Digital Transformation through AI, has it's Challenges
Updated: Jun 6, 2018
by John Leschorn, COO, Lucd
Facilitating a digital transformation through the implementation of AI solutions is fraught with many challenges.
Lucd’s AI as a Service platform solves the technical challenges of data ingest, management, security and fusion. However, once we have resolved these issues a vexing issue remains. Business executives have their universe of challenges and opportunities. With each new wave of innovation they are told that ‘the next great technology’ will transform their business. They are frequently approached by wild eyed technology enthusiasts that think they have all of the answers without really knowing the questions. Unfortunately this enthusiasm does not make up for the lack of experience in the business world, most transformative efforts can end in failure.
Don’t start with the answer.
Today, Lucd is capable of supporting millions of different use cases but with each integrated feature and capability we expand that number as we lower the barrier to AI adoption in the enterprise. We have discovered in our interactions with clients and industry partners that a consultative methodology and solution oriented approach is needed to discover how AI can transform an enterprise or an industry at large.
A journey of discovery must be undertaken to establish the best path forward.
Lucd Envision is our methodology for discovering how AI can transform the enterprise by implementing those transformational capabilities at scale. It is designed to facilitate an iterative deliberate effort that shows value at each stage of the process, minimizing the risks while maximizing the value of the proposed solutions.
Lucd Envision has three phases Capture, Secure and Harness.
The capture phase is focused on exploring the art of the possible, by implementing Lucd’s capabilities in low impact engagements to ingest and fuse data, enabling the discovery of new insights, identifying and validating key use cases for development of pilot engagements. Activities in the secure phase are directed at building confidence in the veracity of solutions powered by the Lucd platform. Implementing solutions at scale is the purpose of theharness phase with a goal of continuous improvement and iterative discovery of new applications for AI in the enterprise.
Quality AI outcomes are the result of a thoughtful and iterative process of discovery, confidence building and successful solution delivery.