PREDICTIONS 2016 PREDICTIONS FOR ARTIFICIAL INTELLIGENCE, DATA AND INNOVATION: 1. ARTIFICIAL INTELLIGENCE WILL STEP INTO THE MAINSTREAM Major tech companies such as Google, Facebook , Amazon and Twitter made huge investments in artificial intelligence, almost all of Gartner’s strategic predictions included AI and headlines repeatedly declared that AI-driven technologies were the next big disruptor to enterprise software. There is still a long way to go but the formidable level of investment this year made it clear that AI-powered business and consumer solutions are on their way to being widely accepted everywhere. NEW AI INVENTIONS WILL EXPLODE WHAT DOES IT MEAN FOR 2016? WHAT DOES IT MEAN FOR 2016? WHAT DOES IT MEAN FOR 2016? As artificial intelligence stepped into the mainstream, another change took place. Companies that made huge strides in AI, including Facebook, Microsoft, and Google, open-sourced their tools. For 2016, new inventions will increasingly come to market through companies discovering new ways to apply AI versus building it. There will also be an explosion in startups with entrepreneurs now having access to low-cost quality AI technologies to create new products. BI PLATFORMS WILL ENTER A NEW ERA Helping to maximize the value of data and scale the amount of stories that can be told, natural language generation capabilities will begin to be integrated into BI platforms. Modernized platforms will increase the reach of analytics within organizations as the average user will be able to quickly understand and act upon insight. 2. “A PICTURE IS WORTH A THOUSAND WORDS” IS A MARKETING PITCH Visualization investments continued to thrive in 2015, but there was also a growing recognition that good data analytics is in fact storytelling. Industry thought leader Tom Davenport said it accurately, “whether your analytical stories are told by human or machine, the key is to recognize the importance of simple and clear storytelling in the communication of quantitative analysis.” EXECS WILL DEMAND TRANSPARENCY FROM INTELLIGENT SYSTEMS Paired with the growing trend of intelligent systems being used to provide answers, there will also be a growing belief that the data isn’t enough; users will want context too. Communication capabilities will increasingly be built into advanced analytics and Intelligent systems so that these systems can explain how they are arriving at their answers. 3. DEMOCRATIZATION OF DATA WILL BECOME THE DEMOCRATIZATION OF INFORMATION We predicted that difficulties related to the average user interpreting data would lead to mass demand for information versus more data. This isn’t occurring just yet as companies are as data-hungry as ever. That said, we are beginning to see a shift toward companies questioning how they’ll actually use all the data they’re amassing. (DATA) SIZE DOESN’T MATTER Facing unprecedented volumes of data and complex global infrastructures, big companies will kick off efforts to merge disparate data sets. Paired with improved, advanced analytics, we’ll see a movement away from big data hype as businesses will also focus on understanding their small data, or datasets that contain very specific attributes,to determine current states and conditions and make more immediate business decisions. 4. THE END OF THE DATA-HOARDING ERA We believed that companies would begin to stop focusing on data collection and increasingly focus on the insight from the data. While this has happened to some extent, we’re seeing a shift towards companies being more nuanced with their data and focusing on collecting segmented sets as it pertains to their business objectives. PORTIONS OF DATA SCIENCE WILL BE INCREASINGLY AUTOMATED INNOVATION LABS WILL BECOME A COMPETITIVE ASSET The option of implementing a scalable automated data science system and training an analyst to use the system will increasingly be a popular choice. Data scientists will still be in demand in 2016, but we don’t think the filling the role will be as urgent as in 2015. With the pace of innovation accelerating exponentially, large organizations in industries like retail, insurance and government, will focus even more energies on remaining competitive and discovering the next big thing by forming innovations labs. Innovation labs have existed for some time but in 2016, we’ll begin to see more resources devoted to innovation labs and more technologies discovered in the labs actually implemented in their parent company. 5. DATA SCIENTISTS AREN’T AS SEXY AS WE THOUGHT Job postings for data scientists actually increased in 2015 so we were a little too aggressive in our prediction. However, it is a challenging role to fill due to job descriptors varying, high costs and other reasons, so companies are finding new ways to solve their data science needs. Stay tuned for how we do and check back in December 2016 to hear our hits and misses. End of year predictions can be bittersweet. They allow us to reflect on the year that has passed, what we’ve accomplished (or didn’t accomplish!) as well as allowing us to be hopeful of what is to come. Sometimes that hope takes form in predictions that wildly overshoot what is actually possible to occur in the very near-term. So, what realistically will happen in 2016 based off of what we’ve experienced this year? Before we crank up the prediction machine, we decided to assess our predictions from last year to learn what proved true, where we missed the mark, what areas had early indicators of change but we were a bit too early and what it all means for 2016. 1. Artificial intelligence will step into the mainstream 4. The end of the data-hoarding era 5. Data scientists aren’t as sexy as we thought 2. “A picture is worth a thousand words” is a marketing pitch 3. Democratization of data will become the democratization of information HIT OR MISS? PREDICTION NAILED IT! NOT QUITE YET MISSED THE MARK NOT QUITE YET NOT QUITE YET NAILED IT! NOT QUITE YET MISSED THE MARK NOT QUITE YET WHAT DOES IT MEAN FOR 2016? WHAT DOES IT MEAN FOR 2016? NOT QUITE YET HITS & MISSES And our new prediction for 2016 (because who doesn’t like ‘new’)? is:
2016 Predictions for Artificial Intelligence, Data and Innovation: Hits and Misses [INFOGRAPHIC]
Jan 18, 2017
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PREDICTIONS2016 PREDICTIONSFOR ARTIFICIAL INTELLIGENCE, DATA AND INNOVATION:
AC
XXCD
1. ARTIFICIAL INTELLIGENCE WILL STEP INTO THE MAINSTREAMMajor tech companies such as Google, Facebook , Amazon and Twitter made huge investments in artificial intelligence, almost all of Gartner’s strategic predictions included AI and headlines repeatedly declared that AI-driven technologies were the next big disruptor to enterprise software. There is still a long way to go but the formidable level of investment this year made it clear that AI-powered business and consumer solutions are on their way to being widely accepted everywhere.
