With financial technology spreading across more consumer use cases every day, the digital transformation revolution is finally making its way into back offices — bringing new efficiencies, heightened levels of transparency and, ultimately, decision-making capabilities at the highest level of organizations.
The impact of AI implementation is profound, transforming business operations and decision-making at the highest levels by enhancing operational efficiency, business intelligence and data analysis. AI systems play a pivotal role in this transformation, introducing new efficiencies and automating tasks that once required human intervention. Various AI technologies are involved in streamlining financial operations, including machine learning, natural language processing and AI-powered virtual assistants.
Here to help unpack this emerging trend and look into the not-too-distant future of business is Siqi Chen, founder and CEO of Runway, a business planning platform that automates the integration of financial data into intuitive workflows that can model, plan and align business for everyone on the team.
Chen joins the Converge podcast for a thought-provoking discussion ranging from his “personal conspiracy theory” that keeps the business world trapped in clunky, spreadsheet-driven enterprise software models to the “philosophical science fiction” of our inevitable adoption of decision-making AI.
AI implementation for CEOs
Even though many businesses appear to be slow adopters of enterprise-level fintech or cross-border payment solutions, Chen asserts that the consumer experience with finance has grown by leaps and bounds lately, adding pressure and expectations for companies to adopt similar processes in-house.
For finance teams, this could mean holistic business intelligence systems that inform real-world decision-making across various business functions, optimizing everything from marketing to customer interactions and CRM applications.
“You won’t need an analyst,” Chen says. “As a CFO, you can just have an AI analyst to update your model for you and run scenarios for you. So that’s going to be incredibly fun and beneficial for everyone. And that’s what the next, say, two to five years looks like.”
A new era of data analysis
AI is also set to transform business processes through advanced data analysis, enhancing efficiency in production, marketing, distribution and even automating market segmentation and campaign management.
Soon after that, Chen projects that systems will become more advanced and integrate deeper into our institutional structures.
“Eventually, the capabilities of AI won’t just increase leverage,” Chen says. “And at some point, these tools are going to get so good that it’s able to do things on its own and ask questions on its own better than any human can. And so it could within 5 to 10 years run a company better than a human CEO could or understand finances better than a human CFO could.”
Algorithms in charge of business processes?
Putting algorithms in charge of everything can paint a dystopian picture, even to the most optimistic proponents like Chen. Though humans may never knowingly innovate themselves into irrelevance, Chen is certain that technology will advance far enough to make that a realistic option.
“We’re going to put these things out in the world in the form of agents and even embody robots that are walking around. It’s going to learn by interacting with the world and create more data the same way humans do,” Chen says.
“So this idea that it’s never going to get to a point where it’s going to be more creative, more artistic than a human, I think is really naïve — it will. It’s going to get way smarter than any human and also way more creative and way more artistic and way more entertaining. It’ll get there.”
An optimistic view of future AI technologies
The so-called “rise of the machines” isn’t necessarily bad news for business leaders.
Chen notes that it might only seem destructive because we’re looking at it through the prism of today. He focuses on the potential human benefits of an ecosystem where automated creations are virtually indistinguishable from human-made ones.
“The world that we live in is just so unnaturally different when it happens, because if that (the loss of jobs to AI) is true, that’s true of every job in the world from an engineer to an artist, to a movie director,” Chen says.
“The world that we live in is just so unimaginably different. It’s hard to even speculate what that’s going to look like, but it is coming.”
Beyond chatbots: How LLMs empower finance teams
At Runway, Chen integrates AI deeply into operations compared to other business-to-business (B2B) platforms.
He points out one common issue with AI products: due to sales incentives, the people who purchase them at organizations are often not the same people who have to use them on a daily basis.
Large language models (LLM) are great for interfacing with customers. Chen adds that they can also add significant value to a company’s internal operations, including enhancing customer relationship management (CRM) systems. AI, particularly LLMs, can automate and personalize customer interactions, providing a more tailored service and improving the overall customer experience.
“If you’re looking at a formula, there should just be an English explanation of a formula right there. If you’re looking at a model, there should be [clear] explanation of what the model does,” Chen says. Furthermore, computer vision can play a crucial role in analyzing financial documents or data visualization, thereby enhancing the capabilities of finance teams by extracting valuable insights from visual data.
Scaling with artificial intelligence
Those features can apply to other aspects of the business, and as a company scales, its teams can benefit from the transparency. Natural language processing extends beyond customer interfacing, aiding in the analysis of financial reports and facilitating smoother internal communications.
“Anyone can propose changes to the model, and there’s approval flow. AI could explain what changed [and] what this is proposing for you. We have snapshots. AI should explain how the snapshot from six months ago is different from the snapshot that you have today,” Chen says. “That’s how you make it more understandable.”
The new generation of founders and finance leaders
As companies evolve and new business leaders come into their own, Chen sees them demanding software that not only solves problems but also brings clarity and understanding to their business through data-driven decision-making.
This approach leverages AI technologies, including deep learning, to analyze complex business data — providing insights that drive strategic decisions and enhance supply chain management.
This could tie employees’ contributions to the company mission in a transparent manner that encourages a deeper comprehension of operations, drives productivity, and highlights the collaboration between AI and human intelligence. Integrating human knowledge in training AI algorithms complements the human workforce, leading to more efficient business operations and decision-making processes.
Balancing transparency and control
“If you look at how transparency has changed in organizations over the past few decades, it’s only ever going one direction,” Chen says. “Transparency is increasing, and finance is not the only area where this happens.”
But could that be too much transparency?
“There is a false trade-off between control and transparency,” Chen says. “The intuitive belief would be that if you are more transparent, that means you have less control over the information … actually, the reverse is true. More control enables more sharing.”
Want more insights on the topics shaping the future of cross-border payments? Tune in to Converge, with new episodes every Wednesday.
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*The information shared on this blog is for informational purposes only and should not be considered financial advice. Please note that the opinions expressed on Converge are solely the opinions of the host and the guests, not Convera’s.
