Emerging Trends: Artificial Intelligence for data economy

According to a survey[1] of 1200 companies across the globe, more than 60% of data service providers believe that Artificial Intelligence (AI) is the future of their business. And quite rightly so, given that the growth of AI to unlock the value of data is set to increase with a Compound Annual Growth Rate (CAGR) of 49.8% over the next five years alone[2]. Let us dive deeper into why that is.

Internet of Things & 5G

The idea of having all our devices connected and communicating with each other over a network, an Internet of Things (IoT), has already materialized into a reality. From smart phones and light bulbs to autonomous cars, everything is now part of the IoT. And it is not just IoT in smart homes, but entire regions which are now filled with devices and sensors to constitute smart cities.

5G will eventually increase the number of IoT connected devices by tenfold to a staggering 10 million devices per sq. km, which will generate significant volume of data.

Digital Twins

All devices in the IoT can be leveraged under the concept of Digital Twins.

Simply put, a Digital Twin is a digital representation of a physical object or system which is constructed to receive input from sensors to gather data from the real-world counterpart. Due to the availability of significantly high volumes of data (via wired or wireless communication), establishing Digital Twin of a dynamic object or systems is gaining popularity to remotely monitor, control and support informed decision making.

In a similar way, data from sensors and devices in the IoT can be used to create a digital version of the system for a wide range of tasks including fault prediction, predictive maintenance, and creation of new scenarios, which make business processes more efficient.

Edge AI

The processing of data to extract insights can be done either on the cloud server or on the devices themselves (i.e. on edge). Most of this processing is currently being done on the cloud, which means that data must be processed and transferred to a cloud server. This leads to data privacy issues as well as issues regarding the latency (time to establish a connection) and consumption of resources for data exchanges.

To solve this issue, AI is being transferred to the edge devices where data is processed in real-time without data transfer delays and privacy concerns. We can already see this being implemented in wearable technologies with which we interact and receive recommendations to monitor our health.

What does this mean for the digital industries?

The success of data driven digital transformation depends on three key areas, where AI can act as an accelerator to drive change with respect to each of these.

Key Area One: Resource Optimization

Productivity growth in the industry depends on two major parameters – reducing operating costs and improving performance in all business areas. This includes operational resource planning and optimization of human resources, accounting and fraud management, where accurate knowledge and prediction can make a significant difference in decision making.

With the influx of data available in these areas, AI can help achieve that progress in several ways:

• Monitoring of processes real-time and predicting possible failures or unexpected behaviour before they occur, thereby reducing delays due to process or production shutdown
• By using Digital Twins and virtual simulations for the respective industries, it is possible to search through maintenance routes or placements for boosters to find the optimal routes and placements depending on a variety of different factors
• Fraud Detection using customer billing information and finances can help accept or reject applications on the spot

Key Area Two: Sales & Marketing

All historical data can also be used to predict demand based factors such as time of day or seasonal trends. This can then be used to offer the most appropriate packages to customers.

Key Area Three: Customer Satisfaction

Enhancing customer experience is a key priority for any business. This can be facilitated with the use of primary data (e.g. via surveys) and secondary data (e.g. via government publications, websites, internal records).

AI can act as an accelerator to provide data-driven insights and support decision making.

In the Long Term

In the long term, AI can help a new generation of small and medium size businesses grow where ‘data harvesting ‘is part of their primary business activity. This will help unlock new revenue streams such as Data-as-a-Service or Decision-as-a-Service.

The SOLVD Project

The SOLVD project supports Telford & Wrekin and Shropshire businesses with the adoption of digital technologies to improve productivity and profit. Experts from the SOLVD team at the University of Wolverhampton can help you explore this potential; for further information please contact SOLVD@wlv.ac.uk or visit wlv.ac.uk/SOLVD to find out how digital technologies can help your business.

Blog by Fahad Zia –  Research and Innovation Graduate at The University of Wolverhampton

[1] Driving ROI Through AI (https://pages.dataiku.com/driving-roi-through-ai)

[2] Global AI in Telecom (https://reports.valuates.com/request/sample/QYRE-Auto-7L853/Global_AI_In_Telecommunication_Market_Size_Status_and_Forecast_2020_2026)