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How One Product Leader is Scaling Global Commerce through AI Integration and International Expansion

We recently had the privilege of sitting down with Vinod Sivagnanam, the global commerce expert driving AI innovation at Adobe Commerce and formerly Amazon, for an in-depth interview about scaling commerce through AI. Sivagnanam has mastered the art of scaling e-commerce across borders while keeping customer experience at the core. Read this insightful interview to unpack what it really takes to scale commerce in the AI era.

Vinod Sivagnanam is a seasoned expert in global commerce, with years of product management experience driving growth, leadership, and innovation in digital commerce and payments. He has expanded e-commerce platforms to new countries and been at the helm of driving AI innovation across major global tech companies.

Sivagnanam started his tech journey as a technology consultant at EY and Deloitte. In these positions, he developed a strong foundation in digital strategy and transformation before making his way up the business ladder.

At Amazon, Sivagnanam led international retail launches in Belgium and South Africa. He also spearheaded their global payments expansion, which included launching cross-border solutions and partnering with financial institutions to improve access for international sellers and customers.

Sivagnanam is currently responsible for reshaping Adobe Commerce’s storefront platform by integrating AI features to provide personalized customer experiences. He has always focused on big-picture goals, which shows tenacity in his work leading cross-functional and global teams.

Through both innovative product strategies and data-driven insights, Sivagnanam has set industry benchmarks for global commerce expansion. His lightweight market expansion strategy has significantly reduced operational costs while his work on AI-powered personalization and visual search technologies has enhanced customer experiences across multiple markets and regulatory environments.

1. What has your journey been like transitioning from technology consulting to leading product strategy at major tech companies?

Vinod Sivagnanam: As a consultant I got to focus on the truly critical business problems and think in conventional and unconventional ways about how technology deployed to solve them. However, I always felt distant from the end-customer. I felt like I was solving problems for a client, but I didn’t really need to have a deep understanding of their customers.

As a Product Manager, I was as close as I could be to the customer. While this was exciting, I had to ramp-up quickly on effective techniques to understand customer behavior such as experimentation and A/B testing, and building effective customer surveys.

Another key difference is ownership. As a consultant, I was never responsible for the long-term success/failure of my solution as long as we met the goals laid out in the statement of work. As a product leader, I own the ultimate success and failure of my product. As a result, I had to learn how to measure success by identifying the right key performance indicators (KPIs) and always had to take a long-term view about the impact of my strategies.

Finally, as a consultant, I was expected to be industry agnostic. I could be engaged to solve problems for clients across all industries. In a product role, a deep industry context is table stakes. Today, because I build e-commerce SaaS products, I am constantly investing time to get a good understanding about the e-commerce industry, the SaaS industry, and the industries my customers operate in.

2. Visual search technology is transforming how customers discover products online. How are retailers overcoming the technical implementation challenges of deploying AI-powered visual search at scale?

Vinod Sivagnanam: While visual search significantly enhances product discovery, it is functionally complex to implement, computationally intensive, and presents technological challenges when integrating with existing infrastructure.

Retailers are taking two approaches to implementing visual search – building in-house or using third-party providers. Developing visual search capabilities in-house requires a tech team of data scientists and machine learning engineers (among other capabilities such as platform and front-end developers). Alternatively, third-party search providers such as Algolia and Elastic have introduced visual search with developer tools to integrate this feature to their existing solutions. This outsources the technological burden of implementing and scaling this feature.

This is the age-old “build vs. buy” predicament, and leaders have to think critically about the value of developing this skill in-house vs. using a provider to fill the gap.

3. You’ve analyzed how visual search creates competitive advantages, particularly in furniture and home goods. How should retailers evaluate whether visual commerce technologies align with their specific industry and customer base?

Vinod Sivagnanam: My recommendation is to take a customer preference driven approach. My suggestions below are for three types of retailers – B2C retailers in categories with high customer preference sensitivity and B2C retailers with low customer sensitivity, and B2B retailers.

In my experience, retailers selling categories with high customer sensitivity to product visual attributes (such as furniture, home goods and apparel) should consider building this feature in-house. To these retailers’ customers, visual search acts as a personalization tool. These retailers could also integrate visual search to existing personalization features.

Retailers who operate in categories with lower customer sensitivity to product visual attributes (such as hardware tools, office supplies) can consider adding this feature via a third-party search provider. To these retailers’ customers, visual search’s main benefit is to increase search accuracy. These customers use other product attributes such as price and specifications to drive their purchase decisions.

