The success of a business goes beyond the concept of profitability, funding, growth rate, and brand awareness. Today, customers, employees, and other stakeholders evaluate a firm based on how its operations affect the economy, community, environment, and society. To be precise, the concern is regarding the larger good rather than just the bottom line. 

Corporate Social Responsibility (CSR), earlier, was merely considered a philanthropic activity, but with the addition of Section 135 to the Companies Act of 2013, India became the first country to make CSR mandatory for specific businesses. Many businesses seek to go beyond the legal requirements and incorporate the concept of "doing good" into their operations. However, the impact generated by CSR programmes does not always achieve its full potential. Artificial Intelligence (AI) in CSR can boost productivity and cut down on faults.

India Inc's Corporate Social Responsibility (CSR) activities will now be closely monitored by the Ministry of Corporate Affairs (MCA), which plans to employ data analytics and artificial intelligence to detect any irregularities through its new disclosure form - CSR 2, as per a story by ET. Hence, it's better for firms to tap into AI's potential.

AI can help

AI can keep an overview of the firm even in large amounts of data (big data); it can easily recognise new patterns from the existing dataset and derive actions; and can connect different data sources. Further, 

• An intelligent system can reveal patterns that are too complex for people to see, and comprehends a company's business value drivers as well as its power to provide good outcomes for a variety of stakeholders. With an understanding of key business drivers and CSR goals, it can create a programme map that can help configure and optimise the CSR activities.
• AI's capacity to handle massive amounts of data helps humans to concentrate on the finer details. Take, for example, anti-corruption investigations are time-consuming. Artificial intelligence programmes can operate as low-cost analysts for teams with limited resources and work in real-time. Citibank, for example, has invested in a machine learning platform that identifies suspicious transactions as they occur in the related field of fraud detection. 

People can be freed to scrutinise dubious contracts or payments in-depth if artificial intelligence can be utilised to augment, deepen, and accelerate normal data analysis. This may increase the number of prosecutions for corruption.

• An AI system can avoid prejudices and treat people equally in some sensitive tasks like job applications, say jobs for male or female candidates, judicial decisions, and crime policing. It is considered more a system devoid of racial or gender stereotypes. However, it depends on training data.  
• AI can identify and analyse developing trends and worldwide changes, allowing for a precise and multi-dimensional assessment of a CSR programme against global benchmarks. For instance, AI algorithms might suggest appropriate NGOs or social service activities; corporations can browse and check whether these activities correspond with their CSR goals and then choose accordingly.

Even if AI can help achieve CSR activities, CEOs, business leaders and the public sector will need to work together to make AI and other sophisticated technologies a success. One example is education and skills: while looking to improve the specific abilities of their own workforce, business leaders may assist education providers by providing a deeper grasp of the talents that will be required in the future workplace.

On the opposite end, there are instances such as a company's influence on people's emotions through information control and companies using facial recognition technology without appropriate privacy checks that have raised concerns about corporate social responsibility in recent years in the age of artificial intelligence. As a result, it's become critical to investigate how to ensure corporate social responsibility in this artificial intelligence era.