Digital transformation

Why AI Journey Mapping Is Critical For Digital Transformation

Nastel® Technologies
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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 To read the full article, click here.

Nastel Technologies uses machine learning to detect anomalies, behavior and sentiment, accelerate decisions, satisfy customers, innovate continuously.  To answer business-centric questions and provide actionable guidance for decision-makers, Nastel’s AutoPilot® for Analytics fuses:

  • Advanced predictive anomaly detection, Bayesian Classification and other machine learning algorithms
  • Raw information handling and analytics speed
  • End-to-end business transaction tracking that spans technologies, tiers, and organizations
  • Intuitive, easy-to-use data visualizations and dashboards

If you would like to learn more, click here.

Nastel Technologies, a global leader in integration infrastructure (i2) and transaction management for mission-critical applications, helps companies achieve flawless delivery of digital services.


Nastel delivers Integration Infrastructure Management (i2M), Monitoring, Tracking, and Analytics to detect anomalies, accelerate decisions, and enable customers to constantly innovate. To answer business-centric questions and provide actionable guidance for decision-makers.
The Nastel Platform delivers:

  • Integration Infrastructure Management (i2M)
  • Predictive and Proactive anomaly detection that virtually eliminates war room scenarios and improves root cause analysis
  • Self-service for DevOps and CI: CD teams to achieve their speed to market goals
  • Advanced reporting and alerting for business, IT, compliance, and security purposes
  • Decision Support (DSS) for business and IT
  • Visualization of end-to-end user experiences through the entire application stack
  • Innovative Machine Learning AI to compare real-time to the historical record and discover and remediate events before they are critical
  • Large scale, high-performance complex event processing that delivers tracing, tracking, and stitching of all forms of machine data
  • And much more


  • Dave
    December 21, 2021
    Fascinating piece of research, but what is unclear from this summary of this study is if the AI is actually more or less reliable than human analysis. 5 radiologists is quite a small sample, and the range of accuracy of fake detection is so wide that the results of the AI actually fit inside that range. Are the volumes of tests enough to be statistically viable? And of course the real issue is that compromised images could take many forms, some could be complete real images replacing the image to be tested, while others could have artifacts added or removed. So is the issue AI or the ability to secure the way an image is managed from creation to analysis. That then becomes a integration infrastructure management (i2M) problem.
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