Artificial Intelligence: People, Planet, Profit

Introduction

Artificial Intelligence is a revolutionary step towards human conduct, making it one of the most transformative technologies of the century, which makes it a space in the future, fundamentally altering the way humans interact and make decisions in both personal and institutional contexts. From predictive algorithms in healthcare that assist in early disease detection, to automated systems in banking that streamline financial transactions, and even risk-assessment tools used within the criminal justice system, AI applications are redefining efficiency across sectors of critical importance. However, the integration of AI into these sensitive domains does not come without challenges. Along with the promise of speed, accuracy, and scalability, AI raises pressing ethical, legal, and social concerns. Issues such as accountability gaps, where responsibility for AI-driven decisions becomes unclear, and algorithmic biases, which can perpetuate systemic inequalities, highlight the double-edged nature of technological advancement.

AI offers unprecedented opportunities by combining speed, accuracy, and adaptability to improve efficiency, strengthen decision-making, and create new possibilities for human progress. As societies continue to integrate AI into essential systems, its role as a catalyst for transformation becomes increasingly undeniable. As AI continues to penetrate deeper into public and private life, it becomes essential to critically examine not only its benefits but also the threats it poses to fairness, transparency, and human rights.

Looking at AI through this lens, it becomes clear that while existing approaches offer some valuable insights, they also leave behind important gaps. Issues such as fragmented rules across jurisdictions, the difficulty of assigning accountability in complex AI systems, and the limits of relying only on voluntary compliance show how incomplete current governance really is. To move forward, there is a need for collaboration across disciplines and fresh, forward-looking policies that can keep pace with rapid technological change¹. The aim is not only to manage risks but also to create systems that protect public values, respect ethical principles, and still leave room for innovation. With thoughtful governance, AI can be guided in a way that benefits society while minimising the harms it might otherwise cause.

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AI And The Three Pillars: People, Planet, Profit

People

The AI thus serves as a tool changing the character of inclusion in society by widening the canvas to provide access to essential services. In matters of health, AI-based diagnostic agents aid in early diagnosis in areas where there are very few doctors. Personalised learning platforms powered by AI are also bridging educational gaps and helping students in remote areas. The language translation and accessibility tools with AI help marginalised groups, including the disabled, to share in society. Thus, AI is creating a more inclusive world by breaking down barriers of geography, literacy, and ability.

Planet

While AI aids in human development, it's also facilitating environmental sustainability. It is being used to stop deforestation, track wildlife, and optimise renewable energy usage. Climate change models infused with AI are equipped with higher precision forecast abilities, hence allowing governments and organisations to better plan their mitigation and adaptation schemes. In agriculture, AI tools help farmers use resources such as water and fertilisers efficiently, limiting waste and conserving natural ecosystems. These applications display the potential for AI to be a great partner in their joint bid to protect the planet and manage resources responsibly.

Profit

Concurrently, AI powers economic growth and sparks innovative abilities. AI is being used by startup companies around the globe to implement disruptive solutions, from fintech platforms that enhance credit access to highly skilled manufacturing systems that increase production. Large corporations are also using AI to foster efficiencies and create cost reductions while developing economically sustainable business models in line with environmental, social, and governance (ESG) goals. The profits here are not restricted to purely short-term returns, but rather increasingly go into long-term profits.

AI In Governance

Whereas AI are changing the very economic systems of the world, on the other side, AI is slowly revolutionising the operations of governments and their interactions with citizens. AI, therefore, could be a promotion tool toward governance systems that are inclusive, responsive, and citizen-centric, in view of transparency, accountability, and participation. AI-powered tools can make bureaucratic workings more efficient, identify bottlenecks to service delivery, and work toward earning public trust for institutions.

