Sandro Lonardi, CMO at SOAX, on the Future of AI and Business Strategy

Businesses are actively exploring the future of AI and how these innovations can enhance their operations, improve customer experiences, and optimize workflows. Two AI models—DeepSeek and OpenAI—are at the forefront of this revolution. While OpenAI has already secured a dominant position in the market, DeepSeek is carving out its niche with specialized capabilities.

To better understand the impact of these AI models on businesses, we spoke with Sandro Lonardi, Chief Marketing Officer at SOAX, a leading provider of intelligent data collection solutions. SOAX offers tools like ethical proxy servers and Scraper APIs. It has incorporated AI into its services to stay ahead in an increasingly competitive landscape. With over 1,000 enterprise clients, SOAX is no stranger to using advanced technologies to help companies collect public web data for various applications, from market research to price monitoring.

In this exclusive interview, Sandro shares his insights on the evolving AI landscape, comparing DeepSeek and OpenAI and discussing how these models will shape business strategy in the coming years.

Q: Sandro, as someone working closely with AI-driven technology, how do you see AI models like DeepSeek and OpenAI shaping the future of business and technology over the next few years?

Lonardi: AI’s evolution is creating a fundamental shift in business operations, especially regarding enhancing efficiency and scalability. At SOAX, AI makes significant strides in three key areas. In how we process and extract data. We’ve moved from offering just proxy services to providing full Data-as-a-Service. AI is really helping to make data extraction smarter and more efficient.

AI is playing a big role in optimizing infrastructure. We’re working on launching a distributed cloud solution in 2025 that will support hybrid computing needs. It is in growing demand as AI workloads reshape infrastructure. By 2028, the cloud computing market is projected to hit $1.27 trillion, driven largely by AI applications.

Lastly, AI is dramatically enhancing customer experiences. As SOAX expands its enterprise client base, we’re seeing AI-powered interfaces become standard rather than a luxury. It’s clear that the expectations for AI in customer-facing applications will only increase.

Q: It’s fascinating how AI is evolving in your business. If we were to talk performance and scalability, what do you think—DeepSeek or OpenAI—is better suited for large-scale business use cases?

 Lonardi: Regarding performance, OpenAI has a more robust track record, especially in multi-modal processing, which aligns with our need for flexible applications across different domains. OpenAI’s ability to handle different tasks simultaneously gives us the required versatility.

On the other hand, DeepSeek excels in code generation and technical reasoning, which has proven incredibly valuable in our R&D processes. We’ve used DeepSeek’s capabilities to streamline development cycles, making our internal processes more efficient.

When it comes to scalability, OpenAI really stands out. Their infrastructure is built to handle enterprise-level implementations. As we’re working with larger public companies, OpenAI’s infrastructure is already mature and tested. While DeepSeek is progressing, it’s not quite there yet for scaling up for big enterprises.

Practical implementation is another area where OpenAI takes the lead. The ecosystem surrounding OpenAI is more developed, with comprehensive documentation and plenty of implementation examples. This has made it much easier for us to integrate OpenAI into our workflows.

While DeepSeek is impressive in its specialized offerings, it often requires more custom development. Depending on a project’s specific needs, this can be both a challenge and an opportunity.

Q: You mentioned the need for flexibility, especially in enterprise settings. Which of these two models—DeepSeek or OpenAI—is better positioned to lead the AI industry in the next five years?

Lonardi: OpenAI has certainly established a significant lead, particularly regarding enterprise adoption and gaining traction among developers. It’s ahead in general capabilities, which makes it better positioned to dominate in the short term. However, I think the market will evolve in a way that won’t be a simple one-size-fits-all scenario. We’ll likely see the AI industry segment rather than consolidate.

The key factors for leadership will include:

• How well AI can be customized for specific industry needs.
• The ability to navigate complex global regulations.
• Cost of ownership—including API usage and the expenses around integration and ongoing maintenance.
• Seamless integration with existing business workflows.

For us at SOAX, the focus has always been on how practical and cost-effective AI solutions are. From our AI Scraper project, we learned that while advanced technology is exciting, it’s the ease of implementation and scalability that really matter.

In the end, the company that can make these solutions both affordable and operationally viable for businesses will lead.

Q: Regarding the competitive landscape, OpenAI has already forged major partnerships, like the one with Meta. Do you believe DeepSeek will follow suit with strategic collaborations, or will it try to maintain more of an independent approach?

 Lonardi: Strategic partnerships have become a critical component of success in the AI space. At SOAX, collaborating with other tech players has greatly enhanced our development of Scraper APIs. I expect DeepSeek will do the same to strengthen its market position.

I believe partnerships for DeepSeek will likely focus on:

• Gaining access to specialized data for training their models.
• Optimizing infrastructure to support more complex AI applications.
• Focusing on industry-specific implementations to tailor their AI tools to specific sectors.
• Gaining access to new regional markets may be critical for growth.

As much as there is value in having proprietary technology, the growing demands for infrastructure and data make it increasingly difficult for any company to go it alone.

Even if DeepSeek has unique offerings, partnerships will be crucial for scaling up effectively.

Q: As businesses expand globally and AI is deployed across borders, which AI provider—DeepSeek or OpenAI—do you think is better equipped to handle the challenges of international expansion and complex regulatory environments?

Lonardi: This is a major challenge, especially given the constantly evolving regulatory landscape. OpenAI has more experience with Western regulatory frameworks, which gives it an edge in terms of navigating privacy laws and data governance, especially in the US and Europe. However, both DeepSeek and OpenAI will face significant challenges when it comes to managing cross-border data governance.

At SOAX, we’re considering relocating our headquarters from the UK to the US to better align with market opportunities and regulatory frameworks. Similarly, AI providers must adjust their structures to comply with data residency rules, privacy regulations, and industry-specific compliance demands in different regions.

The company that builds flexible deployment options and keeps its solutions adaptable to these regulatory shifts will have the upper hand. It’s all about staying ahead of the compliance curve while maintaining performance.

Q: To wrap up, could you share any specific examples of how DeepSeek or OpenAI have had a transformative impact on SOAX or the industry in general?

Lonardi: Certainly. We’ve seen OpenAI provide direct value to our operations in several areas:

• Scraper API development: Using AI, we’ve automated the identification of patterns in websites and the creation of parsing rules, drastically accelerating our ability to support new target domains.
• Operational efficiency: Our cost reduction initiative in 2024, which cut expenses by over 20%, was supported by AI tools that helped optimize resource allocation while maintaining service quality.
• R&D: Our AI Scraper project faced high operational costs, but OpenAI helped us analyze the root problems and repurpose key technologies into our more successful APIs.

These examples show that AI isn’t just about innovation for its own sake; it’s about finding practical solutions to real business problems, and OpenAI has helped us do that.

Q: Anything else you’d like to add about the future of AI?

Lonardi: The key takeaway is that the AI landscape is rapidly evolving toward specialization. At SOAX, we’ve learned that success isn’t about jumping on every shiny new tech trend but finding the right application that solves specific business problems. This philosophy has guided us through transitioning from a proxy provider to Data-as-a-Service and now to Intelligence-as-a-Service.

The most successful organizations will not deploy the most advanced AI models—they will strategically integrate those models into their business processes and align their tech adoption with clear business goals.

Explore more of the AI in the industry series.