Companies today are keen to commit to sustainable development and a more ethical organization, two essential pillars of corporate social responsibility. At the same time, artificial intelligence is emerging as a powerful tool that is being used more and more frequently. Are CSR and AI compatible? Can we take advantage of new artificial intelligence technologies to improve our CSR policy? Answers based on four AI processes that support and help improve a CSR strategy
Process Optimization And Human Empowerment
Intelligent process automation (IPA) refers to the combination of artificial intelligence (AI) and robotic process automation (RPA). Through the use of technology, software and robots, computer systems are able to reproduce a human cognitive process. Concretely, the IPA works to simulate the most recurring and routine tasks carried out by humans, which frees them from this repetitive work.
The benefits of using IPA on CSR are numerous. First of all, freeing workers from these mechanical and time-consuming actions allows them to devote themselves to other, more fulfilling parts of the job. Activities requiring high added value can only be carried out by humans, but this more complex work is more rewarding for the teams and brings more meaning. The development of human capital is a powerful axis of CSR. People are at the heart of the company’s performance, and it is they who generate value creation.
Machines make it possible to optimize productivity and reduce processing time and the number of errors, but human labor obviously remains irreplaceable to make a business prosper. By offering its human resources activities that call more on their relevance, creativity, common sense, judgment, and ultimately all the interpersonal qualities that no AI can boast of having, the company makes them feel important—the workers.
The recognition of skills and abilities contributes significantly to a feeling of well-being at work, as does the trust granted by management. Valuing expertise and experience on a daily basis leads to employee empowerment and, ultimately, to a better quality of life at work, two essential objectives when implementing a CSR strategy.
It is possible to go further in its efforts to implement a societal policy by involving employees in participating in the development of new CSR-oriented directives within the company. Freed from their famous low-value tasks, they can reinvest the time saved in Green Opinion CSR training.
Understand the fundamentals of CSR, assimilate its issues, determine good practices, raise awareness of the environmental impact of society, and ultimately co-construct societal policy and communicate on actions, a more fulfilling form of work, in part thanks to contributions of artificial intelligence.
Analyze Data To Perform
This is one of the great strengths of artificial intelligence: its ability to analyze gigantic volumes of data. This feat is based on a branch of AI: machine learning. When you submit data (numbers, texts, graphics, images, biometric or sensory data, etc.) to an AI, it uses intelligent algorithms to process the data.
These algorithms tell the AI how to analyze information, use it, and draw conclusions. The AI learns as it assimilates data, allowing it to improve and make predictions. Transposed to the CSR field, the collection and analysis of large quantities of data is an immeasurable opportunity to draw lessons about the environmental, economic and social performance of the company.
Indeed, artificial intelligence can be used, for example, on the critical subject of energy management. Once the company’s energy consumption has been examined, the AI extrapolates concrete measures (regulation of temperature and lighting of premises, instructions to turn off devices and computers, etc.) to reduce energy expenditure and thus limit energy consumption—the company’s carbon footprint.
Depending on the company’s sector of activity, AI can also be interested in the supply chain with a view to possibly diversifying its sources to adopt more ethical practices and monitor psycho-social risks in order to prevent burn-outs, absenteeism, work atmosphere, etc.… Generally speaking, AI, by generating numerous reports on various subjects, also serves the interests of CSR if these reports are disseminated to all employees.
Indeed, one of the principles of a solid societal will is clear and transparent communication conveyed to everyone, an equal level of information, whatever the hierarchical position. This obviously also applies to CSR performance. The company, by reporting its successes and failures in this area to its stakeholders, allows them to evaluate progress and continue to support the efforts.
Finally, and this is an inexhaustible source for the company, the analysis of consumer data by artificial intelligence reveals their expectations, their needs, their concerns and their interests. If the company assimilates this statistical data well and offers a product or service adjusted to these recommendations, the entire production is optimized, with fewer losses and more sustainability.
Predictive Analysis And Risk Apprehension
Another remarkable asset of AI is its ability to predict and anticipate different scenarios. When artificial intelligence plans a plan, it bases its construction of the future on a present model; on the other hand, when it anticipates a project, it makes a hypothesis about the future.
Here, too, in terms of CSR, these abilities to develop scenarios for the future provide very relevant analyses for a company. AI is, of course, capable of predicting the environmental impacts of the company and assessing the risks involved, such as an attack on biodiversity, an increase in waste, or an explosion in the carbon footprint.
That being said, identifying and quantifying risks is the best strategy for deciding whether to circumvent or control them. Artificial intelligence is, therefore, of great help in removing or minimizing possible negative impacts. This proactive approach requires companies to implement initiatives consistent with CSR in order to address problems before they even face them.
AI can, for example, predict the consequences of a climatic event on the supply chain, which allows the company to draw up an emergency plan to deal with it and mitigate the negative impact. When it comes to societal and environmental challenges, artificial intelligence is also of great help. By analyzing the behaviors, needs and expectations of end consumers, particularly in terms of corporate social responsibility, AI allows companies to adjust their strategies in order to offer offers adapted to market trends.
Finally, the field of responsible development is still evolving, and regulations are multiplying; artificial intelligence, by monitoring the provisions in place, is also able to anticipate new directives. Here, too, early information allows better anticipation for faster compliance and an absence of sanctions.
As we have seen, artificial intelligence wonderfully identifies models and predicts trends, which is the basis for generating new ideas, in other words, innovating. Although no AI can match human creativity, the interest of AI here is to avoid suffering from prejudices or preconceived notions, unlike humans.
Thus, this avoids a form of censorship that humans could have applied and opens up a wider field of possibilities. Enter technical, regulatory constraints, ethical, environmental aspirations, etc., to be presented with new proposals combining all these aspects. AI, therefore, meets one of the objectives of CSR: innovating through the design of sustainable products or services, whether on a social, ethical or environmental level.
Another strong point, often highlighted, is that artificial intelligence can assess risks early. Of course, existing data makes it possible to identify the models that led to success but also those linked to failure; this is the responsibility of empirical analysis. What is more relevant is that AI, through modeling several scenarios, can assess the different risks that the company could face.
Vulnerability of a resource in the future, social threat, financial risk: all the impacts of an innovation are mapped, thus providing an overview and increased understanding of the potential disadvantages and advantages of a new project. Finally, and this is not insignificant, the contributions of AI significantly accelerate prototyping time.
By producing a functional model within a given time, artificial intelligence saves the company significant amounts of money. The new product is tested and adjusted quickly without generating excessive costs or waste, ideally in line with CSR recommendations.