Future adoption of CI will require expertise in predictive analytics and AI. The anticipate explosive growth in the adoption of predictive analytics will give businesses the experience with such sophisticated analytics methods.
Continuous Intelligence (CI) enables smarter business decisions using real-time data streams and advanced analytics. It differs from traditional analysis in that it is always on for situational awareness, prescribes actions, and allows businesses to be proactive.
In most cases, CI makes use of artificial intelligence (AI) and machine learning (ML) to complement traditional analytics used to investigate streaming datasets. Businesses can realize significant benefits from CI when their real-time analytics capabilities are integrated into their operations. In this way, CI can prescribe actions in response to business moments and other events.
Not all businesses have a need for CI today, but many will in the near future. By 2022, more than half of major new business systems will incorporate CI that uses real-time context data to improve decisions, according to Gartner.
One thing that will hold businesses back in their CI adoption is a lack of expertise in using sophisticated analytics. The reality is that many businesses are still using spreadsheets and descriptive analytics solutions to look for trends and anomalies in their data. If in the future, these companies need Ci, they will need to use sophisticated analytics, typically predictive analytics and AI.
AI has come a long way in the past five years, as new frameworks, platforms, and providers have launched to help businesses deploy successfully. However, there is still a lack of understanding of AI’s benefits, which AI to choose, and whether it’s necessary at all. In fact, companies deploying AI are seeing lots of challenges as they struggle to integrate it properly into their operations.
Predictive Analytics Boom
The situation with predictive analytics is more promising. The worldwide predictive analytics market is expected to grow at a compound annual growth rate (CAGR) of around 20.8% through 2026, reaching a market value of around $25.2 billion in 2026, according to Acumen Research and Consulting.
The firm’s recently published report, “Predictive Analytics Market Size, Share, Growth Opportunity, Trends and Forecast, 2019-2026,” identified regional and industry predictive analytics usage trends. Some of their findings include:
The U.S. market is seeing a high adoption of advanced technology and greater penetration of predictive analytics in multiple industries such as government; banking, financial services, and insurance (BFSI); and e-commerce.
Asia Pacific is anticipated to observe the fastest growth in the adoption of predictive analytics during the next seven years. According to a release highlighting the report, increasing awareness about predictive solutions and their advantages will lead to growth in the deployment of predictive analytics solutions in the region in the coming years. Furthermore, investment by service providers and the growing adoption of emerging technologies such as ML and AI also are contributing to the growth of this region in the predictive analytics field.
The predictive analytics market is divided into financial analytics, customer analytics, network analytics, marketing and sales analytics, supply chain analytics, risk analytics, web and social media analytics, and others. In 2018, risk analytics accounted for the largest share of the market. This can be attributed to the presence of solutions for a wide range of industries and greater adoption by these industries to identify upcoming risks and risk mitigation measures. However, the customer analytics segment is expected to observe the fastest growth in the coming years. Customer analytics are the solutions that are used by companies to understand customer behavior. This helps organizations to retain existing customers and attract new customers by focusing on their needs. In many scenarios, CI will play a role in customer analytics.
In 2018, large enterprises accounted for the largest share of the market due to greater adoption of these enterprises. However, in the coming years small and medium-size enterprises segment is projected to witness the fastest growth. These enterprises need predictive analytics solutions to enhance their operational performance and to reduce overall cost. Hence, the growing adoption of these solutions is anticipated to observe the fastest growth.
Based on the end-use, the global predictive analytics market is further divided into BFSI, healthcare, IT &telecommunication, media and entertainment, automotive and transportation, aerospace and defense, and others. The BFSI segment accounted for the largest share in 2018, and the retail and e-commerce segment is estimated to observe the fastest growth during the forecast period. Again, CI can play a significant role in all these segments.
Future adoption of CI will require expertise in predictive analytics and AI. The anticipate explosive growth in the adoption of predictive analytics will give businesses the experience with such sophisticated analytics methods. This expertise can then be applied when CI initiatives are undertaken.
On the AI front, the growth in easy to use AI and cognitive services and solutions should give businesses an entry point into using AI. That experience can then be applied to CI efforts.