Today, few technologies receive as much hype as artificial intelligence. Regardless of the form it takes, AI has the ability to dramatically transform everything from mundane tasks all the way up to significant business decision-making.
Already, AI is having a major impact. Over the last four years, AI adoption by major organizations has increased by 270%, and it has increased by 37% just in the past 12 months. And this all may be the tip of the iceberg too, with enterprise AI usage likely to grow even further in the next few years.
AI is disrupting every industry, especially financial services. In 2019, banks and other financial services are expected to spend around $5.6 billion on AI-related
solutions and services.
While AI holds a lot of promise, its embrace doesn’t come without a fair share of challenges. As a new report from Forrester Research — titled Q&A: The Top Five Questions Digital Financial Services Leaders Should Ask About AI In 2019 — highlights, financial services organizations need to be extremely thoughtful in their AI adoption plans, otherwise their investments will not yield tangible results.
In particular, the report recommends that companies keep these key points in mind:
AI is a Strategy, Not Just a Tactic
AI is far more than a tool. While AI, machine learning and other algorithmic technologies can be deployed as one-off solutions, doing so limits their reach and effectiveness. AI works best when it is embraced at every level of the organization and serves as a key strategic business driver.
Look Beyond the Hype
AI has gotten a lot of hype over the past few years, and it’s easy to see its mentions as merely marketing folly — just another buzzword. As Forrester has noted, many firms have fallen prey to the hype without really understanding how it could work and what potential drawbacks looked like, and as a result have seen disappointing results so far.
“AI washing is like greenwashing,” Michele Goetz, Principal Analyst at Forrester, wrote in a 2018 blog post. “Big data firms, for example, may claim that their tech is AI. But just because it has an algorithm doesn’t mean it’s AI. This phenomenon is everywhere.”
But financial services firms cannot accept defeat so quickly. It’s critical to understand actual use cases now and in the immediate future. Look beyond the hype and embrace the use cases that are ready to make a material impact now.
A common example used by many credit card companies and banks is the application of AI to spot fraudulent purchases. AI is good at understanding patterns and spotting anomalies, enabling financial services firms to more quickly spot potential instances of fraud and stop them early on.
Chatbots are another good example of AI in action today. As machines become smarter at understanding human language and responding to set needs, AI-powered chatbots can be deployed to address any customer concern that may arise in the moment, all without needing to rely on fallible humans for this effort. Plus, chatbots are often faster and more adept than their more manual counterparts in replying and directing to customers in any language they choose.
“Look at how you are using technology today during critical interactions with customers
— business moments — and consider how the value of those moments could be increased,” says Whit Andrews, distinguished vice president analyst at Gartner. “Then apply AI to those points for additional business value.”
How Do Use Cases Impact the Business?
There are dozens of potential applications of AI that financial services firms can adopt today. And many more will arise in the coming months and years. But not all that glitters is gold.
Not every potential AI application should be embraced. In the early goings, it’s critical to devote limited AI budgets only towards applications that can improve the business and make it stronger.
“Although the potential for success is enormous, delivering business impact from AI initiatives takes much longer than anticipated,” says Chirag Dekate, senior director analyst at Gartner. “IT leaders should plan early and use agile techniques to increase relevance and success rates.”
Teamwork Makes the Dream Work: Find Ideal AI Partners
As the Forrester report notes, many financial services organizations often lack the internal expertise, technical resources and IT infrastructure needed to make the most of AI across the business. For example, there are already hundreds of thousands of AI-related job openings
that are likely to go unfilled due to a lack of individuals with the required skill sets available.
In many instances, it doesn’t make sense for financial services firms to go it alone. With quality partners and solutions in place, organizations are able to benefit from AI without having to make significant internal capital and operations investments.