By Satish H C, Executive Vice President, Data & Analytics and Digital, Infosys Limited
We are in a transformative era where the confluence of cloud, data, AI, and automation have driven organizational efficiencies across multiple industries. At the centre of this digital transformation is data. Data is no longer only about finding insights; it has become a pivot for enterprise transformation and digital acceleration.
AI plays a critical role in extracting the best value from data. It supports the creation of a digital ecosystem by connecting unconnected data across industries and providing actionable business insights. An AI-based data economy allows data producers and consumers to collect and share data from various sources, creating new opportunities for enterprises as they become more autonomous and cognitive-powered. A recent survey-based report published by Infosys in collaboration with MIT Technology Review Insights finds that 53% of the respondents believe that participating in a data economy has led them to create new business models.
In a modern data economy, AI-based insights will become key to creating differentiation. Enterprises will shift from legacy systems and processes to data, algorithms, and collaboration to develop competitive advantages. The ability of an enterprise to respond in real-time to market stimuli with enhanced intelligence will be critical to its success, and this ability will be deeply influenced by how it chooses to use data.
The data footprint of an enterprise will define its success in the future
Today, the adoption of ground-breaking technologies such as digital, cloud, AI, 5G, and edge computing have created a digital mesh that provides unlimited network, compute, and storage, accelerating the digital transformation of enterprises. The enterprises of the future will be defined by their data footprint in the digital mesh.
Data will start driving connections for enterprises, within and beyond. Marketplace ecosystems will begin to flourish and become the primary means for sourcing and delivery of services. These ecosystems will offer a stage for innovation and collaboration. Enterprises must discover opportunities to engage with such marketplace ecosystems to create new products and services and reimagine existing ones. Purposeful collaboration with partners and marketplace services will create new revenue streams.
For example, Telstra, a telecommunications company, plans to deliver Australia’s agricultural industry with meaningful data to improve agricultural output. It plans to use data collected from applications that monitor waste, water, air, soil, and noise and combine it with information gathered from weather stations on the climate to arrive at actionable insights such as determining pesticide usage or predicting the health of crop yields.
AI will bring the best value from data
The next phase of evolution involves gaining a level of autonomy in operations and making smarter decisions. Business processes and operations must be infused with intelligence end-to-end, using explainable algorithms and smart contracts. As AI adoption matures, algorithms will evolve to take on the functions of inference and decisions that were once the exclusive domain of humans.
Innovative AI-driven industry platforms and ecosystems will come into existence, creating new revenue streams. A case in point is Skywise, an aviation data platform developed by Airbus. It allows aircraft owners and operators to collect data – throughout its manufacturing and operational life – onto a single platform and apply AI-driven analytics to help them make informed decisions that improve aircraft operations.
Here is another example of AI-powered data and analytics enabling utilities to become carbon neutral from a supply standpoint. A cloud data analytics platform provides them with real-time insights on grid operations. To build grid resiliency programs, utilities use advanced AI/ML models to run on massive datasets to analyse, classify, and associate unstructured datasets. Detailed insights on usage and billing ensure energy efficiency.
The success of a data-based economy must be supported by sound policies on data ownership, exchange, retention, protection, and usage to ensure the data-centric structure of the enterprise is well protected. Similarly, business leaders must re-think governance to formulate and enforce policies on the ethical use of AI and algorithms to eliminate bias while providing autonomous command and control.
Summary
With the explosion of data, digital transformation will only work if systems and processes are platform-ized. As we’ve seen in the pandemic, data-rich and data-powered businesses adapted better to the new normal.
Enterprises will have to establish a symbiotic relationship with their customers, partners, community, government, and the environment at large across geographies. They will need to invest in and leverage AI to fuel data and analytics to augment business intelligence and drive further innovation and efficiencies.
