The AI trilemma: Speed, cost or performance?

Published: 29 April, 2025

Picture this: an AI-powered tool that gives you instant responses, hyper-personalized experiences and reduced operational costs. As you get ready to make this happen, reality hits; you can't have it all. If you prioritize developing and putting the AI tool on the market quickly, you'll sacrifice its performance. But prioritizing performance will risk delaying the launch and increasing costs. And if you're on a tight budget, well, that will affect the speed and performance. This is the AI trilemma – the inherent trade-off between speed, cost and performance.

Many businesses fail to understand and navigate this trade-off, stumbling to implement AI. The pressure to innovate rapidly, stick to a tight budget and achieve high-quality results creates a complex balancing act. Read on to learn more about the AI trilemma and how to navigate it, all to help ensure that your next AI project delivers real value.

Learn more: How your business can make sure AI adds real value

The AI trilemma – a balancing act

Before attempting to navigate the AI trilemma, understanding it is important. So, let's break it down:

Speed is about how fast development and deployment it. Prioritizing this allows for a short time-to-market and competitive advantage. However, it can lead to rushed development, sacrificing quality and long-term stability, which can require costly rework later on.

Cost generally includes any expenses related to infrastructure, talent and operations. While prioritizing cost-efficiency allows for an optimized budget, it can compromise performance and functionality. Cheaper resources might result in lower quality outputs and limit your AI solution's capabilities.

Performance is about the accuracy, reliability and robustness of your AI solution. Prioritizing this ensures high-quality outputs, but usually demands significant investments and extended deadlines. Generally, the higher the performance you want, the more resources and time are needed.

As you might have realized by now, speed, cost and performance are tightly interconnected. Decisions you make regarding one of these will inevitably affect the other two, and vice versa. Understanding their relationship is crucial and there's rarely a scenario where you can maximize all three elements simultaneously.

Navigating the AI trilemma

“So, what can I do to navigate this?” might be your next question. A successful AI implementation relies on a strategic approach and informed prioritizations based on your business objectives. This is how you should approach the AI trilemma:

1. Define your objectives

When starting a new project, the first thing you'd do is to reflect on and define the objective, right? You should be doing the same before embarking on your AI implementation journey. Ask yourself: What is the purpose of the AI initiative? What is the problem we're trying to solve? This will help you prioritize what adds the most value. The more specific you are, the better!

2. Do things step by step

Trying to build the perfect AI solution from the get-go is risky. By cramming as many features as possible into one solution, you might unknowingly – and unintentionally – overcomplicate your AI project. Instead, start small and then scale. This allows you to test the waters and gather insight, which will help you manage the trade-offs. For instance, you might realize that what you need to prioritize in the beginning will change later on.

3. Always prioritize data quality and governance

Regardless of whether you're prioritizing speed, cost or performance, high-quality data is an absolute must. Poor data quality will lead to poor quality insights. This is the one thing you should not compromise!

Consider the AI trilemma is crucial before venturing into AI

Understanding it is the first step, and while there's no universal solution, adopting a strategic approach is the next. By defining your business objectives, doing things step by step and prioritizing data quality, you'll effectively navigate the trade-offs and ensure that your AI initiative adds real value. How you decide to balance speed, cost and performance ultimately depends on your business objectives and circumstances.