Introducing our “Three E’s of AI Success” series about AI in action at BetaNXT. We’re sharing how we embed AI into our core systems, drive efficiency and put user experience first—helping clients and teams achieve more.
So much of the conversation about AI in the investment and wealth management industry today focuses on the “what”: what models, what data, what prompts. At BetaNXT, these aspects are undoubtedly important, but all of our work is also guided by a bigger-picture “how”—how we can most effectively leverage AI in our innovation pipeline to accelerate success for our clients as well as for our own team.
Our approach to AI innovation is shaped by a few key principles that we call the three E’s of AI success:
Embedded
Efficient
Experience-First
In this first post of our three E’s mini-series, we’ll share a preview of how we define and deploy each of these principles. Be sure to check back in over the next few weeks as we dive into each “E” in more detail and share some examples of AI in action at BetaNXT.
Embedded: Anticipating Client Needs at the Source
We often see firms piloting AI in a siloed way, trying to find value by adding it on top of their core operations. But to realize AI’s true potential, it’s essential to integrate it directly and seamlessly into the very systems and processes that power your business day-to-day.
As a longtime data and technology solutions partner to many leading investment and wealth firms, we have always focused on how we can do more to help our clients succeed.
This means we often predict what they need most—sometimes before they even realize it. This anticipation of client needs translates to our embedding solutions at the source, whether that be in our underlying data foundation, our operational support technology, or in our front-end products and services.
Our emphasis on good data governance, multi-layered security and responsible guardrails ensures that AI has an optimal environment to operate. The clean, accurate, real-time data foundation of our DataXChange platform has a flywheel effect on AI-driven innovation, empowering us and our clients and partners to develop transformative solutions more easily.
Efficient: Operating at Peak Productivity
Typically, efficiency is thought of in quantitative terms, as a matter of time savings and speed. We think of efficiency in qualitative terms as well—not just doing things faster, but also smarter and better, generating greater impact per unit of effort.
Efficient AI delivers tangible value and insights while minimizing complexity and unnecessary effort.
Efficiency has always been a core objective for the solutions we deliver. With the integration of AI, today this means not just automating routine and manual tasks, but also detecting anomalies, surfacing new insights and helping users make better decisions, faster. We’re focused on enabling internal and external users operate at peak productivity.
In practical terms, we’re deploying AI throughout our organization—from complex code refactoring to automated data aggregation to predictive analytics—and seeing tremendous benefits. The reclaimed time savings and the new intelligence are helping our team and our clients’ teams work more efficiently and more effectively, too.
Experience-First: Designing for People, Not Processes
In the rush to innovate, some firms seem to be barreling forward with an AI-first mentality: how can we “AI-ify” our processes? This can lead to highly automated and seemingly accurate outcomes, but in an industry like ours where human judgment and decision-making are so critical, we believe that people, not processes, should be at the center of new product development.
That’s why our last E for AI success is Experience-First—we prioritize the experience of the people using our solutions, whether they are technologists, operations leaders, asset managers, advisors or investors.
AI should enhance human judgment, not overwhelm it, and provide the helping hand that users are glad to have.
To ensure a positive experience, we design our AI-powered solutions to be intuitive, insightful and transparent. User-friendly interfaces, natural language interaction and hyper-personalization guide all our AI innovation. Plus, we have an intimate understanding of our clients’ day-to-day workflows and long-term goals, which directly shapes our product development.
The Bottom Line
AI success isn’t about technology alone. It’s about how that technology is embedded into workflows, how efficiently it operates, and how experience-first it feels to the people who use it. At BetaNXT, these three E’s guide our AI development, and are integral to how we enable success for our clients and their clients.
Stay tuned for the next article in this series, where we dive a little deeper on Embedded.
