We've written a lot about the convergence of cloud infrastructure, Big Data, and artificial intelligence (AI) this year. Throughout the Software-as-a-Service (SaaS) space, we've seen an inextricable link between these three factors in business intelligence (BI) tools, social listening platforms, customer relationship management (CRM) solutions, or really any industry that's leveraging cloud-based data ingestion and analysis—which is pretty much all of them.
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Across use cases, we've observed a four-step process. Enterprise businesses gather massive amounts of data by using a portfolio of SaaS apps. They then store that data in the cloud by using a data warehouse or data lake, using data governance to keep data compliant and secure. Step three is data science experimentation: throwing everything at the data, from machine learning (ML) algorithms and natural language processing (NLP) to predictive analytics. Step four, ideally, is where that data science yields deeper, data-driven business insights from which your organization can take action and gain an edge.
The execution differs but the idea is the same. Salesforce are combining AI and data management with its Einstein platform. The cloud players themselves, such as Google Cloud Platform and Microsoft Azure, are employing an arsenal of cognitive computing tools and ML algorithms to redefine business clouds. Others still are inching closer and closer—through the combined power of AI, cloud, and Big Data—to truly map an AI brain.
10 AI, Cloud, and Data Trends for 2017
As we head into 2017, these three factors are only growing more intertwined. We spoke to companies and experts from all over the industry about how the convergence will continue to play out, and how AI, cloud, and data technology will also continue to evolve and morph on their own.
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1. AI Everywhere
Dr. Michael Bjorn, Head of ConsumerLab Research at business-to-business (B2B) communications and networking giant Ericsson, talked about AI as a given in all new technology vectors. Ericsson's Top 10 Trends for 2017 research starts off with "AI Everywhere" atop the list. Dr. Bjorn explained the lab's thinking behind the prediction.
"With every new topic, there is an AI dimension," said Dr. Bjorn. "AI everywhere is the angle that informs every other trend on our list. It plays into AR, VR, and merged reality, autonomous cars, the Internet of Things…look at an IoT application like Amazon's machine learning experimental store with Amazon Go.
"We're starting to see people getting used to AI as an assistant, but now we're moving toward AI as more of a manager, proactively helping with tasks. This can also be scary because of the notion of AI and robots taking jobs but much of that is perception. Technology creates jobs. If you go way back to the industrial revolution, we automated the easiest jobs and new jobs were created as a result. What we're seeing with AI is that jobs will change across the whole scale, because going from AI assistants to AI managers is more complex."
2. AI Investment Will Triple
Research firm Forrester predicts that investment in AI technology will triple in 2017, projecting an increase of more than 300 percent in cognitive computing investment as compared to 2016. Consequently, Forrester also predicts that 2017 will kick off an "insights revolution" in which businesses will prioritize customer data insights as a key differentiator going forward, with Big Data integrations and data management projects set to increase by 75 percent as a result.
3. Cloud Comfort
Cloud-based business platforms are proliferating across every vertical, including small business accounting. At the recent SaaS North conference, FreshBooks CEO Mike McDerment talked about a growing level of comfort with SaaS experiences, even in a traditional industry such as accounting and finance.
"People are getting more and more comfortable with the cloud. It's past the earliest of days, which to me is exciting," said McDerment. "We enabled our customers to file an expense or create an invoice with the five minutes they have when their kid goes to brush their teeth. Entrepreneurs try to get things done in these little pockets of time, so having your business with you on your phone and in the cloud gives you this convenience, contributing to the massively growing number of people choosing to run their businesses with cloud-based technologies."
4. Pure Cloud Becomes the Norm
Cloud disruption affects all industries with legacy technology and the business Voice-over-IP (VoIP) space is no exception. Craig Walker, CEO of business VoIP provider Dialpad, said digital disruption will spur enterprise leaders to adopt cloud-based solutions while legacy players consolidate or acquire next-generation providers.
"As every business eyes its own digital transformation, 2017 will be the year that modern, relevant businesses finally kill the the desk phone for good," said Walker. "As enterprises move to the cloud to make their employees more productive from anywhere, cloud-based solutions that enable seamless communication and collaboration across devices and locations are a necessity.
"I expect to see a lot of consolidation ahead for the industry as legacy phone providers fall further and further behind the cloud communications providers who can give higher quality, faster, and easier deployments—from anywhere on any device—at a much lower total cost of ownership. As the nature of work changes, powered by data and driven by speed, businesses will also seek a solution that integrates with their internal data to place knowledge at sales and support teams' fingertips, no matter where they are to gain an edge over the competition."
5. The Cloud Race Will Narrow
The IaaS space has a number of big players but the undisputed market leader is Amazon Web Services (AWS). According to the latest Cloud Adoption and Risk Report from cloud security provider Skyhigh Software, Amazon will maintain its lead while market challengers gain ground in 2017.