NEW AI INVENTIONS WILL EXPLODEWHAT DOES ITMEAN FOR 2016?
WHAT DOES ITMEAN FOR 2016?
WHAT DOES ITMEAN FOR 2016?
As artificial intelligence stepped into the mainstream, another change took place. Companies that made huge strides in AI, including Facebook, Microsoft, and Google, open-sourced their tools. For 2016, new inventions will increasingly come to market through companies discovering new ways to apply AI versus building it. There will also be an explosion in startups with entrepreneurs now having access to low-cost quality AI technologies to create new products.
BI PLATFORMS WILL ENTER A NEW ERA
Helping to maximize the value of data and scale the amount of stories that can be told, natural language generation capabilities will begin to be integrated into BI platforms. Modernized platforms will increase the reach of analytics within organizations as the average user will be able to quickly understand and act upon insight.
2. “A PICTURE IS WORTH A THOUSAND WORDS” IS A MARKETING PITCH
Visualization investments continued to thrive in 2015, but there was also a growing recognition that good data analytics is in fact storytelling. Industry thought leader Tom Davenport said it accurately, “whether your analytical stories are told by human or machine, the key is to recognize the importance of simple and clear storytelling in the communication of quantitative analysis.”
EXECS WILL DEMAND TRANSPARENCY FROM INTELLIGENT SYSTEMS
Paired with the growing trend of intelligent systems being used to provide answers, there will also be a growing belief that the data isn’t enough; users will want context too. Communication capabilities will increasingly be built into advanced analytics and Intelligent systems so that these systems can explain how they are arriving at their answers.
3. DEMOCRATIZATION OF DATA WILL BECOME THEDEMOCRATIZATION OF INFORMATION
We predicted that difficulties related to the average user interpreting data would lead to mass demand for information versus more data. This isn’t occurring just yet as companies are as data-hungry as ever. That said, we are beginning to see a shift toward companies questioning how they’ll actually use all the data they’re amassing.
(DATA) SIZE DOESN’T MATTER
Facing unprecedented volumes of data and complex global infrastructures, big companies will kick off efforts to merge disparate data sets. Paired with improved, advanced analytics, we’ll see a movement away from big data hype as businesses will also focus on understanding their small data, or datasets that contain very specific attributes,to determine current states and conditions and make more immediate business decisions.
4. THE END OF THE DATA-HOARDING ERA
We believed that companies would begin to stop focusing on data collection and increasingly focus on the insight from the data. While this has happened to some extent, we’re seeing a shift towards companies being more nuanced with their data and focusing on collecting segmented sets as it pertains to their business objectives.
PORTIONS OF DATA SCIENCE WILL BE INCREASINGLY AUTOMATED
INNOVATION LABS WILL BECOME A COMPETITIVE ASSET
The option of implementing a scalable automated data science system and training an analyst to use the system will increasingly be a popular choice. Data scientists will still be in demand in 2016, but we don’t think the filling the role will be as urgent as in 2015.
With the pace of innovation accelerating exponentially, large organizations in industries like retail, insurance and government, will focus even more energies on remaining competitive and discovering the next big thing by forming innovations labs. Innovation labs have existed for some time but in 2016, we’ll begin to see more resources devoted to innovation labs and more technologies discovered in the labs actually implemented in their parent company.
5. DATA SCIENTISTS AREN’T AS SEXY AS WE THOUGHT
Job postings for data scientists actually increased in 2015 so we were a little too aggressive in our prediction. However, it is a challenging role to fill due to job descriptors varying, high costs and other reasons, so companies are finding new ways to solve their data science needs.
Stay tuned for how we do and check backin December 2016 to hear our hits and misses.
End of year predictions can be bittersweet. They allow us to reflect on the year that has passed, what we’ve accomplished (or didn’t accomplish!) as well as allowing us to be hopeful of what is to
come. Sometimes that hope takes form in predictions that wildly overshoot what is actually possible to occur in the very near-term. So, what realistically will happen in 2016 based off of
what we’ve experienced this year?
Before we crank up the prediction machine, we decided to assess our predictions from last year to learn what proved true, where we missed the mark, what areas had early indicators of change
but we were a bit too early and what it all means for 2016.
1. Artificial intelligence will step into the mainstream
4. The end of the data-hoarding era
5. Data scientists aren’t as sexy as we thought
2. “A picture is worth a thousand words” is amarketing pitch
3. Democratization of data will become thedemocratization of information
HIT OR MISS?PREDICTIONNAILED IT!
NOT QUITE YET
MISSED THE MARK
NOT QUITE YET
NOT QUITE YET
NAILED IT!
NOT QUITE
YET
MISSED THE
MARK
NOT QUITE
YET
WHAT DOES ITMEAN FOR 2016?
WHAT DOES ITMEAN FOR 2016?
NOT QUITE
YET
HI TS & MISSES
And our new prediction for 2016 (because who doesn’t like ‘new’)? is:
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