Artificial intelligence (AI)

Simply put, Artificial intelligence (AI) is intelligence demonstrated by machines. We can define AI as “a system’s ability to correctly interpret external data, to learn from such data, and to use those learning’s to achieve specific goals and tasks through flexible adaptation”. Artificial intelligence is a science and technology based on disciplines such as Computer Science, Biology, Psychology, Linguistics, Mathematics, Engineering, etc. Goal of AI is to create expert systems, which exhibit intelligent behavior, learn, understand, think, behave, explain, and advice its users like humans.

Economies stand to benefit from AI, through increased productivity and innovation. Deployment of AI and automation technologies can do much to lift the global economy and increase global prosperity. At a time of aging and falling birth rates, productivity growth becomes critical for long-term economic growth. AI can also boost innovation, enabling companies to improve their top line by reaching underserved markets more effectively with existing products, and over the longer term, creating entirely new products and services.

One McKinsey survey suggests that AI adoption could raise global GDP by as much as $13 trillion by 2030, about 1.2 percent additional GDP growth per year. Artificial intelligence (AI) is disrupting diverse industries. Banking, for example, is projected to benefit the most out of incorporating AI systems in the next couple of years. Analysts estimate that AI will save the banking industry more than $1 trillion by 2030.

AI is being used to develop and advance numerous fields and industries, including finance, healthcare, education, transportation, agriculture, marketing and more. While AI is increasingly pervasive in consumer applications, businesses are beginning to adopt it across their operations, at times with striking results. AI can be used to improve business performance in areas including predictive maintenance, where deep learning’s ability to analyze large amounts of high-dimensional data from audio and images can effectively detect anomalies in factory assembly lines or aircraft engines. In logistics, AI can optimize routing of delivery traffic, improving fuel efficiency and reducing delivery times. In customer service management, AI has become a valuable tool in call centers, thanks to improved speech recognition. In sales, combining customer demographic and past transaction data with social media monitoring can help generate individualized “next product to buy” recommendations, which many retailers now use routinely.

Although many organizations have begun to adopt AI, the pace and extent of adoption has been uneven. Many companies and sectors lag in AI adoption. Developing an AI strategy with clearly defined benefits, finding talent with the appropriate skill sets, overcoming functional silos that constrain end-to-end deployment, and lacking ownership and commitment to AI on the part of leaders are among the barriers to adoption most often cited by executives. On the strategy side, companies will need to develop an enterprise-wide view of compelling AI opportunities, potentially transforming parts of their current business processes. Organizations will need robust data capture and governance processes as well as modern digital capabilities, and be able to build or access the requisite infrastructure.

The implementation of artificial intelligence or machine learning is making people’s lives simpler and smarter. But workers will need different skills to thrive in the workplace of the future. Certain categories of activities are technically more easily automatable than others. About half of current work activities (not jobs) are technically automatable. They include physical activities in highly predictable and structured environments, as well as data collection and data processing, which together account for roughly half of the activities that people do across all sectors in most economies. The least susceptible categories include managing others, providing expertise, and interfacing with stakeholders. Workplaces and workflows will change as more people work alongside machines.

AI is all about continuous learning and re-learning of patterns, data, and development. AI has the flexibility to build upon the current system of the industry and thus there is no need to start from scratch, but can easily keep improvising the system in place gradually. Over time, AI is not only going to revolutionize businesses & industries but become the industry itself. But in the meantime, AI will need to address societal concerns including unintended consequences, misuse, and questions about data privacy. We are certainly living in exciting times.