There are many governance fronts on which AI makes an impact through practice, from machine learning algorithms detecting fraud in welfare distribution schemes to smart city-level traffic management; even predictive policing works in one form or another toward crime hotspot identification. In India, however, initiatives are Aadhaar-enabled authentication services, the Digital India programme, and AI tools for grievance redressal, that is said to have greatly widened the access of citizens to government services. Assistants in the guise of chatbots are present everywhere on the government portals to enable a citizen to make applications for a subsidy, know the status of an application, and avail of healthcare information faster and more efficiently; AI also helps the judiciary in analysing backlogs of cases and providing decisive inputs. At a conceptual level, scholars highlight that AI in governance should be seen not merely as a set of tools, but as a socio-technical transformation that requires new frameworks². This perspective stresses the importance of embedding accountability, fairness, and citizen trust into AI systems from the outset. Similarly, research on resilient governance points to the need for data science reforms that ensure transparency, ethical safeguards, and equitable access, so that governments can truly harness AI for long-term stability and responsiveness³.

Despite these advances, significant challenges remain. The digital divide, unequal access to internet connectivity, digital literacy, and devices, continues to prevent vulnerable populations from benefiting equally from AI-driven governance. Ethical concerns, such as privacy violations, surveillance risks, and algorithmic biases, further complicate the landscape. If left unaddressed, these issues may reinforce inequality rather than reduce it. AI in governance represents both an opportunity and a responsibility. While it holds the promise of more transparent, accountable, and participatory governance, it also demands thoughtful regulation, ethical safeguards, and inclusive strategies. With proper frameworks in place, AI can serve as a powerful catalyst for strengthening governance and enhancing the social contract between governments and citizens.

Role of governance professionals in the AI era

As AI increasingly permeates governance and organisational decision-making, governance professionals, including company secretaries, compliance officers, and policy advisors, are uniquely positioned to guide its responsible adoption. Their role goes far beyond monitoring regulatory compliance; they act as bridges between technology, law, and society, ensuring that AI initiatives align with ethical standards, legal frameworks, and broader societal goals.

One of the key responsibilities of governance professionals is to integrate AI with ESG (Environmental, Social, and Governance) objectives. AI can help organisations optimise resource use, reduce environmental impact, and enhance social inclusivity, but without careful oversight, it could unintentionally exacerbate inequalities or create ethical risks. Governance experts can help embed sustainability and social responsibility into AI strategies, ensuring that technological progress does not come at the expense of people or the planet.

The AI era demands that governance professionals not only understand traditional compliance requirements but also possess a working knowledge of AI systems, data management, and algorithmic decision-making. By staying informed about emerging technologies and their implications, these professionals can anticipate potential risks, develop effective monitoring frameworks, and design policies that safeguard organisational integrity and public trust.

Governance professionals also play a crucial role in shaping organisational culture around AI adoption. They ensure that ethical considerations, transparency, and accountability are integrated into decision-making processes. For example, when AI systems are deployed in human resources, financial operations, or public service delivery, governance experts can establish checks and balances to prevent bias, protect data privacy, and maintain fairness. Their involvement ensures that AI tools are not just efficient but also socially responsible and legally compliant.

Governance professionals act as advisors to policymakers and regulatory bodies, bridging the gap between technological innovation and legal frameworks⁴. By providing insights on AI's operational, ethical, and societal implications, they help craft policies and guidelines that promote innovation while protecting public interest. In doing so, they become pivotal actors in building a governance ecosystem where AI can flourish responsibly, contributing to inclusive growth, sustainable development, and ethical organisational practices.

Governance professionals are the custodians of responsible AI. Their proactive engagement ensures that AI serves humanity's collective interests, enhancing transparency, accountability, and sustainability while enabling organisations and governments to harness its transformative potential effectively.

Research gaps: AI is still reshaping governance fundamentally

AI's role in government is growing fast, but most studies have been about making things more efficient, improving services, and boosting the economy. There's not much talk about how AI's changing the game in governance, like how it's shaking up the way decisions are made, policies are crafted, rules are set, and how folks get involved over time. getting the hang of these deeper changes is key because governance isn't just about services; it's about the rules, processes, and institutions that make up our societies. There's a big gap when it comes to the ethical and legal stuff. Even though AI is getting used for public services and making decisions, there's not much research on making sure it's fair, clear, and accountable when it's used a lot. There's still a lot to figure out about who's responsible when AI messes up, how to keep our privacy safe, and how to stop AI from being unfair, and that's leaving our leaders kind of in the dark about what

