The rise of Artificial Intelligence and Machine Language in a Connected World
Since 1995, the number of internet users has grown from 16 million to about 3.6 billion in 2016. This growth in usage results in one thing – more data. Looking back at the year 2016, trends in Business Intelligence and Analytics reveals a common message around increased data and significant strides in BI and Analytics technologies. Beginning with Internet of Things (IoT), businesses started to experiment with potential use cases and solutions that would derive data from sensors, machines, server logs and internet, and moved to Internet of Anything (IoA). The need for simplification of Big Data technologies was significant. Big data technologies moved from “web” companies such as Yahoo! and Facebook to more traditional companies. Data democratization moved a notch higher with more businesses moving their applications to the Cloud, breaking silos and redundancies, and providing access with rapidly evolving modern BI tools.
In 2017, five BI and analytics trends are expected to rise and shift conventional approaches to a more innovative (artificial intelligence) AI-based industrial-grade analytics.
Trend #1: The rise of mainstream Connected Services Platforms and Applications
In 2017, 87 percent of the worldwide smart connected device market will be tablets and smartphones, with PCs (both desktop and laptop) being 13% of the market.1 By 2020, 74 percent, 17 percent and 8 percent of the total cloud workloads will be Software-as-a-Service (SaaS), Infrastructure-as-a-Service (IaaS), and Platform-as-a-Service (PaaS) respectively.2
We see a growing trend of powerful, integrated end-to-end solutions that utilize embedded design, device, cloud, mobile, and analytics capabilities. Within the consumer segment, we see digital platforms such as social media, mobile apps, online marketplaces and an increase in video streaming services to be the main contributors of data and workloads. Within the enterprise segment, we see machine-to-machine connectivity, monitoring devices, conversational AI-based systems to be the main contributors of data and workloads.
The worldwide IoT Market will grow from $1.3 trillion in 2013 to $3.04 trillion in 2020.3 By 2020, there will be 30 billion connected devices in use. These smart and connected devices will in turn drive connected supply chain and smart manufacturing. In order to take advantage of this new industrial economy, for example, General Electric has created Predix, a cloud-based operating system, for industrial applications and automation, built on a cloud foundry that optimizes for secure connectivity and analytics at scale.
However, the challenges around lack of industry standards and well-defined best practices for IoT, regarding connectivity, data storage, and security will continue to drive innovation to make it better.
Trend #2: The shift towards Modern BI
In 2016, the progressive shift over the years from IT-led reporting to business-led self-service analytics passed the tipping point, empowering the business users with the power of advanced, statistically sound business analytics for agile, simple, actionable, and relevant decision-making. Modern BI and analytics tools have broken the traditional data warehousing paradigms by abstracting the end-to-end process, not requiring semantic models or even a data warehouse. They offer a highly interactive and intuitive visual-based exploration experience for business users.
In 2017, we see more and more businesses are investing in cloud-capable, robust BI platforms that can handle multiple data management capabilities such as integration, storage, visualization, statistical and quantitative analysis, instead of multiple specialty tools.
Trend #3: The rise of Artificial Intelligence (AI), Machine Language (ML) and Cognitive Computing Assets
In 2020, the worldwide adoption of cognitive and AI is estimated to grow from $8 billion in 2016 to more than $47 billion.4 38 percent of enterprises are already using AI technologies (that includes machine language, deep learning, predictive and prescriptive analytics) while 62 percent will use AI technologies by 2018.5
As described by Klaus Schwab, the fourth industrial revolution, in its scale, scope and complexity, driven by increased adoption of mobile devices, and application of AI, ML, robotics, IoT, autonomous vehicles, 3-D printing, nanotechnology, biotechnology, materials science, energy storage, and quantum computing, is disrupting exponentially almost every industry in the country.6
The market for AI technologies is beyond the hype and its adoption in applications is hitting main-street. Enterprises have started embracing text analytics and natural language processing (NLP), natural language generation (NLG), Speech Recognition, Virtual Agents, Machine Language and Deep Learning Platforms, AI-optimized Hardware, and Robotic Process Automation.7
AI and machine language will redefine how organizations use the advanced analytics techniques and predictive algorithms to create economic impacts. As data volumes, variety and velocity increases, algorithmic models get trained, and re-trained to get smarter. It will push traditional Pareto principles to smart paretos, super-paretos and supra-paretos as data becomes more granular and algorithms process complex patterns in data.8
Trend #4: Data Strategy, Governance and Security reimagined
In the last couple of years, as the value and cost drivers have been dynamically changing due to the pace of disruption in technology, politics and industry, businesses face shrinking revenues, regulatory measures, and saturated opportunities. In order to change the value propositions to remain relevant, they are turning towards data assets to gain competitive advantage. They are sitting on massive amounts of data that need to be harnessed and insights have to be derived to evaluate new opportunities. This requires an enterprise-wide data strategy effort to evaluate business strategies and vision, organization capabilities, process and governance, data needs, tools and technology and infrastructure.
The rapid rise of the Chief Data Officer (CDO) role, from 400 in 2014 to 1000 in 2015, has emphasized the importance of data in organizations.9 This role is now charged with establishing and championing data strategies, governance, quality, architecture, and analytics.10
Changes in international law such as EU’s General Data Protection Rights (GDPR) regulation which was adopted in 2016, have altered the data privacy laws and has business implications. It applies to all companies processing personal data of data subjects residing in the European Union. It touches upon data subject rights such as breach notification, right to access, right to be forgotten, data portability, privacy by design, and data protection officers.11 As a result, BI tools or analytics solutions that adhere to these new regulations will emerge winners.
Trend #5: The rise of Digital Ecosystems
Customer experience remains a top priority in 2016 and beyond.12 Gartner defines Customer experience as, Customer’s perceptions and related feelings caused by one-off and cumulative effect of interactions with an enterprise’s employees, channels, systems or products. A rise in the application of AI, ML and IoT is shifting the use of channels by customers at a rapid pace from human-based and web to machine-based and mobile. A new report into disruption by the Economist Intelligence Unit shows changing customer behavior is the second greatest driver by 26.4 percent of the executives.
Survey data reveals typical CIOs are already spending 18 percent of their budget to support digitalization and is expected to increase to 28 percent by 2018.13 There is a growing value connection between digital maturity and digital ecosystem participation. Businesses will continue to forge new digital relationships with their customers, employees, partners, and suppliers as they offer new services, reimagine experiences and enter new markets.
BI and Analytics is seen as a key value to digital ecosystem as it continues to Gartner the highest funding.14
To sum it up, the five trends discussed above – connected platforms, modern BI tools and technologies, Artificial Intelligence and related technologies, data management, and digital ecosystems are re-defining the business intelligence and analytics landscape in terms of technologies, organization structure and capabilities, complexity, application, data characteristics such as volume, governance, security and quality.
1. International Data Corporation (IDC)
2. Cisco Global Cloud Index: Forecast and Methodology, 2015-2020 (Whitepaper)
3. International Data Corporation (IDC)
4. International Data Corporation (IDC)
5. Report from Narrative Science, based on a survey of 235 business executives conducted by the National Business Research Institute (NBRI), sheds light on the state-of-AI in enterprises today and in the future
12. Gartner Analyst Day 2017