AI is having a huge impact on a diversity of businesses. To gain an insight, Digital Journal spoke with Experian’s Chief Scientist Shanji Xiong.
Xiong is the Chief Scientist and co-founder of the Experian Innovation Lab. With more than 30 years of experience, he has applied AI and machine learning to develop solutions in fraud detection, marketing, risk management, and identity resolution.
Xiong dives deep into solving complex business challenges with agentic and generative AI.
Digital Journal: What’s the biggest way AI is making a positive impact on businesses right now?
Shanji Xiong: The rise of no- and low-code AI has been a game-changer. Tools like our generative AI‑powered Experian Assistant use natural-language processing to make analytics accessible to more people, not just data scientists.
Experian Assistant is like having an Experian expert with you 24/7. It’s powered by decades of expertise in analytics, decisioning, and fraud prevention. Our clients across sectors—finance, healthcare, marketing, automotive—use it to develop models faster, gain insights more easily, and ultimately launch new products and services more efficiently.
Developers are using AI copilots to code faster and test more effectively, and business users can now explore data, simulate strategies, and gain insights in ways that were previously too complex or time-consuming.
We’ve seen this firsthand. At Experian, engineers use AI to speed up code development dramatically. In one case, a data scientist with no prior experience in OCR (Optical Character Recognition) created a prototype in under an hour. That’s the kind of agility that AI now enables.
DJ: Based on your experience, what are five ways AI can solve complex business problems?
Xiong: Here are a few strategies to make the most out of AI to solve business challenges:
- Empowering Consumer Engagement and Education: AI virtual assistants can provide real-time support, from locking a credit file to explaining loan options. This builds consumer trust and improves satisfaction.
- Scaling Content and Knowledge: AI can generate marketing copy, training materials, and customer support scripts—turning static documents into living resources.
- Accelerating Development: Tools like GitHub Copilot have revolutionized how our engineers build and test code, improving productivity across teams.
- Enhancing Market Research: AI can analyze vast amounts of unstructured data—news, social media, earnings reports—to extract meaningful insights.
- Improving Risk and Fraud Management: We’ve patented generative AI methods for analyzing credit card transaction patterns to detect fraud. These models are now being used in production by major financial institutions.
DJ: How can smaller companies begin integrating AI, even with limited budgets?
Xiong: Start with business problem you wanted to tackle. You don’t need to train your own AI from scratch—platforms like ChatGPT and Claude are incredibly capable out of the box.
Focus on real pain points, like automating internal reporting or using AI chatbots for customer support. Then run small pilots with tools like Zapier, Notion AI, or Slack GPT. These are low-cost and low-risk, but can yield high returns.
Also, no-code platforms like Microsoft Power Platform and Airtable let teams build AI‑powered apps without a dedicated engineering staff. Starting small and thinking long-term builds the internal know-how to scale up effectively.
DJ: What advice do you have for business leaders who are still hesitant about adopting AI?
Xiong: I would encourage leaders to see AI as an enabler—just like the PC, mobile phones, or the internet were in their time. It’s no longer a niche technology. It’s an operational advantage.
At Experian, we’ve embraced a culture of grassroots innovation. We train and empower our teams to explore AI responsibly and use it where it can drive measurable outcomes. Business leaders should do the same—identify where AI can reduce friction or accelerate decisions, and start there.
DJ: Looking ahead 5–10 years, how do you see AI shaping the business landscape?
Xiong: One of the most exciting trends is agentic AI—systems that can reason, make decisions, and execute tasks independently within defined objectives. Imagine asking a platform to plan your entire overseas trip—flight, hotel, side trips—and having it execute instantly.
These systems will be “smarter” than humans in specific tasks, but they need guardrails. We must keep humans in the loop and define the bounds of what AI is allowed to decide. At Experian, we’re already working on frameworks for AI governance, transparency, and fairness.
Another priority is fraud prevention. Generative AI is being weaponized by fraudsters, who can now scale attacks faster than ever. That’s why we’re developing multi-layered detection systems—from behavioral biometrics to device fingerprinting—to help our clients stay ahead.
DJ: What does this mean for the broader relationship between businesses, customers, and communities?
Xiong: When used responsibly, AI can create more inclusive, personalized, and efficient experiences. Our platforms are used by over 1,500 clients worldwide. In North America alone, more than 8,000 users from 80 companies access over 12 petabytes of data each week for analytics.
We’ve seen this with companies like Lendr, a fintech serving small businesses. By using Experian Assistant, they improved agility, reduced losses, and doubled their business in just one year. That’s the kind of impact we want to see—AI that lifts businesses and the communities they serve.
