While use cases for generative AI in ecommerce are still emerging, here are five examples of how the technology is being applied today.

How Leaders Are Navigating AI in Ecommerce

If it feels like resources are running thin, you’re not alone: 65% of commerce professionals say they’re being asked to do more with less. The good news? Necessity breeds innovation. The rise of generative AI — and its uses in ecommerce — is already proving to be a valuable tool for productivity, efficiency, and revenue growth. In fact, 84% of organizations that have fully implemented AI in ecommerce say it’s had a moderate to major improvement in these areas.

Here’s everything you need to know about the unique benefits of AI in commerce, and how leaders are evaluating, investing in, and implementing it.

What you'll learn:

Benefits of AI in ecommerce

  1. Personalize your product recommendations
  2. Upgrade chatbots to AI-powered copilots
  3. Make every ecommerce engagement more productive
  4. Enhance post-purchase operations
  5. Improve ecommerce fraud prevention

Hurdles to implementing AI in commerce and how to navigate them

Benefits of adopting AI in ecommerce

Predictive AI has been improving ecommerce for yearsopens in a new window, from product recommendations to intelligent search results. But now, generative AI has the potential to change things further by revolutionizing customer experiences. Not to mention the ways it’s also increasing productivity, driving conversions, and fostering customer loyalty. A whopping 84% of ecommerce professionals believe AI gives companies a competitive advantage. Here’s how generative AI is helping them get ahead.

Hyper-personalize experiences at scale. When technology advances, 73% of customers expect better personalization. As AI extends business capabilities to tailor promotions, marketing messages, pricing, and more, shoppers will increasingly expect more customized experiences — wherever and however they shop. AI is already a key differentiator for businesses: More than a third of organizations (37%) credit AI for major improvements to personalization.

Automate tasks for maximum profitability. Growing revenue is always a top priority for businesses. One way to boost your bottom line? Automating tedious, manual tasks to improve productivity within your business. Thanks to machine learning and large-scale analysis of data powered by AI, commerce leaders can do this fast. They already see big gains using automation for self-serve order tracking, inventory, and returns management. By automating these parts of the ecommerce journey, your teams have more time to focus on strategic initiatives that move the business — and your revenue — forward.

Increase employee satisfaction and productivity. Customers aren’t the only ones who reap the benefits of AI in commerce. There are also advantages for employees. In fact, most businesses implementing AI report moderate to major improvements in employee productivity and satisfaction (84% and 82%, respectively). Developing a deep working knowledge of AI tools gives employees valuable career experience with a new technology. It can also offload many job functions that once felt tedious and monotonous, opening up new career trajectories and reskilling opportunities.

While use cases for generative AI in ecommerce are still emerging, here are five examples of how the technology is being applied today. Here’s everything you need to know about the unique benefits of AI in commerce, and how leaders are evaluating, investing in, and implementing it.

1. Personalize your product recommendations — even more

What is the most common use case for generative AI in ecommerce? Writing product descriptions. This is especially beneficial for businesses with large catalogs or technical, complex products. Although AI-powered product recommendations have been part of the online shopping experience for a long time, generative AI adds even more nuance and makes the entire process feel more bespoke. Generative AI allows better targeting and more refined personalization, helping you create relevant experiences faster and with more context. AI even allows you to create dynamic product descriptions tailored to each customer’s unique preferences and pain points.

The best AI platforms offer highly relevant personalization at the individual level without having to create a separate model for each customer. Even better? By incorporating user feedback, AI-based recommendations and personalization become smarter over time, leading to increased conversions and higher customer satisfaction.

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2. Upgrade chatbots to AI-powered copilots

In brick-and-mortar stores, sales and service agents are your biggest asset. They’re able to pick up on cues from customers as they shop and suggest appropriate products. Thanks to generative AI, this can happen online, too. Chatbots have been a part of online shopping for years, but they never had the kind of conversational power that could really enhance the customer experience in an effective way. Those days are over. Now, digital concierges can process natural language and image-based prompts, generate tailored answers, and engage in data-driven interactions. This enhances multiple aspects of the customer journey.

