What Does It Mean to Build a Company with AI in Mind?
February 22, 2024

James Field

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AI is no longer a niche buzzword. Today, every industry uses AI, from healthcare and finance to retail and transportation — everything. Some companies are just starting to dip their toes into developing AI capabilities, while (few) others can claim they have built a truly AI-first product. Regardless of where a company is on the AI journey, leaders must understand what it means to build every aspect of their product with AI in mind.

First: What Does Building with AI in Mind Entail?

Building AI capabilities is not just about implementing machine learning algorithms or adding a ChatGPT extension. It's about turning information and data into actionable insights and, eventually, automated actions. By prioritizing end users' needs, companies can create innovative products that move the tech world further.

However, in order to do so, companies must understand the data at their fingertips. Low-quality and biased data can lead to flawed AI models, so starting with high-quality input is essential. Even small tasks, like writing instruction manuals or FAQs for customers, should be done with AI in mind, so it is easily readable for bots in the future. This critical mindset sets companies up for success and helps AI become a trusted advisor that enables users to make better decisions and automate actions.

Tactical Tips on How to Do It

Education comes first for both employees and customers. All employees should understand how AI is being used, or how they are utilizing it, to improve products and services and the impact it can have on their jobs. Companies are also obligated, or should be, to inform customers about what AI is and how it will be used to benefit them.

Secondly, companies should have a governance policy for adopting, deploying, and using AI, clearly explaining the privacy and data sources used for AI solutions. This will help ensure that the company uses AI ethically, which is key to building customer trust.

Lastly, companies should use customer data wisely. For example, companies can watch how customers are interacting with a particular tool and track where their pain points are. Product teams make use of AI and this data to look for ways to automate things customers didn't even know they needed.

Always, Always Keep the Customer in Mind

Understanding the end user's needs is the most important aspect of building an AI product. Make sure every decision, big or small, is focused on creating a better product for customers. Ensure reasoning is provided so they understand how AI is making the decisions and it is — never "closed box." Much like being asked to show your work in an exam — it demonstrates your thought process and understanding of the customer's needs.

AI will continue to grow over the next days, months and decades, and sooner than we realize, it will be built into every product we use. To be successful, product leaders must prioritize transparency and education when building these products. Companies should not be afraid to experiment with AI but should also be mindful of its potential risks. By keeping goals and the end users in mind, companies can stay ahead of the curve and provide customers with innovative and helpful products.

James Field is Sr. Director of Product Strategy and Operations at LogicMonitor
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