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The State of Artificial Intelligence in 2019

[fa icon="calendar"] Jan 3, 2019 2:19:06 PM / by Jay Barrett

ai2019

The promise of Artificial Intelligence has been dominating the headlines for the last few years, promising massive disruption across all industries. “Fifty-three percent of global data and analytics technology decision makers are implementing or expanding their use of AI, while another twenty percent plan to implement AI in the next 12 months.”1 Even though AI has been dominating the headlines in 2018, there has still been very few massive deployments of enterprise AI. Instead, CXOs have been focusing on quick win AI projects to drive real ROI. In 2019, this shift will continue as organizations realize that a massive enterprise AI deployment is not possible with the current state of their data.

In a recent Forrester Report, Michele Goetz said:

Data doldrums will continue to drown the majority of firms embarking on AI. The No. 1 challenge for AI adopters is quality data. The CTO of a government agency specifically stated that unless they can trust the data, they can't use AI. The tables will turn from AI to Infrastructure Architecture (IA) for the majority of firms that have already dabbled in some form of AI. They will quickly realize their irrational exuberance for AI adoption must be equally met with solid efforts on an AI-worthy data environment.”2

In 2019, organizations need to become “data-first” in order to ensure a successful deployment of AI. CIOs will invest heavily in delivering quality data to feed their AI tools. The good news for companies is they have massive amounts of valuable data already in their organization, they just need to harness it.

Shinydocs has a foolproof strategy to get you up and running fast. Our customers are blown away by the ease and simplicity of installation. Read the following guide on how to deploy the Shinydocs solutions across your business:

  1. Install Software - Takes a simple 60-minute call to install our toolkit at your organization and start crawling your environment.
  2. Quick Win - Full Metadata across data sets looking for file types, date ranges.
  3. Visualize data - Shortens business conversations as you can discuss the exact data in your organization.
  4. Sets up a quick win - The data set is reduced as much as 60% based on date ranges, file types, and duplicates. By aggregating virtual servers, a petabyte of data can be crawled in as little as a few months.
  5. In parallel, a Full-Text extraction crawl is initiated across all sources. This sets up the opportunity for federated search, classification and entity extraction. Focus on the most critical information that’s deemed high value and classify that first. Conversely, zero value documents can be slated for disposal. This should come easily to every department. The remaining data can be readily classified and/or disposed of as the business delivers the rules.
  6. Data is now understood and can be tiered to desired destinations.
  7. You now have clear, valuable and classified information ready to be fed into your RPA and AI tools.

The time to get started is early 2019 because it’s too late. Reach out to Shinydocs to learn how you can start to improve your data quality and get ready for the AI wave coming to every industry.

 

  1. Forrester Analytics Global Business Technographics Data And Analytics Survey, 2018.
  2. Forrester Predictions 2019: Artificial Intelligence No Pain, No Gain With Enterprise AI

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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