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Artificial intelligence is a powerful tool… but only if you know how to use it effectively. This is when prompt engineering comes into play. Its impact is equal to the impact of AI, as learning it is the only way to unlock the full potential of genAI. In this article, we discuss the role of prompt engineering for finance in more detail. We invite you to read on.
Table of Contents
- Prompt Engineering in a Nutshell
- The Impact of Generative AI Prompt Engineering for Finance
- The Takeaway
Prompt Engineering in a Nutshell
Prompt engineering is a multi-step process of creating inputs for generative AI that will result in the best possible outcomes. It involves multiple techniques and goes beyond creating a single prompt. Its goal is to make the model more effective and easy to use for the end-user.
You’ll usually see prompt engineers working in tech companies designing AI-powered products for a plethora of clients. Here, this science is used mostly to teach a given model about the ins and outs of the business that will be using it and align its responses with the goals of a given business.
Moreover, prompt engineering is an ongoing process involving experimenting with multiple response variants. Therefore, it largely contributes to the optimization of the use of generative AI in modern businesses.
You can learn more about it in our article: What Is Prompt Engineering?
The Impact of Generative AI Prompt Engineering for Finance
Generative AI is a tool like any other—you need to know how to use it to reap all of its benefits. Even if you were to enter the best bolide, you would still be unlikely to win an F1 race; even if you had the best equipment and ingredients, you would still be unlikely to make the most delicious meal in the world—it all comes down to experience and skills. The same is true for artificial intelligence.
Learning prompt engineering is basically learning how to utilise generative artificial intelligence — how to become a pro racer or a master chef. That’s why it’s the key to modern banking. Let’s look at its impact in more detail.
Mastering the Use of AI
First of all, learning how to prompt will help your employees (prompt Engineers, Data Scientists, Natural Language Processing Engineers, Machine Learning Engineers) generate better responses. This leads to a major improvement in their service quality, efficiency, and personalisation. It also helps remove errors that could occur by relying on ineffective prompts.
Building Employee Satisfaction
Generating bad responses over and over again leads to frustration. For example, your employees that are end-users for AI Prompter might be fed up with unhelpful replies from the AI or even doubt its purpose. To solve this problem, you need to invest in teaching (and constantly expanding knowledge of) prompt engineering for the technical side of your team. After all, prompt engineering is a relatively new field of expertise. Plus, AI-based app developers need to gain related competencies quickly. At the same time, they need to keep managing new projects for their organisation. Thus, providing them with additional training will help them cope with all of this work.
Promoting Self Learning and Development
Prompt engineering isn’t a ready-to-use solution; it’s a set of methods and techniques that will help your employees resolve their problems regarding AI. Therefore, by coaching them on it, you set them on a path to self-development, learning about AI, and mastering its use. They will become more aware of the dangers of current genAI engines, experiment with their use, and maybe even find new ways to utilise artificial intelligence and share them with their team. Hence, prompt engineering is a way to boost engagement, promote ownership, and incentivise self-development.
Expand your knowledge on prompt engineering!
Download our ebook: The new reality of a Natural Language Processing Engineer
The Takeaway
Prompt engineering is key for finance, as it lets organisations master generative AI. Therefore, it is the basis for modern banking—you need to ensure that your team is skillful at it.
You might also read: How Can AI Improve Customer Service in Banking?
