Managing AI's Social Impact: Responsible Business Use
Managing AI's Social Impact: Responsible Business Use
Understanding AI’s impact on society
June 2026
Artificial intelligence is often discussed in terms of productivity gains, efficiency improvements and technological innovation. Yet behind every AI system are people whose jobs, opportunities, experiences and rights may be affected by the way the technology is designed and deployed.
As organisations increasingly integrate AI into their operations, attention is turning to a critical question: how can businesses harness the benefits of AI while ensuring positive outcomes for employees, customers and wider society? This question sits at the heart of the social pillar of ESG, which focuses on how organisations manage their impact on people and communities.
From workforce transformation and skills development to fairness, inclusion and data privacy, AI presents both opportunities and challenges. As adoption accelerates, understanding these social implications is becoming an increasingly important part of responsible and sustainable AI use.
WHY AI'S SOCIAL IMPACT IS A GROWING ESG CONSIDERATION
The social pillar of ESG focuses on how organisations manage their relationships with employees, customers, suppliers and communities. Traditionally, this has included issues such as workforce wellbeing, diversity and inclusion, human rights, customer protection and community engagement.
AI has the potential to influence all of these areas, and unlike many other technologies, AI is increasingly being used to support decisions that affect people directly. Whether helping to screen job applicants, personalise customer experiences, identify training needs or automate workplace processes, AI systems can shape opportunities, experiences and outcomes in ways that are not always immediately visible.
As AI adoption accelerates, organisations are facing growing expectations from employees, customers, investors and regulators to look beyond efficiency gains and consider the wider social implications of the technology. This includes understanding both the risks that need to be managed and the opportunities that can be realised when AI is used responsibly.
AI AND THE FUTURE OF WORK
Perhaps the most widely discussed social impact of AI is its effect on employment and the workforce. AI can automate certain tasks that have traditionally been carried out by people, particularly those involving routine administration, information processing or repetitive activities. At the same time, it can enhance productivity, support decision-making and create entirely new roles and skill requirements.
According to the World Economic Forum's Future of Jobs Report 2025, technological change, including AI, is expected to result in significant labour market shifts over the coming years. While some roles may decline, new opportunities are also expected to emerge, particularly in technology, data, sustainability and human-centred professions (World Economic Forum, 2025).
While technological change has historically created new opportunities alongside disruption, concerns about job displacement remain significant. Public expectations also reflect this concern. According to the 2025 Impact Monitor Report by SEC Newgate, 71% of people surveyed believe businesses should only utilise AI in their operations if it does not make existing employees redundant (SEC Newgate, 2025).
This highlights the importance of transparency and workforce engagement when implementing AI. Employees and stakeholders are often more receptive to AI adoption when it is positioned as a tool to support people and enhance productivity, rather than simply reduce headcount. For organisations, this reinforces the importance of preparing employees for change rather than simply focusing on automation. Investment in training, upskilling and reskilling can help employees adapt to evolving roles while enabling organisations to maximise the benefits of AI adoption. Increasingly, investors, customers and employees are paying attention not only to whether organisations are adopting AI, but how they are managing its impact on people.
Businesses that actively support workforce development are likely to be better positioned to maintain employee engagement, attract talent and demonstrate strong social responsibility credentials.
FAIRNESS, BIAS AND INCLUSION
AI systems learn from the data on which they are trained. If that data reflects historical biases or inequalities, AI models can unintentionally reproduce or amplify them. This has become a growing concern in areas such as recruitment, lending, insurance, healthcare and performance assessment, where AI-supported decisions may have a direct and lasting impact on people's lives. Several well-publicised examples have highlighted the risks of biased AI systems producing unfair outcomes, one such being an experimental AI recruitment tool that was found to disadvantage female applicants because it had been trained on historical recruitment data that reflected existing gender imbalances in the workforce (MIT Technology Review, 2018).
In response, organisations are increasingly implementing measures to test models for bias, to review decision-making processes and to maintain appropriate human oversight (OECD, 2019; UNESCO, 2021).
Responsible AI deployment requires organisations to think carefully about fairness, inclusion and equal opportunity. This may involve assessing training data, regularly monitoring outputs and ensuring diverse perspectives are considered throughout the design and implementation process. From an ESG perspective, addressing these biases is closely linked to broader commitments around diversity, equity and inclusion in the workplace.
DATA PRIVACY AND CONSUMER TRUST
Many AI systems rely on large volumes of data to operate effectively. This can create valuable opportunities for organisations to improve services, gain insights and enhance customer experiences. However, it also raises important questions around privacy, transparency and data protection.
Customers increasingly expect organisations to handle their information responsibly and to be transparent about how data is collected, stored and used (OECD, 2019). Maintaining trust is particularly important as AI tools become more sophisticated and integrated into customer-facing processes, and organisations that are clear about how AI is used, what data is involved and what safeguards are in place are more likely to build confidence among customers and stakeholders. Strong data governance, cybersecurity measures and compliance with relevant regulations remain essential components of responsible AI adoption.
