The four steps to becoming an AI Enterprise

[fa icon="calendar"] Feb 6, 2019 2:59:29 PM / by Jay Barrett

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Organizations need to improve data quality and information architecture to power their transformational efforts. Artificial Intelligence and Machine Learning have proven effective tools to gain insight into enterprise documents and kick off the journey to automation.

Of the roughly 1,100 IT and business executives interviewed for Deloitte’s second annual State of AI in the Enterprise survey, 39 percent identified “data issues” as being among the top three greatest challenges they face with AI initiatives.1  

What does improved data quality accomplish?

According to a recent Deloitte report, organizations 5033_fig2surveyed are looking to AI to enhance current products, optimize internal operations, make better decisions,  optimize external operations and free up workers. (See right)

To leverage the power of AI systems, organizations need to focus on understanding their mass amounts of data across repositories and applications.

Feeding AI systems with clean data improve outcomes and reduce costs. To become an AI-powered organization, you need access to the right data.

Steps to AI Automation

Artificial Intelligence can understand the business value of your content at scale. Tireless, accurate and fast - AI automation saves thousands of hours in manual classification, migration, and remediation, leaving knowledge workers free to work on more meaningful tasks.

Step 1: Manage your data

The first step in every organization's AI automation journey is to manage your documents across the enterprise. Organizations need to apply policies to all data including documents living in file shares and email.

Step 2: Understand your data

Visualize all your information and get the bigger picture, expose data value, identify vulnerabilities, and eliminate ROT. This step is vital in gaining valuable insights into your business.

Step 3: Let the data understand itself

Artificial Intelligence understands the business value of your content at scale. Let machine learning automatically classify and enrich documents.  

Step 4: Data manages itself

Automate business tasks, triggering workflows, processing transactions and building towards predictive analytics that drives actionable insights.

 

How Artificial Intelligence tackles Big Data - Shinydocs Cognitive Analysis

 

 

On February 28th, Shinydocs hosted: “What we’ve learned from crawling our customers’ data” webinar, which will highlight examples of how our customers are on the journey to AI automation.

Sign up today to learn how you can get started on the journey to AI automation.

 

Register here

 

Shinydocs can start to manage your documents after only a 60-minute call. Shinydocs Cognitive Analysis is a lightning-fast way to leverage your unstructured data to power insights, improve processes, and meet compliance requirements.

1. https://www2.deloitte.com/insights/us/en/focus/tech-trends/2019/driving-ai-potential-organizations.html

Topics: AI

Jay Barrett

Written by Jay Barrett

Customer Engagement at Shinydocs Corporation. My goal is to help customers realize the value of enterprise data.

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