Catching the Wave of AI Innovation to Build AI Products

Today. businesses are faced with a choice: delay adoption and risk falling behind competition or embrace the change with an uncertain outcome.

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With the excitement around AI, many are trying to figure out how to catch the wave to leverage AI in their business. However, building something new, particularly on a very new technology platform that is evolving day to day can feel daunting. Businesses are faced with a choice: delay adoption and risk falling behind competition or embrace the change with an uncertain outcome.

AI Essential #1: Build with the Customer In Mind

If your organization isn’t already customer-centric, there has never been a more crucial time to shift your focus. 

Building a product, particularly an AI product, might initially seem like a 'science experiment' or showcasing something cool, but that misses the point. The goal is to address a significant and tangible problem—a problem that genuinely needs solving. 

The process begins by deeply engaging with your ideal customers to thoroughly understand their challenges through open-ended questions. Instead of directly asking what problem they want solved, it's more effective to grasp their business and core workflows. 

A customer advisory board is one way to glean essential customer feedback and insights. Hosting a forum or event with key clients offers a vital opportunity for you to gain deeper insights into your customers’ daily operations and decision-making processes. 

During these sessions, the product team leads a workshop focused on understanding the customer’s day to day interaction with the product, delving into their everyday tasks and the ways in which they utilize data in making daily decisions.

These events, coupled with numerous micro-interactions that happen day-to-day provide insights to help you build your understanding of customers' needs and distinguish between what is essential vs what is nice to have.

AI Essential #2: Leverage Your Technical Talent

Another critical aspect of developing an AI product is understanding the current capabilities of large language models (LLM), while at the same time anticipating the technology’s potential future capabilities.

This is where you need to engage closely with your best technical talent – not only to keep tabs on latest platform releases from the LLM platforms, but also to begin building internal knowledge of how to best leverage this new technology.

In order to determine the optimal architecture for the platform, our technical team created various sandbox environments using different language models. With the ability to quickly change parameters, we were able to test out the capabilities across the team. This rigorous process of testing and learning allowed us to gauge the practical limits and pitfalls of the technology to inform how and what customer problems to solve first. 

Launching a successful technology product is fundamentally about aligning customer needs with technological capabilities to create a viable solution. Success is impossible without this union. 

AI Essential #3: Sell Your Vision

You might be eager to catch the AI wave but suppose others in your organization are less bullish. With the constant demands from customers and internal stakeholders, it's natural for some to question why AI should take precedence. 

One key to winning over skeptics is to pitch investment in AI as a strategy that can solve multiple key business objectives, while simultaneously driving innovation. Painting that picture on the value of the investment is essential to gaining support. 

A decision to invest in AI innovation should begin with a vision for the future of your product, supported by a strategic plan that considers both near- and long-term impacts.

It can be difficult to strike the right balance between investing in an exploratory project and supporting more immediate but less impactful needs and issues.

Managing priorities and expectations sometimes comes down to keeping others informed. Involving key stakeholders from various parts of the organization beyond the technical team in co-creation and internal testing helps to foster greater understanding of AI, contributing to superior design outcomes for an initial product and building excitement across the whole organization. 

Customer Feedback Loop

Of course, true customer needs become even more apparent when you launch a product and capture market usage and data. 

Push through discomfort to launch something sooner rather than achieving a perceived idea of perfection. Start with your most trusted loyal customers that you know will partner with you to make the product better. 

Implemented a tight feedback loop, involving in-depth analytics and regular check-ins to understand how your key customers are seeking to utilize the product and the challenges they encounter. This continuous stream of feedback is crucial in making iterative improvements that directly address user needs. 

Through a meticulous process of monitoring, iterating and gathering user feedback post release, you can refine your product to not only deliver substantial value for customers but also to generate genuine enthusiasm both internally and externally.  Powered with early customer feedback you can be assured you are delivering a solution that will meet and exceed customer expectations. 

The Beginning of the Future

When you are ready to launch to your entire customer base, continue to embrace the iterative process that got you to this point. Measure adoption and feedback relentlessly to drive what should come next. Embrace the exciting possibilities AI holds for the future of your business and your industry