EVIDENCE BASEDDEEP LEARNING
Artificial Intelligence (AI) isn’t new. It has been around for decades, but AI technologies
are only making headway now due to the proliferation of data and the investments being
made in storage, tracking and analytics technologies. Based on a survey of 235 business
executives, we discovered:
Between 2014 and 2015 alone, the number of organizations either
deploying or implementing data-driven projects increased by 125%1
62% of organizations will be using AI technologies by 2018
of respondents currently
use predictive analytics
of enterprises’ net new
investment in business
intelligence and analytics2
59% of our survey respondents cited a
lack of data science talent to help them
analyze their data and communicate
insights as one of the most common
challenges they face in trying to generate
value from their data.
In fact, 95% of respondents who indicated that they are skilled at using big data to solve
business problems or generate insights also use AI technologies.
Global demand for data scientists will
exceed supply by more than 50% by
2018. Without individuals trained at
analyzing complex data, companies can
easily miss out on a valuable asset.5
of organizations currently
use AI technologies in
the workplace
AI adoption is imminent.
Outlook on Artificial
Intelligence in the Enterprise
Companies are
benefiting from
AI-powered solutions,
without realizing it.
There is
confusion in the
marketplace.
Paradoxically,
88%of those claiming to not be
users of AI went on to cite
using specific solutions that
rely on AI techniques
???
NLP/TEXT MINING
The AI Ecosystem
NATURAL LANGUAGE GENERATION
PREDICTIVE
ANALYTICS
RECOMMENDATION
ENGINES
MACHINE
LEARNING SYSTEMS
PRESCRIPTIVE
ANALYTICS
Predictive analytics is
dominating the enterprise.
The shortage of data science talent
continues to affect organizations.
Gartner anticipates that by 2020, predictive analytics will attract
One of the reasons for the popularity of predictive analytics may be the
tremendous potential that it can offer across an array of industries.
Last but not least...
Healthcare
It’s being used to anticipate and
prevent costly and unnecessary
hospital readmissions3
Manufacturing
It’s allowing for more efficient
supply chain management by
adjusting for potential delays4
?
What all of this suggests is that as companies have
ever more data to work with, they’re going to require
the machine scalability that AI-based solutions make
possible to truly realize its value.
Companies that gather the most value from their
technology tend to make innovation a priority.
For the full Outlook on Artificial Intelligence
in the Enterprise report, please visit:
https://narrativescience.com/OutlookAI
61% of the respondents
who had an innovation
strategy are using AI to
identify opportunities in
data that would be
otherwise missed.
Of the business leaders
surveyed for this report,
54% indicated that their
organization has an
innovation strategy.
While 62% of business
leaders noted that their
companies have a
dedicated innovation
budget.
“2015 Big Data and Analytics, Insights into Initiatives and Strategies Driving Data Investments,” IDG, March 9, 2015.
Lisa Kart, Gareth Herschel, Alexander Linden, Jim Hare, “Magic Quadrant for Advanced Analytics Platforms,” Gartner,
February 9, 2016.
“Using Data Science to Tackle Home Healthcare Readmissions Head On,” SlideShare, May 19, 2016.
Tyson Baber, “How FusionOps is Delivering the Future Supply Chain: On-Time In-Full, ”georgianpartners.com, April 19, 2016.
James Manyika, Michael Chui, Brad Brown, Jacques Bughin, Richard Dobbs, Charles Roxburgh, and Angela Hung Byers, “Big
data: The next frontier for innovation, competition, and productivity,” McKinsey & Company, May 2011.
Additional Sources
1
2
3
4
5
Possible Answers
Documents
Unstructured Data Structure Trends &
Correlations
Input Layer
Hidden Layers
Output Layer
Recommendation
Data
Facts
Assessments
Language
Assessment
Advice
Available Features
Document
Extraction Rules
DATA
“January 10, 2015”
“Tax Reform”
“US Congress”
“Barack Obama”
“IRS”
“John Boehner”
Prediction
Available Features
58%
40%
62%54%61%
38% of organizations could
not confirm the use of
AI technologies
62%

Outlook on Artificial Intelligence in the Enterprise 2016

  • 1.
