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Back at the beginning of the calendar year, I published an article here in eWEEK titled, “Why Cognitive Intelligence Will Play Pivotal Role in Tech 2016.” Putting artificial brains to work in business use cases is hard to do well, but it hasn’t deterred the bolder enterprises from investing, testing and deploying intelligent applications here in 2016.
By definition, cognitive intelligence is the capability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly and learn from experience. Humans are born with this; machines need humans to make them “smart.” But humans are finding new ways to insert intelligence into IT machines wherever and whenever possible for business purposes.
A cognitive intelligence system such as IBM Watson can ingest scads of data and process it far faster and more accurately than any human can. It also can offer various solutions based upon various use cases, and then lay all of them out to be decided upon by a human.
AI Bringing Automation to Workplaces
Artificial intelligence is improving the workplace by applying automation to big data to replace manual, repetitive tasks. Automation is leaping from the enterprise to the consumer, making the objects around us not just connected, but smarter every day.
Having this capability within an IT system enables C-level leaders to use all their business data to its best purpose: to look at the big picture of the business and its market, see the important trends, and use only facts in the data to make informed decisions that enable the business to grow.
As pointed out by Oracle Big Data and Analytics Vice President Neil Mendelson a while back here in another eWEEK article, data has become actual capital. Ultimately, Mendelson said, information stored about people, places and things will truly differentiate enterprises.
Accordingly, the more data enterprises store up about their customers, the markets, their competitors and their own organizations, the more opportunity enterprises will have to obtain insights that will help grow their bottom lines. There is great potential power in big data.
What Trends eWEEK Is Seeing
What types of software are being used to wring out the truly illuminating facts and figures from volumes of data storage? Enterprises will need a few new-gen tools to do this: secure storage and backup with encryption, solid and dependable data management, fast and intuitive analytics engines and good data visualization (DV) all should be on that list.
Here are current key trends in business intelligence eWEEK is seeing in using insight from big data:
–Data must come from both internal and external sources. Intelligent organizations know smart decisions come from the use of data, but where that information comes from is what matters. To gain true context around trends and industry happenings, organizations must look to both internal and external data sources. Simply focusing on their own data and shying away from the accelerating data boom is a mistake. Organizations that use comprehensive solutions to process information from multiple sources and in multiple views are better able to stay ahead of the game.
–Real-time interaction with business intelligence (BI) will become a requirement. In 2016, BI solutions that excel in reporting but lack analysis via interaction will be a thing of the past. The shift in BI platform requirements, moving from reporting-centric to analysis-centric, means companies will expect to be able to digest and gain insights at a glance. Visualization is key, as users need to be able to understand their data in a way that is natural to them, breaking down the barriers between people and their data.–Governed data discovery will become crucial. As data discovery tools spread to more users across the organization, companies must revamp their governance practices to control the chaos. Data governance, when done correctly, can be tailored to meet the organization’s specific needs, ensuring the efficient and effective use of data while enabling users to make smarter business decisions.
–The evolving role of IT is a key factor. In the past, the role of the chief information officer was to oversee infrastructure and ensure that systems were up and running. Now the “I” in CIO has evolved, and it is much more about innovation and information. CIOs now are being looked upon to transform the organization in a more strategic way—not just to attend to IT infrastructure.
–The need for speed won’t change. The speed of business has accelerated, and IT systems must keep pace. As analytics becomes part of the standard operating procedure, users rely more and more on speed to drive fast and agile business decisions. For example, retailers that once had two major fashion seasons a year now are being pushed to design and distribute new lines each week to keep up with new trends.
–“Information activism” is emerging. Inside each organization, users want to be actively engaged with their data; however, they haven’t had the technology to do so. By providing users with BI solutions that allow true self-service, they move from passively consuming the data to actively using it to glean important information. We live in a world of data—both at a personal and professional level—and people express themselves through the work they do with it.
New Roles for Business Intelligence in IT Decision-Making
What Thought Leaders Are Thinking
eWEEK talks to thought leaders in this area on a regular basis. Here are some thoughts from Chris McLaughlin, chief marketing officer in the Enterprise Content Division at EMC.
–Smart machines and cognitive systems are forming the foundation for automating knowledge work and play an expanded role in enterprise content management—not only in speeding access to information and better personalizing customer experiences, but also in automating routine knowledge-worker activities.
–Smart machines will play a crucial role in customer service and engagement. Not only can Web content be personalized, but cross-channel customer service interactions can be similarly personalized and highly automated. Gartner Research predicts that, by 2017, 70 percent of customer communications will be digital, contextualized and consumed on demand via multiple channels, including the Web, mobile devices and social media. My prediction is that by 2020, smart machines will entirely automate many routine customer communications and service interactions, effectively mimicking human-to-human interactions to provide engaging customer experiences while dramatically reducing costs.
–Smart machines will automate how new content is captured and ingested. One of the ongoing challenges many companies face with digital transformation is that much of their existing knowledge and information is still analog, or trapped in traditional paper forms. Machine learning is starting to play a critical role with document-capture technologies, automating how paper-based content is captured and ingested into corporate knowledge bases. This will not only take tremendous cost out of traditional back-office capture activities, it will also greatly expand the pool of information or knowledge that is available to the organization for reuse, analysis and decision-making.
–Smart machines will increase knowledge-worker productivity. A knowledge worker spends much of his or her day searching for existing content and creating new content. We are seeing expanded applications of cognitive technologies to help knowledge workers find critical and relevant information. Smart machines will be used to observe user behaviors, understand user roles and to deliver critical information proactively to knowledge workers, eliminating valuable time lost each day in searching for content.
Insights From Infosys
Here are insights eWEEK obtained from Abdul Razack, senior vice president and head of big data and analytics at Infosys, a global leader in consulting, technology and IT services.
–“Artificial intelligence is defining the future of work: In 2016, the pace at which enterprises more widely adopt artificial intelligence to replace manual, repetitive tasks will rapidly increase. We’re already seeing enormous investments from companies such as Toyota to use AI for more precise decision-making, and we’ll only see more companies taking this approach to foster higher productivity and business profits, and also streamline responsibility for high-skill jobs. We’ll also start to see the effects of AI in the way we work, with a shift from problem-solving [as one of the most coveted skills in organizations] to problem-finding becoming the way to rise within an organization and drive innovation.”
–“Automation will deliver on the promise of big data: Time and again, we’re seeing big data initiatives fail because of how companies are organizing their data. But in order to capitalize on big data investments, companies need to transform insights into actions. We’re already seeing big data automation being used to streamline and eliminate processes, but in 2016, it will be more widely used to accentuate the unique human ability to take complex problems and deliver creative solutions to them. Google’s open-sourcing its AI engine TensorFlow is a big step in this direction, enabling more companies to apply automation to their big data.”
–“Machine learning is invisibly transforming our lives: 2016 is the year machine learning is making the leap from the workplace to the consumer. We’re already seeing it happen with self-driving cars from Tesla and Amazon Echo’s voice commands. Next year, machine learning will quietly find its way into the household, making the objects around us not just connected, but smarter every day.”