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.
The Latest
App sprawl has been a concern for technologists for some time, but it has never presented such a challenge as now. As organizations move to implement generative AI into their applications, it's only going to become more complex ... Observability is a necessary component for understanding the vast amounts of complex data within AI-infused applications, and it must be the centerpiece of an app- and data-centric strategy to truly manage app sprawl ...
Fundamentally, investments in digital transformation — often an amorphous budget category for enterprises — have not yielded their anticipated productivity and value ... In the wake of the tsunami of money thrown at digital transformation, most businesses don't actually know what technology they've acquired, or the extent of it, and how it's being used, which is directly tied to how people do their jobs. Now, AI transformation represents the biggest change management challenge organizations will face in the next one to two years ...
As businesses focus more and more on uncovering new ways to unlock the value of their data, generative AI (GenAI) is presenting some new opportunities to do so, particularly when it comes to data management and how organizations collect, process, analyze, and derive insights from their assets. In the near future, I expect to see six key ways in which GenAI will reshape our current data management landscape ...
The rise of AI is ushering in a new disrupt-or-die era. "Data-ready enterprises that connect and unify broad structured and unstructured data sets into an intelligent data infrastructure are best positioned to win in the age of AI ...
A majority (61%) of organizations are forced to evolve or rethink their data and analytics (D&A) operating model because of the impact of disruptive artificial intelligence (AI) technologies, according to a new Gartner survey ...
The power of AI, and the increasing importance of GenAI are changing the way people work, teams collaborate, and processes operate ... Gartner identified the top data and analytics (D&A) trends for 2024 that are driving the emergence of a wide range of challenges, including organizational and human issues ...
IT and the business are disconnected. Ask the business what IT does and you might hear "they implement infrastructure, write software, and migrate things to cloud," and for some that might be the extent of their knowledge of IT. Similarly, IT might know that the business "markets and sells and develops product," but they may not know what those functions entail beyond the unit they serve the most ...
Cloud spending continues to soar. Globally, cloud users spent a mind-boggling $563.6 billion last year on public cloud services, and there's no sign of a slowdown ... CloudZero's State of Cloud Cost Report 2024 found that organizations are still struggling to gain control over their cloud costs and that a lack of visibility is having a significant impact. Among the key findings of the report ...
The use of hybrid multicloud models is forecasted to double over the next one to three years as IT decision makers are facing new pressures to modernize IT infrastructures because of drivers like AI, security, and sustainability, according to the Enterprise Cloud Index (ECI) report from Nutanix ...
Over the last 20 years Digital Employee Experience has become a necessity for companies committed to digital transformation and improving IT experiences. In fact, by 2025, more than 50% of IT organizations will use digital employee experience to prioritize and measure digital initiative success ...
