: AI-assisted shopping. According to Adobe Analytics, 39% of U.S. consumers say they've already used generative AI for shopping-related tasks. More than half (53%) plan to use it this year to research products, get gift ideas, compare pricing and discover unique brands. Instead of browsing dozens of web pages, AI assistants summarize product options instantly, personalize recommendations and even build shopping lists tailored to individual needs. Here are the latest developments you need to know: Related: The Future of SEO — 3 Trends Every CEO Should Know AI-powered shopping: what's already happening This shift isn't just theoretical — it's already taking shape: Even before fully integrating with Shopify, Open AI has improved ChatGPT's product search and memory, allowing customers to buy products surfaced by AI chat responses. Amazon recently launched a "Buy for Me" feature that allows AI agents to purchase products from other brand websites when they aren't available on Amazon. Perplexity introduced a Pro Shopping Assistant in 2024, designed to streamline decision-making by providing AI-curated product summaries This new generation of intelligent shopping tools is redefining what it means to be "discoverable." For e-commerce brands, that means adapting fast, or risk being left out of the conversation entirely. What does this mean for your business? To stay competitive in an AI-driven marketplace, brands must rethink how they present their products online. Here are five practical steps you can take today: Step 1: Shift from SEO to AEO Search engine optimization (SEO) dominated digital marketing for decades. Brands invested heavily to optimize their websites and content with keywords for search engines – a race to be listed at the top of Google's search results. That's how companies stood out among competitors, driving traffic and boosting sales. But searching for products on Google forces consumers to scroll through various websites and click a lot of links to read reviews, compare product features and evaluate pricing and shipping times. While convenient and fast compared to traditional, in-person shopping, AI now offers an even more efficient shortcut. AI chatbots can instantly search everywhere, scouring the Internet for websites and feedback, and then provide an easy-to-follow summary of findings. With customers increasingly using AI instead of Google to shop, SEO is becoming less relevant. In addition to SEO, what you now need is a way to make sure your products are included in ChatGPT's recommendations and responses. Answer engine optimization (AEO) is the new SEO. While this shift is just getting underway, tech and consumer behavior are moving fast. If you want to stay ahead of the competition, you need to start adapting your strategies now to optimize for AI. Step 2: Make sure AI can understand and recommend your products As platforms like Shopify become more integrated with AI systems, you want to make sure the AI chatbot suggests your products, not your competitor's. To be recommended, brands need to organize and present their data in a way that's accessible and readable by ChatGPT. And, as consumers engage in conversation with chatbots – by adding or taking away criteria, for example – updated responses will surface in real-time. Brands will need support designing their Shopify storefronts and listings in order to stay ahead of ChatGPT's nuanced recommendation engine. That means: Optimizing your Shopify product listings with clear, conversational copy Using standardized formats for pricing, availability and shipping Highlighting your most competitive features in plain language When consumers interact with AI assistants — adding preferences or asking follow-up questions — the AI dynamically updates recommendations. If your product data isn't accessible or detailed enough, your brand could be left out. My company, FORE Enterprise, is developing infrastructure to support both customers and brands through this AEO shift. By connecting your company's own data to ChatGPT, we help ensure the accuracy of the information shoppers receive about your brand. Related: Predictive AI Search Is Here — Is Your Brand Ready for It? Step 3: Differentiate or disappear AI assistants rely on data to make decisions, and that means only the best-positioned products will be recommended. To stand out, you need to clearly communicate: What makes your product different Why it's worth the price What value it offers over similar options Ask yourself: If a consumer were using a chatbot to shop, what would they want to know about your product? Price? Durability? Eco-friendly packaging? Award-winning design? Start by identifying your brand's unique value propositions, then ensure those qualities are clearly reflected in your listings and website content. Step 4: Write like a human, not a spec sheet AI tools like ChatGPT rely on natural language understanding, so your product pages need to speak the way humans do. Instead of jargon-heavy descriptions or overly technical language, focus on conversational, customer-focused storytelling: Answer common questions customers might ask Highlight use cases and real-life benefits Use bullet points, bold text and digestible formatting The more your content resembles how people actually talk and shop, the easier it is for AI to understand — and recommend — your products. Step 5: Start now — not later The AI shopping revolution is happening quickly. While the concept of AEO is still evolving, the companies that move first will have the biggest advantage. Right now, there's a narrow window to position your brand at the forefront of AI-driven discovery. This means: Auditing your product content and structure Rewriting listings for clarity and AI-readability Partnering with experts to connect your data to AI platforms Final thought: adapt early, win big This isn't just a new tech trend. It's a fundamental change in how people find, evaluate and purchase products online. Brands that succeed in the next era of e-commerce will be those that understand how AI thinks, speaks and recommends. If you want to ensure your products are seen — and bought — you need to act now. Let AI work for you, not against you. Ready to break through your revenue ceiling? Join us at Level Up, a conference for ambitious business leaders to unlock new growth opportunities.
