Having too many options is the biggest challenge to bringing artificial intelligence into a business for the first time. The market is flooded with all sorts of new technologies and ideas. Everybody is launching something newer and smarter. Unfortunately, there is a temptation to get lost in all the hype; to develop an AI tool for its own sake.
Getting lost in the hype is how budgets get blown. It is how engineers end up developing technology that no one wants or needs. In order to succeed, organizations need to step back and ask two fundamental questions:
- How and where can AI actually help our business?
- What can we build first, to lay the foundation for long-term success?
The experts at GojiLabs believe the best way to answer these two questions is to embrace AI strategy & opportunity mapping. But to do so, decision-makers need to understand what it is.
It Doesn’t Have to Be Complicated
AI Strategy & Opportunity Mapping does not have to be complicated. There is nothing mystical or ethereal about it. Rather, it’s a collaborative and short-term planning process designed to clear up technical confusion. The process should only take a few weeks, during which business leaders work with product experts to evaluate how the organization operates, where the bottlenecks are, and how AI can be utilized to solve problems.
The most important thing to note is this: the goal of AI Strategy & Opportunity Mapping is not to look at AI in a general sense. It is to focus on what AI should be able to do for specific business needs. The process should turn abstract technical concepts into a clear, step-by-step business plan that fully directs how AI application development occurs.
A Three-Step Process
GojiLabs is a leading AI application development provider. They say that successful mapping relies on a three-stage process as follows:
1. Identify High-Impact Opportunities
The first step is to identify high-impact opportunities by evaluating day-to-day operations. For example, what types of repetitive tasks are employees spending excessive amounts of time on? Where are customers experiencing friction?
By speaking to employees and analyzing workflows, engineers can pinpoint the most relevant opportunities for AI to drive measurable business value. They might choose to cut costs in one area while improving customer response times in another.
2. Validate the Possibilities
The team will probably come up with a ton of great ideas during the ideation stage. But not every idea is actually feasible. GojiLabs says it is important to validate all the possibilities from technical, practical, and financial perspectives. Only validated ideas should be considered moving forward.
3. Build a Roadmap
The third and final step is to take the list of validated ideas and prioritize them based on two factors: business value and ease of implementation. This allows the team to build a prioritized roadmap that plots out how AI application development will proceed.
Turning Ambiguity Into Action
The ultimate goal of opportunity mapping is to take all the guesswork out of the equation. Mapping opportunities alongside technical AI strategies bridges the gap between high-level business goals and engineering capabilities. A strong bridge empowers the software development team to give its best efforts to AI app development.
Instead of going to developers with vague requests to build an AI tool, decision-makers should invest time and effort in AI Strategy & Opportunity Mapping. The results of doing so are usually measurable. With strong mapping data and a prioritized roadmap, the development team should be able to deliver something that actually makes the organization better.