The Five Components of Transformational AI

by | Mar 2, 2018 | GLYNTBlog

It’s B.A.S.I.C.
 
During the past year, I led the development of a new product at WattzOn, GLYNT, which uses machine learning (ML) to transform data trapped in documents (PDFs, scans and images) into structured data flowing to customers. During that year, I witnessed a shift in our priorities, problem framing and conversations. WattzOn became “AI-First.” Now, we are always asking
 
• Does this effort, product feature, or project plan leverage the full powers of AI?
• Is this effort set up to successfully serve and support the AI?
 
These questions change how we see what’s important and how we prioritize activities. AI-First became a company-wide change in thinking. We call this shift of an existing business Transformational AI.
 
As many have noted, AI is a stupendously powerful tool that can transform industries, creating both winners and losers. To be a winner, a company must have more than a toe in the AI water. I’ve summarized what we’ve learned about Transformational AI with the acronym BASIC, which stands for
 
Business impact
AI expertise is not enough
Software in service to AI
Infrastructure to support the AI solution
Collaboration with the non-AI team
 
Transformational AI and the BASIC framework is not meant for companies that just want to add a small AI project. This is a perspective for companies that have acquired a taste of AI through their first projects, and now want to re-think their business strategy and engineering priorities so they can leverage the power of AI throughout their organization.
 
My white paper details what it takes to be AI-First, to transform a company and gain a powerful competitive advantage. This sounds ambitious, but actually it’s just B.A.S.I.C.

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