    EVIDENCE BASEDDEEP LEARNING ArtificialIntelligence (AI) isn’t new. It has been around for decades, but AI technologies are only making headway now due to the proliferation of data and the investments being made in storage, tracking and analytics technologies. Based on a survey of 235 business executives, we discovered: Between 2014 and 2015 alone, the number of organizations either deploying or implementing data-driven projects increased by 125%1 62% of organizations will be using AI technologies by 2018 of respondents currently use predictive analytics of enterprises’ net new investment in business intelligence and analytics2 59% of our survey respondents cited a lack of data science talent to help them analyze their data and communicate insights as one of the most common challenges they face in trying to generate value from their data. In fact, 95% of respondents who indicated that they are skilled at using big data to solve business problems or generate insights also use AI technologies. Global demand for data scientists will exceed supply by more than 50% by 2018. Without individuals trained at analyzing complex data, companies can easily miss out on a valuable asset.5 of organizations currently use AI technologies in the workplace AI adoption is imminent. Outlook on Artificial Intelligence in the Enterprise Companies are benefiting from AI-powered solutions, without realizing it. There is confusion in the marketplace. Paradoxically, 88%of those claiming to not be users of AI went on to cite using specific solutions that rely on AI techniques ??? NLP/TEXT MINING The AI Ecosystem NATURAL LANGUAGE GENERATION PREDICTIVE ANALYTICS RECOMMENDATION ENGINES MACHINE LEARNING SYSTEMS PRESCRIPTIVE ANALYTICS Predictive analytics is dominating the enterprise. The shortage of data science talent continues to affect organizations. Gartner anticipates that by 2020, predictive analytics will attract One of the reasons for the popularity of predictive analytics may be the tremendous potential that it can offer across an array of industries. Last but not least... Healthcare It’s being used to anticipate and prevent costly and unnecessary hospital readmissions3 Manufacturing It’s allowing for more efficient supply chain management by adjusting for potential delays4 ? What all of this suggests is that as companies have ever more data to work with, they’re going to require the machine scalability that AI-based solutions make possible to truly realize its value. Companies that gather the most value from their technology tend to make innovation a priority. For the full Outlook on Artificial Intelligence in the Enterprise report, please visit: https://narrativescience.com/OutlookAI 61% of the respondents who had an innovation strategy are using AI to identify opportunities in data that would be otherwise missed. Of the business leaders surveyed for this report, 54% indicated that their organization has an innovation strategy. While 62% of business leaders noted that their companies have a dedicated innovation budget. “2015 Big Data and Analytics, Insights into Initiatives and Strategies Driving Data Investments,” IDG, March 9, 2015. Lisa Kart, Gareth Herschel, Alexander Linden, Jim Hare, “Magic Quadrant for Advanced Analytics Platforms,” Gartner, February 9, 2016. “Using Data Science to Tackle Home Healthcare Readmissions Head On,” SlideShare, May 19, 2016. Tyson Baber, “How FusionOps is Delivering the Future Supply Chain: On-Time In-Full, ”georgianpartners.com, April 19, 2016. James Manyika, Michael Chui, Brad Brown, Jacques Bughin, Richard Dobbs, Charles Roxburgh, and Angela Hung Byers, “Big data: The next frontier for innovation, competition, and productivity,” McKinsey & Company, May 2011. Additional Sources 1 2 3 4 5 Possible Answers Documents Unstructured Data Structure Trends & Correlations Input Layer Hidden Layers Output Layer Recommendation Data Facts Assessments Language Assessment Advice Available Features Document Extraction Rules DATA “January 10, 2015” “Tax Reform” “US Congress” “Barack Obama” “IRS” “John Boehner” Prediction Available Features 58% 40% 62%54%61% 38% of organizations could not confirm the use of AI technologies 62%