ACCESSIBILITY AND SOCIAL OPPORTUNITY
While much attention is often given to the risks associated with AI, it is equally important to recognise the opportunities it can create. One such example is AI-powered tools being used to help improve accessibility through technologies including speech recognition, real-time translation, captioning and image description. These innovations can help remove barriers and improve access to information, communication and services (UNESCO, 2021).
AI is also being used to support education, healthcare and public services by enabling more personalised and responsive experiences. When designed thoughtfully and deployed responsibly, AI has the potential to increase inclusion and expand access to opportunities for groups that may previously have been underserved.
PRACTICAL STEPS FOR ORGANISATIONS USING AI
As with environmental impacts, organisations do not need to have all the answers before they begin taking a responsible approach to AI's social implications. Practical steps may include:
Assess how AI is being used across the organisation: Understand where AI tools are being applied and whether they influence decisions affecting employees, customers or other stakeholders.
Consider workforce impacts: Identify how AI may change job roles and explore opportunities for training, reskilling and employee engagement.
Maintain human oversight: AI should support human judgement rather than replace accountability for important decisions. Companies can take a human-in-the-loop approach to maintain accuracy and accountability when using AI. This is where humans remain actively involved in the use of AI, from development to deployment and decision-making, rather than allowing AI systems to function totally autonomously.
Review fairness and inclusion risks: Where AI supports decision-making, consider whether appropriate checks do or should exist to identify and address potential bias.
Strengthen data governance practices: Ensure employees understand expectations around privacy, confidentiality and responsible use of information.
Develop an AI policy: As AI use becomes more widespread, employees may begin using tools independently without clear oversight or understanding of the associated risks. An effective AI policy can provide guidance on approved tools, acceptable use, data privacy, confidentiality, copyright considerations, quality assurance and human review requirements. It should also clarify where AI can support decision-making and where human judgement remains essential. A clear policy helps organisations promote consistent, responsible AI use while reducing legal, operational and reputational risks.
Document your approach: Recording how social impacts have been considered and how you intend to consider them into the future demonstrates accountability and supports future ESG reporting and stakeholder engagement.
THE BIGGER OPPORTUNITY
As organisations explore the social implications of AI, it can be tempting to focus solely on managing risks. However, the organisations likely to realise the greatest value from AI may be those that view it not simply as a technology initiative, but as an opportunity to strengthen relationships with employees, customers and other stakeholders.
The way organisations introduce and govern AI can send important signals about their values and priorities. Businesses that engage openly with employees, invest in skills development and place human wellbeing at the centre of decision-making are more likely to build trust and support during periods of change. In contrast, organisations that prioritise efficiency gains without considering wider social impacts may face greater resistance from employees, customers and other stakeholders.
Research from the International Labour Organization suggests that the future impact of AI will depend significantly on how organisations choose to implement it, with outcomes ranging from enhanced job quality and productivity to increased workforce disruption if change is poorly managed (ILO, 2023). Beyond the workforce, responsible AI practices can also help strengthen customer confidence, support inclusion and demonstrate a commitment to ethical business conduct. As stakeholder expectations continue to evolve, organisations are increasingly being judged not only on what technologies they adopt, but on how they use them.
Ultimately, the social dimension of AI is about more than managing potential harms. It is about ensuring that technological progress contributes positively to people, communities and organisations alike. Those businesses that successfully balance innovation with responsibility are likely to be better positioned to attract talent, build trust and create long-term social value.
HOW ESGMARK® CAN HELP
At ESGmark® we help organisations to credibly demonstrate and improve their Environmental, Social and Governance (ESG) credentials. We do this through ESGmark® Certification (visit page), carbon footprint measurement (visit page), and sustainability support. Speak to our friendly team to get started today by contacting us.
EXPLORE MORE: ESG & AI
This is the third blog in our series looking at how AI use links to Environmental, Social, and Governance (ESG) areas, and the considerations companies can take to use it responsibly.
Head to our other articles to explore more on this topic:
Understanding AI and its Environmental Implications (link here)
Understanding responsible AI governance: Building trust, transparency and accountability (link here)
Sources
Deloitte (2025) Global C-suite Sustainability Report. Available at: https://www.deloitte.com
International Labour Organization (2023) Generative AI and Jobs: A Global Analysis of Potential Effects on Job Quantity and Quality. Available at: https://www.ilo.org
MIT Technology Review (2018) Amazon ditched AI recruitment software because it was biased against women. Available at: https://www.technologyreview.com/2018/10/10/139858/amazon-ditched-ai-recruitment-software-because-it-was-biased-against-women/
OECD (2019) OECD Principles on Artificial Intelligence. Available at: https://oecd.ai
SEC Newgate (2025) Impact Monitor Reports: Global Impact report 2025. Available at: https://secnewgate.com/impact-monitor/reports/global-report-2025/
UNESCO (2021) Recommendation on the Ethics of Artificial Intelligence. Available at: https://www.unesco.org
World Economic Forum (2025) Future of Jobs Report 2025. Available at: https://www.weforum.org