Finally, B2B retailers need to think critically whether visual search as a product discovery tool will really add value to their customers. Most B2B customers know exactly what product they want and create purchase orders based on existing quotes. However, visual search might increase the purchase efficiency for B2B customers in other ways. For example, customers can take a picture of a previous packing slip and have it automatically create a new purchase order.

4. In your experience launching retail sites in Belgium and South Africa, what are the biggest technical and regulatory challenges companies face when expanding to new international markets?

Vinod Sivagnanam:

Trade and payment compliance hurdles: each jurisdiction has its own set of rules about how commerce is conducted. The hotspots for these local legal constraints are usually around trade and payments. The impact of these regulations manifest in the form of what products can be sold in these jurisdictions and how funds can be collected from customers and disbursed to sellers. Both of these have a significant impact on the tech build (more on that below).

Consumer privacy and data protection regulatory challenges: another set of regulations that presented challenges were what customer data can be collected, how this data can be used and the rules around how this data can be transferred and stored. Many features aiding customers in the shopping flow rely on customer behavioral data, and need to be altered to comply with these regulations.

Commerce infrastructure scaling challenges: while our primary aim is to launch the right set of features and product catalog for our customers, a large part of what we can ultimately launch is influenced by these regulations.

As a result, the core commerce infrastructure cannot be scaled to operate in these new countries – customizations and incremental technical build impacting the catalog, CX features, data pipelines and payment infrastructure is necessary to launch with compliant systems.

These builds are usually not straightforward and often come in conflict with providing the best possible purchasing experience for customers and selling experience for merchants.

5. You’ve analyzed various AI technologies from visual search to personalization for reducing customer decision-making time. What’s your framework for determining which AI capabilities will have the greatest impact on conversion rates?

Vinod Sivagnanam:

To prioritize AI investments, I bucket technologies by their impact on the customer journey:

  • Purchasing efficiency (e.g., agentic purchasing)
  • Search & discovery (e.g., recommendations, visual search)
  • Pricing & promotions (e.g., dynamic pricing, discounts)

I am intentionally avoiding AI tools which boost operating efficiency (ex: automated customer service and supply chain optimization) since they are more focused on optimizing cost versus growth.

I start by understanding the shopping behavior of the customer. I pay particular attention to how their purchase journey originates, how intentional they are when they land on the online store and how informed they are about the product catalog.

This deep understanding allows me to prioritize the AI features. If a material number of customers land on the online store from other platforms (search engines, social platforms) or emulate browsing behavior after landing, it tells me that there are opportunities to influence purchase decisions through recommendations and other discovery tools. This is often true for B2C retailers operating in categories where personal taste heavily influences purchase decisions.

If customers are highly informed about their products or if most purchases are repetitive in nature, then I would prioritize tools for purchasing efficiency. This is especially true for B2B customers.

Finally, depending on how price sensitive customers are, which is usually influenced by market conditions and the competitive environment, I would prioritize pricing and promotions features to optimize for customers’ willingness to pay.

While this is a rough framework, in reality, this exercise is extremely analytical with strong data to bolster recommendations.

6. How do you approach balancing rapid international expansion with maintaining quality customer experience and regulatory compliance across different markets?

Vinod Sivagnanam: When it comes to International Expansion, sequence matters. In my experience, expanding to geographies where customer behavior is similar to your current customer base has shown good success (ex: if you operate in the UAE, it might make sense to expand to Saudi Arabia first over Singapore or India). Usually, this means expanding to countries which are physically closer to where you operate.

While this deviates from the traditional market-entry framework (go for the higher market size and growth with lower competition), it gives retailers a competitive advantage and allows them to compound on the success and brand loyalty they enjoy in incumbent markets. Also, it potentially reduces the Cross-border compliance complexities retailers may face (regulations are usually similar for closely located countries). With this approach, retailers can scale customer experience (CX) with minimal changes and other core infrastructure systems in a cost efficient way. Retailers can also hit the ground running by leveraging cross-border fulfillment systems due to proximity.

However, retailers inevitably encounter geographies with regulatory requirements which restrict their ability to scale the existing CX. At this point, retailers must make a decision whether to invest in re-envisioning the CX and other impacted systems. Internal expansion is an expensive endeavor with an uncertain payback period and path to profitability, and sometimes the right answer is not to expand (at this point in time).

7. What role does data architecture play in enabling successful cross-border payment solutions, and how do you ensure data integrity across multiple regulatory environments?

