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A version of this article was originally published in Finance Middle East.

The modern banking system has endured more than its share of change since its emergence during the Renaissance in Europe. The world map has been re-drawn many times, society has transformed through agricultural, industrial, and technological revolutions — and the banking system has evolved with it to become an indispensable pillar of modern society.

Now the emergence of artificial intelligence (AI) signals another major change. It is vital that banks and other organizations operating in the financial services sector move quickly to start developing and executing coherent plans to utilize AI technologies. I say ‘technologies’ because AI has many forms including generative AI, machine learning, natural language processing, robotic process automation, predictive analysis, and sentiment analysis, to mention just a few. This can be daunting for banks, as it brings a level of complexity and confusion. Many organizations will struggle to define what AI is, making it difficult to begin developing a strategy for its best implementation and use.

Preparing banks for AI-powered change

In this context, financial services organizations need to take stock and assess who they are as an organization, what they stand for, and where their value proposition lies. They need to recognize that AI is transformative, but also that no matter how many types of AI they want to implement, it is very different from implementing a single technology solution such as a new CRM platform. AI is transformational on another scale, and therefore organizations must take a more comprehensive approach and transform around it, which means considering its impact across the board, including the implications for strategy, marketing, operations, customer service, HR, and all other aspects of the business.

While banks should certainly not delay plans to embrace AI, it is important that they approach it with an amount of caution so that they get it right from the outset, given the many aspects to consider. This means up-skilling and gaining a sound understanding of what AI, in all its forms, can enable a company to achieve. It also means assessing the potential pitfalls, such as AI algorithms introducing bias and risk, because like everything, AI has the potential to be misused and to introduce errors if not used properly.

The role of regulators as AI develops

The situation is made more complex by the fact that regulators globally are still playing catch-up with AI, and the rapid pace of AI development and the highly regulated nature of the financial services sector makes the situation even more tricky for governments. As and when regulations are implemented, it is likely that they will need to be modified frequently. It is therefore vital that banks educate themselves about trends in global and local regulation so that they are either complying with new regulations, or better positioned to comply with upcoming rules.

Even banks that are not yet actively deploying AI solutions must be mindful of AI regulation as they may be inadvertently using AI systems that are part of third-party solutions, such as CRM software or cybersecurity solutions, and thus they need to be aware of this and of any risks and issues around regulatory compliance.

In terms of developing an AI strategy, banks should first define what they stand for, and decide on their objectives and limitations. They should simultaneously consider the broader implications and ethical ramifications of what they are looking to do — whether that is deploying a chatbot to handle customer calls or launching a personalization engine to recommend products and services to customers. Banks should be conscious that AI can cause real harm to customers, and so any AI implementation must be carefully managed and monitored from its inception. Business leaders must recognize that AI requires a big upscaling exercise in terms of knowledge and management to ensure it is properly leveraged and able to achieve its goals.

Despite the game-changing nature of AI, it is important to note that organizations do not necessarily need to leap into AI with a large, expensive technology overhaul. They can start by working with what they already have — for example, they can leverage their current data to gain insights and make incremental, tangible improvements.

AI is a journey, not an end, and any implementations should be considered part of a continuous transformation. As part of this journey, it is imperative to continually measure the impact of AI initiatives and share successes across the organization, because nothing unites people more than victories, and employees need to see the benefits of AI to realize that it is critical to their organization’s success.

AI is coming, whether companies like it or not. The sense of urgency may sound alarmist, but when you see a 20-meter wave coming, you cannot swim against it, you must ride the wave to a successful outcome. To do so, all players must take stock of where they are at and where they want to go, and plan to deploy AI as part of a comprehensive transformation journey, tailored for the specific needs of their organization, their customers, and key stakeholders.

Read the original piece, here.