Why AI Journey Mapping Is Critical For Digital Transformation

Actually, forget “digital transformation.” Artificial intelligence has become such an integral part of digital transformation today that it’s almost synonymous with DX itself. AI allows us to extrapolate value from our data. It allows us to gain operational efficiencies. It even allows us to replace entire job functions! But to do so, it needs to be implemented well. That’s why AI journey mapping is so important.

Just like digital transformation calls for a clear and cohesive strategy, so does the implementation of AI throughout the enterprise. While it’s easy to add AI in drips and drabs across single departments, the real value comes when it’s implemented company-wide. That means weaving AI into the fabric of the entire company, rather than adopting it here and there as the need arises. But what does AI journey mapping even look like? And how do you know if your map is heading you in the right direction? Follow these steps for AI journey mapping success.

Step One: You Are Here.

The first step of any journey begins with understanding where you are and where you want to go. This involves being completely honest about how your vision for the company aligns with the reality of what your company is currently experiencing in terms of your budget, the skills of your workforce, the time commitment you’re able to make, etc. In the “You Are Here” discussion, take a good hard look at things like:

  • Data preparation: How well are we currently collecting data? Is it clean? Is it organized? Is it available to different departments that may need it? Are we capable of processing it with the infrastructure we’re currently using?
  • Infrastructure readiness: Just 15% of companies have the right infrastructure in place to support AI. What does that mean? It means you can’t use legacy infrastructure to run AI. You need technology that is fast enough to process mounds of data in real-time to get meaningful results. Take stock of what tech you’re using, and what you’ll need to purchase or service out to get the results you’re looking for.
  • Organizational planning and change management.Does your company have the mindset to succeed with AI right now? Are leaders ready to adopt data-driven decision-making? Are your teams open to adopting new technology? If not, plot out what you need to do to start changing the culture and mindset! You’ll never move forward without clear goals in mind, and that means addressing the current state of mind your employees and leaders are operating within.
  • Data science and expertise. Yes, there are lots of AI services you can outsource. But who on your team will be tasked with speaking the language—setting the goals—looking for patterns and relationships in the data you gather? Does your team have the expertise to develop models and test them already? Be smart about what you need to outsource and what you can mine in-house.

This article originally appeared on forbes.com To read the full article, click here.

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