A decision to embrace artificial intelligence tends to lead to excessive excitement among decision-makers. The leadership team meets in the boardroom and starts throwing ideas around. Some of those ideas are great, while others, not so much. Regardless, it is easy to get swept up in the excitement of it all. Yet embracing AI should not be any different from more traditional decisions.
Quickly making the leap from an exciting idea to a massive coding project is a recipe for disaster. How many tech initiatives have stumbled because engineers built something the market didn’t actually want or need? It happens far too often. In the real world of successful AI digital product development, success isn’t defined by financial investment. It’s defined by validation.
Idea Validation With Prototyping
Before committing the time and financial resources to a complete software build, smart organizations experiment and test. They do so by prototyping – a lot like auto companies do. Automakers introduce concept cars just to see how the market responds. Prototyping in software development works pretty much the same way.
A prototype is a simplified but functional version of whatever idea an organization wants to build on. It’s created in just a few weeks. The goal is not perfection; it is to safely test an idea and its assumptions to see how the market responds. Prototyping is also an opportunity to better understand how AI will handle real-world information for the benefit of its users.
If prototyping validates a great idea, decision-makers find it easier to write a massive check. But if validation proves an idea isn’t worth the investment, engineers can move on to something else. It is really no more complicated than that.
Why Prototyping Is Non-Negotiable
Prototyping is absolutely essential to AI digital product development. According to GojiLabs, stepping back to build and test a simple AI prototype yields valuable results for both corporate leadership and stakeholders.
For starters, prototyping dramatically lowers financial risk. It costs an organization a lot less to change the direction of an AI product during early stages than to fix a fully coded nightmare. In essence, prototyping acts as a type of insurance. But that’s not all. Here are three more reasons prototyping is non-negotiable:
- Technical feasibility – Just because an idea looks good on paper doesn’t mean a company can actually support it. Prototyping allows for a modeling phase that clearly demonstrates whether the idea is technically feasible.
- Stakeholder buy-in – Moving from concept to full deployment always requires stakeholder buy-in. Prototyping represents an opportunity to gain that buy-in before massive amounts are spent.
- Honest feedback – It is nearly impossible to predict how users will interact with an AI product. Prototyping gives them an opportunity to try things and offer honest feedback.
Embarking on an AI digital product development project without prototyping in the mix spells trouble. A company can spend massive amounts of money and invest considerable time in creating a product that eventually falls flat. Companies do it all the time, and it costs them dearly.
Business Outcome Should Always Be the Focus
When GojiLabs is brought in to handle AI digital product development, they are quick to remind customers that business outcome should always be the focus. AI-enhanced software should never be developed for its novelty. If it does not generate a positive business outcome, there is no justification for investing in it.
Prototyping is the precursor to successful business outcomes. Before a great idea is fully developed, it should be tested with a simplified but functional prototype. Prototyping answers a lot of questions. It drives development and leads to success.