"Microsoft will narrow the gap with Amazon for a neck-and-neck race for IaaS dominance," said Rajiv Gupta, CEO of Skyhigh Neworks. "AWS had the fastest breakout of the gate in the IaaS market but Azure is closing in: 35.8 percent of new cloud apps in Q4 were deployed in AWS followed by 29.5 percent in Azure. Niche providers have carved out 14 percent of the market independent of brand names like Google, Rackspace, and IBM/SoftLayer."
6. Big Data Becomes Fast and Approachable
Diving deeper into the data weeds, BI provider Tableau predicts that the barrier to leveraging Big Data will lower even further. Dan Kogan, Director of Product Marketing at Tableau, said advancements in interactive SQL will make for faster Hadoop querying.
"Sure, you can perform machine learning and conduct sentiment analysis on Hadoop, but the first question people often ask is: How fast is the interactive SQL? SQL, after all, is the conduit to business users who want to use Hadoop data for faster, more repeatable [key performance indicator] KPI dashboards as well as exploratory analysis," said Kogan. "In 2017, options will expand to speed up Hadoop. This shift has already started, as evidenced by the adoption of faster databases like Exasol and MemSQL, Hadoop-based stores like Kudu, and technologies that enable faster queries."
7. Self-Service Extends to Data Prep
Tableau also foresees the capabilities of self-service analysis and data visualization tools extending to even more aspects of the data management pipeline. Francois Ajenstat, Chief Product Officer at Tableau, said business users will gain greater access beyond simple data discovery to deeper data prep and analysis.
"While self-service data discovery has become the standard, data prep has remained in the realm of IT and data experts. This will change in 2017," said Ajenstat. "Common data-prep tasks like data parsing, JSON, HTML imports, and data wrangling will no longer be delegated to specialists. With new innovations in this transforming space, everyone will be able to tackle these tasks as part of their analytics flow."
8. Big Data for Governance or Competitive Advantage
In 2017, the data governance versus data value tug of war will be front and center. John Schroeder, Executive Chairman and founder of enterprise Hadoop company MapR, said businesses will have a wealth of information about their customers and partners feeding into new data-driven strategies, particularly when it comes to compliance.
"Organizations are now facing an escalating tug of war between governance required for compliance and the use of data to provide business value and implement security to avoid damaging data leaks and breaches," said Schroeder. "Financial services and healthcare are the most obvious industries, with customers counting in the millions with heavy governance requirements. Leading organizations will manage their data between regulated and non-regulated use cases."
9. Data Lakes Overtake Data Swamps
MapR's Schroeder also predicts that, in 2017, organizations will shift from a "build it and they will come" data lake approach to a business-driven data approach that will combine analytics and operations. Consequently, he said that "data agility" between back-office analytics and front-office operations will separate the winning and losing organziations when it comes to seeing return-on-investment (ROI) on that data.
"In 2017, organizations will push aggressively beyond an 'asking questions' approach and architect to drive initial and long-term business value," said Schroeder. "Approaching a data lake as 'Imagine what your business could do if all your data were collected in one centralized, secure, fully-governed place that any department can access anytime, anywhere' could sound attractive at a high level. But too frequently [this] results in a data swamp that looks like a data warehouse rebuild and can't address real-time and operational use case requirements. Once in place, the concept is to 'ask questions.' In reality, the world moves faster today.
"Today's world requires analytics and operational capabilities to address customers, process claims, and interface to devices in real time at an individual level," added Schroeder. "For example, any e-commerce site must provide individualized recommendations and price checks in real time. Healthcare organizations must process valid claims and block fraudulent claims by combining analytics with operational systems. Media companies are now personalizing content served though set top boxes. Auto manufacturers and ride sharing companies are interoperating at scale with cars and the drivers."
10. Mainstream AI Is Here to Stay
AI has gone in and out of vogue over the past half-century but the concept of machine and deep learning algorithms applying to Big Data is here to stay. MapR's Schroeder said we'll see rapid adoption in 2017 in the form of relatively straightforward algorithms deployed on large data sets to address repetitive automated tasks.
"AI is now back in mainstream discussions and [is] the umbrella buzzword for machine intelligence, machine learning, neural networks, and cognitive computing," said Schroeder. "Why is AI a rejuvenated trend? The three Vs come to mind: velocity, variety, and volume. Platforms that can process the three Vs with modern and traditional processing models that scale horizontally provide 10-20x cost efficiency over traditional platforms. We'll see the highest value from applying AI to high-volume repetitive tasks where consistency is more effective than gaining human intuitive oversight at the expense of human error and cost."