Product discovery: AI-powered concierges are particularly helpful when it comes to product search discovery. Most businesses (82%) using AI for commerce report at least moderate levels of improvement to product discovery. Consider a shopper looking to recreate one of their favorite celebrity’s recent outfits. Instead of aimlessly browsing through product listing pages, they can simply upload a photo of the famed fashionista and ask AI to recommend similar products. Bespoke experiences like this can also open new doors to customer loyalty and retention.

Customer service: Chatbots have always been able to handle the most basic customer inquiries, like “Where’s my order?” or “What’s your return policy?” But as AI advances, digital copilots can handle increasingly complex interactions. For example, a copilot trained on your product details can answer specific questions about an item’s specifications and unique attributes. They can also suggest related and secondary items during conversations with shoppers, like batteries, chargers, and other products that will enhance the post-purchase user experience.

Shopping just got a lot easier — and much more entertaining.

3. Make every ecommerce engagement more productive

Whether you’re a merchandiser, marketer, designer, or developer, generative AI can help you save time. In fact, commerce professionals using AI estimate it saves them an average of 6.4 hours per week. Businesses can automate routine tasks and increase sales with GPT-powered product descriptions, smart promotions, and more. Time-intensive tasks that once required manual configuration, like creating new promotions, can be automated at scale. And generative coding can help teams innovate faster.

Now, tools like generative page designers allow users of all skill levels to design webpages in seconds with simple, conversational building capabilities. AI can also uncover insights and make recommendations to help teams reach strategic goals. Want to clear out dead stock and make way for new merchandise? Improve your abandoned cart strategy? Generative AI can suggest promotions, price points, and marketing messages to help you achieve your goal. Need to boost average order value? AI insights can recommend proven strategies that can increase add-to-carts and improve revenue.

4. Enhance post-purchase operations

Expedited shipping, self-service order tracking, and easy returns have become table stakes in ecommerce technology. Now, generative AI will bring a new wave of optimization to inventory and order management.

For example, inventory managers can train AI on returns reports and customer reviews to fine-tune product descriptions and decrease return rates. Route managers can use AI to map out more sustainable delivery routes. And operations teams can have AI analyze shipping and fulfillment data to determine more efficient and cost-effective ways to source and ship items. This is especially useful considering that shipping costs, sustainability concerns, and inefficient order routing are top business concerns.

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5. Improve ecommerce fraud prevention

Fraud detectionopens in a new window is a critical part of ecommerce, but scammer tactics are always evolving and increasing in sophistication. In fact, 5% of its annual revenueopens in a new window to fraud each year.

AI’s predictive capabilities can learn scamming behavioropens in a new window and become smarter than the bad actors. The data points gained in this process can help payment solutions teams improve their fraud detection and target malicious activity without impeding legitimate purchases.

Hurdles to implementing AI in commerce — and how to navigate them

For all the benefits of AI, there are certain roadblocks that keep businesses from realizing its full potential.

Your AI is only as good as the quality of your data. A majority (70%) of commerce leaders say that poor data integration and harmonization is at least a moderate pain point on the road to AI implementation. To reap the benefits of AI in commerce, make sure all your company’s data is in one consistent format. This is known as “data harmonization”. Once your data is harmonized, it can be used to fine-tune an existing large language model (LLM) — an AI algorithm that uses deep-learning techniques and large datasets to understand, generate, and predict new content — to enable generative intelligence.

The best AI platforms will let you deploy your business’s transactional, product, order, fulfillment, and other commerce data — along with your customer relationship management software (CRM) and any third-party data — to get a 360-degree view of your customer. And they’ll do it while ensuring strict data security and privacy controls. That data will then provide opportunities for automation and growth, personalization, and actionable insights.

Maintaining customer trust is critical. Only 17% of customers fully trust companies to use their data responsibly, and a mere 13% fully trust companies to use AI ethically. This means organizations must be transparent about data collection and how they use it in business operations. To do that successfully, companies will need to develop ethical standards around their use of AI.

You’ll need to answer tough questions like: How do you ensure sensitive data is anonymized? How will you monitor accuracy and audit for bias, toxicity, or hallucinations? These should all be considerations as you choose AI partners and develop your code of conduct and governance principles.