Ever since its existence, technology has been creating a positive impact on the socio-economic wellbeing of every community. For instance, the advent of technology has increased leisure or improved longevity. By expanding the theories of welfare economics, the McKinsey team simulated how technology would function across the economy. In their research, they found that the digital tycoons who reap the biggest benefits of technology are those who focus on new products and markets. And as a result, they are more likely to increase or stabilize their workforce than reduce it. At the same time, human capital is also an essential component of their strategies.  

With the introduction of technology, a new age of CSR has begun. Prof. Al Naqvi of the American Institute of Artificial Intelligence calls it the “intelligence age”. The corresponding stage according to him is the ‘cognitive era’, where the machines are deployed to transform and improve the process of CSR. CSR is a business process at its core, which needs improvement in its efficiency and effectiveness. This orientation to make CSR more effective forms the foundation of Cognitive CSR. Even though the intentions of CSR are well, there are several criticisms raised against it. Some of the major criticisms raised against CSR are divided into 3 broad categories and listed below:  

1. Measurement: Problems constantly arise when enterprises fail to measure or measure the wrong or irrelevant thing. Debates exist on how value is measured, what should be included and whether CSR creates or burdens shareholder value.  
2. Behavioral: This refers to management behavior that limits the CSR programs in achieving their full potential. They at times undermine the success or positive impacts of the programs.  
3. Strategic and organizational: This represents the inability to properly integrate CSR into business strategy or vice versa. It is the result of negligence or incompetence.  

Overcoming challenges in CSR using AI  

The emergence of AI has been creating an impact in the business world- from sales to marketing and finance supply chain. The AI technology is deployed in a strategic and integrated manner to radically improve the CSR process. An intelligence system can understand the components that drive the business value of a firm and can generate positive results for multiple stakeholders. It recommends a program strategy and keeps the management honest. By consciously evaluating the drivers of the business and CSR goals, it formulates a plan that can help configure and optimize the CSR program.  

When AI technology is used in CSR, it can eliminate the possibilities of any bias evolving due to human perceptions. An AI system can provide accurate and multi-dimensional performance measures that can measure the performance of a particular program in regulatory and global standards. For this, the system will monitor and track emerging global changes. AI can identify incentive misalignment, bias in the management, insincerity and other management issues. Companies make use of AI in fraud detection and improving internal controls. It can also aid in the identification of the integration points of corporate strategy and CSR.   

McKinsey had developed a concept called TSR- Technological Social Responsibility. According to them, TSR is an alignment between short and long-term business goals and long-term societal ones. By parallelly working on societal and business interests, they have found through their research that the adoption of technology can increase productivity and economic growth powerfully.  

 Developing an AI-based CSR strategy  

 The long process of developing an AI-based CSR strategy can be explained in four points:  

1. Business plan: The initial step is to create a formal business plan for CSR. While creating the plan it is important to recognize that it is a fast-emerging and complex field. Many consulting firms have only a little knowledge of this area.  
2. Building architecture: It is important to think holistically about full-scale automation and interdependent technologies. A cognitive architecture will include various capabilities such as data management, big data, machine learning and the use of various AI artefacts and capabilities.  
3. Use of AI in clerical processes: Using AI in data-entry type processes can give quick success and can be the starting point of transformation.  
4. Training and participation of departments: It is important to engage and bring other departments to develop the transformation. Also, traditional tech departments which do not process AI skills should not be relied on. Either they should be well trained in the AI algorithms or a new tech team should be set up.  

Machine Learning as a subfield of AI, is helping to create machines that can learn and accumulate experience. Analyzing the impact of AI in the corporate world, it is clear that in the age of AI, CSR will find its zenith.