The implementation of Artificial Intelligence (AI) in business will have a profound impact on the financial landscape of the future. Read on to find out more. 

Artificial Intelligence (AI) is being implemented in many different industries, including in the financial sector. While the mechanics behind developing and building AI and machine learning software might be complex to understand from a layman’s point of view, their impact doesn’t have to be.

To understand how the financial landscape is going to be affected in the years ahead, a study was conducted by the World Economic Forum in collaboration with the Cambridge Centre for Alternative Finance at the University of Cambridge Judge Business School, called “Transforming Paradigms A Global AI in Financial Services Survey”.

In this study, opinions about how AI is going to change the financial landscape were surveyed. To help us get more insight into this topic, this post will summarise some of the main findings as it relates to this topic. 


How is AI Changing The Financial Landscape? 

1. Generating More Valuable Insights from Data

As in most industries where it is being applied, AI is helping businesses and corporations in the financial sector to generate more valuable insights from data. 

Since data is being created on an exponential scale everyday, AI provides the tools with which to analyse data more efficiently than can be done manually. These automated processes therefore allow for more data to be analysed at a time, and for patterns and trends to be more easily recognised.

However, as has been demonstrated in some well publicised cases, the effectiveness of AI is related to the quality of the data itself. This means that while AI has the ability to analyse data more effectively, the financial data sets that are being examined also need to be subject to some kind of quality control (which can be a challenge, especially at enterprise scale).

2. A Reimagined Customer Experience

As we touched on in the point above, AI and machine learning have the power to more efficiently manage, process and analyse data. This means that it can assist tremendously when it comes to automating customer service processes, thereby creating a more enjoyable customer experience.

From simple chatbots to personalised recommendations based on user data, the use of AI presents many opportunities for a reimagined customer experience. 

As many financial transactions are now carried out digitally, it makes sense that this technology can be applied in the financial services sector to help facilitate business growth, for example, with the more streamlined management of client queries and information, in both the B2B and B2B sector. 

3. Personalised Investments

With a reimagined customer experience now available with the implementation of AI and machine learning, efforts can now be directed more towards targeting previously neglected markets.

For example, in an article that discusses the findings of the above mentioned study, it is mentioned that the +60 age group category has not been as targeted as much as other age groups when it comes to developing personalised investment portfolios

This is despite the fact that this age group holds a large percentage of global wealth, and provides many different opportunities when it comes to financial product innovation. 

4. Driving Business Model Innovation

With the ability to more efficiently manage and analyse data, and the capacity to create new and exciting products for varied target markets, AI and machine learning provide many opportunities for new business model innovation.

While many businesses in the financial sector are using AI technologies to enhance their existing product offerings, there are many companies that are innovating new business models using up and coming technologies.

In fact, it can be said that these businesses might gain a competitive advantage in the years ahead, as opposed to those who are holding back from investing in developing AI and machine learning functionality within their businesses. 

5. Potential Barriers to Entry

While many companies are investing in AI, some of the survey respondents from the above mentioned study stated that the possibility of large tech companies dominating the market in the years ahead is a real concern.

This is because tech giants like Google, for example, have the funding to invest in research and development, which some smaller companies may not, which leads to potential barriers to entry for some businesses, in a “winner takes all scenario”.

However, while many companies might not have the capital to invest in intensive AI research and development, there are still many opportunities to implement some level of AI with all of the various technological developments taking place in the financial landscape at the moment, so as not to be left behind. 


In the article above, we have provided a general overview of some of the points raised in a study conducted by the World Economic Forum in collaboration with the Cambridge Centre for Alternative Finance at the University of Cambridge Judge Business School, called “Transforming Paradigms A Global AI in Financial Services Survey”.

While this topic is complex, and more detailed discussion and study is required to really understand how the financial landscape will be affected in the years ahead, this post has provided some key takeaways about the future of AI in the financial landscape. 

These include the fact that AI will assist businesses in the financial industry to generate more valuable insights from data, create a reimagined customer experience, help to personalise investments, drive business model innovation and potentially create some barriers to entry for certain businesses.