Vinod Sivagnanam: Data architecture plays an important role in enabling cross-border payment solutions. Retailers rely on payment processors (sometimes multiple processors in key markets for resiliency) to accept customer payments and disburse funds to international sellers. Sometimes specialized regulatory partners are involved too to satisfy the compliance requirements. Data must flow seamlessly between the various internal systems and these partners, and a robust architecture is required to handle this complex data flow.

Retailers must build data systems that prioritize security – payments data is very sensitive and needs to be encrypted and tokenized. Security vulnerabilities in payment data is a fast way to lose customer trust. These systems must be scalable and resilient to ensure that payment data is complete and available in a timely manner. These systems must also provide intelligent fraud monitoring, troubleshooting and error handling so issues can be identified and rectified quickly. Finally, these systems must support reporting and auditing to ensure transactions are searchable and stored per regulatory data storage requirements.

8. Leading international expansion projects requires coordinating teams across multiple time zones and cultures. What strategies have you found most effective for managing cross-functional global teams?

Vinod Sivagnanam: The following strategies have served me well:

  • Manage your project diligently: build a detailed project plan with milestones, tentative dates, workstream owners and dependencies. Extensively socialize your plan and gain buy-in from key members and stakeholders. Maintain collaboration tools to ensure visibility. Always err on the side of over-communication.
  • Build mechanisms to identify and resolve challenges and blockers: weekly status and progress reviews provides a forum for team members to raise blockers in a timely manner. These mechanisms help to overcome obstacles quickly and keep the work-streams on track. Also, it helps to keep executive sponsors informed and raise risks proactively.
  • Develop a shared operational vocabulary: it helps if all team members communicate and operate in a similar fashion. In my experience, it is best to follow the organization’s principles and values. This helps break any cultural barriers.
  • Be flexible with your work hours: when working with global teams, traditional work hours might not work. What has worked for me is to be flexible about my work hours instead of traditional timings. Also, rotating late-day / early-morning meetings across the teams allows to distribute the inconvenience equitably.
9. How do you ensure that AI-driven product features remain customer-centric rather than technology-driven when working with engineering and data science teams?

Vinod Sivagnanam: To ensure that the product features remain customer-centric, it is essential to have a strong understanding of customer behavior and a clear vision for the end-state. Also, be very specific about the user behaviors you want to influence and the metrics you will monitor to measure success.

Once you are clear with your vision, it is imperative to communicate this vision to all partner teams such as engineering, data science and product design. Be sure to seek their feedback (this helps identify improvements and challenges early on) and gain alignment and buy-in.

Finally, be sure to be very engaged throughout the development process – maintain regular check-ins and demos to ensure that what’s being built aligns with the original vision. Avoid taking a hands-off approach as this often leads to misalignment and poor outcomes.

10. Looking ahead, how do you see AI and machine learning—from visual commerce to cross-border payments—reshaping global e-commerce over the next 3-5 years?

Vinod Sivagnanam: Visual search combined with contextual search will redefine product discovery by enabling shoppers to find relevant items using images enriched with intent-aware understanding. This powerful combination allows e-commerce platforms to deliver results that are not only visually similar but also aligned with the user’s purpose, preferences, and situational context.

Commerce will become hyper-personalized, with homepages dynamically tailored by location and customer preferences, weather, inventory, and fulfillment options (think personalized landing pages by ZIP codes). This level of personalization will turn every digital storefront into a locally relevant experience, boosting engagement and conversion.

Cross-border payments will become increasingly seamless, removing long-standing barriers to global commerce. AI-driven payment orchestration, real-time FX conversion, and localized checkout experiences will allow businesses to sell and settle across markets with the ease of domestic transactions. As payment complexity fades into the background, more merchants will be able to scale internationally without friction.

11. For executives considering international expansion or AI integration in their commerce platforms, what key priorities should they focus on to ensure successful implementation?

Vinod Sivagnanam: For executives exploring international expansion or AI integration in their commerce platforms, success hinges on prioritizing customer experience, regulatory compliance, and a resilient and scalable technology infrastructure.

Start by identifying the features that meaningfully enhance the customer purchasing journey and tailor them to the specific needs of each market. Equally important is understanding the regulatory and compliance landscape, which usually vary significantly across regions. On the technical front, assess how these initiatives impact your architecture, data strategy, and compute infrastructure, ensuring your systems can scale accordingly.

Ultimately, every strategic investment should be evaluated not just for operational feasibility, but for its ability to deliver a differentiated, frictionless customer experience across geographies.

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