One key gap lies in ethical and legal implications. Although AI tools are being deployed for public service delivery and decision-making, there is limited research on ensuring fairness, transparency, and accountability at scale. Questions around liability when AI makes errors, the protection of citizen privacy, and mitigating algorithmic bias are still underexplored, leaving governments vulnerable to unintended consequences. In this context, after the development of this type of event, where AI, governments, and the data collection capacity of corporations are questioned, essential questions regarding the knowledge, authority, and power of government use of BDS techniques should be explored⁵. But there are also a number of unresolved issues, like how reliable is user behaviour prediction? To whom does this behavioural data pertain? To the best of our knowledge, no prior study had recognised and detailed the hazards of governmental adoption of AI to citizens' privacy, as indicated by the privacy concerns mentioned above and the uniqueness of the study supported by the BDS's new developing concept. No studies have connected the idea of BDS to the primary applications of AI by governments. Therefore, using the new BDS conceptual framework, we want to close a gap in the literature by investigating the potential applications and privacy risks of governments implementing AI in their plans.

Another area in need of attention is the integration of AI with existing governance structures. Many systems are designed to work within traditional bureaucratic frameworks, and research is limited on how AI interacts with hierarchical decision-making, inter-agency coordination, and policy compliance. This can create friction, inefficiencies, or even systemic blind spots if not carefully studied.

There is a lack of interdisciplinary research examining the socio-cultural impact of AI on governance. How do citizens perceive AI-driven decisions? Does reliance on automated systems affect trust in public institutions? How do digital divides influence inclusivity and participation? These human-centred questions are critical to designing AI systems that not only perform tasks efficiently but also resonate with the public they are meant to serve. The automation of labour, modifications to medical and educational procedures, and the effects on social and cultural ties were the primary factors influencing how artificial intelligence affected contemporary sociocultural processes. This gave insight into how the advancement of artificial intelligence is causing changes in the workplace, such as the automation of repetitive tasks and the implications for employment and the labour market⁶.

Finally, the role of governance professionals in harnessing AI responsibly remains underexplored. Company secretaries, policy advisors, and regulatory experts can play a pivotal role in embedding ethical standards, compliance measures, and ESG principles into AI initiatives. However, research on their strategies, best practices, and capacity-building needs is limited, leaving a gap between technological potential and practical implementation. Deep learning algorithms are a class of neural networks designed to tackle complex problems by learning patterns from large datasets, often with minimal guidance from human programmers. A neural network functions by processing input data through interconnected layers of nodes, each of which applies a set of weights and thresholds to transform the inputs into predicted outputs. The network then evaluates how close these predictions are to actual results and adjusts the weights accordingly, gradually improving its accuracy over time. This iterative process allows neural networks to "learn" from data, enabling them to make increasingly precise predictions and uncover patterns that may not be immediately apparent to humans.

AI's changing the game for how things get done in government, but we're still figuring out the big picture, like how it affects our systems, moral compass, and people's faith in the system. Having a handle on these research gaps is key to making governance systems that work well and are fair, responsible, and tough enough to handle the AI stuff. Beyond individual applications, AI has the potential to create solutions that simultaneously benefit people, the planet, and profit. For instance, in agriculture, AI-powered precision farming can optimise crop yields, reduce the use of water and fertilisers, and support farmers' livelihoods. This not only improves economic outcomes (profit) but also conserves natural resources (planet) and enhances food security and income for rural communities (people). Similarly, in healthcare, AI-driven predictive analytics can identify disease outbreaks early, allowing governments to allocate resources efficiently. This protects public health (people), reduces wastage of medical supplies (profit), and minimises environmental strain from overuse of pharmaceuticals and energy-intensive treatments (planet).

AI also fosters innovation in sustainable business models. Startups and corporations increasingly use AI to monitor supply chains, minimise waste, and improve energy efficiency, linking economic growth with environmental stewardship. Moreover, AI tools designed for inclusive education, skill development, and accessibility enhance social equity, ensuring that technological progress does not leave behind marginalised groups. Ethical AI practices, regulatory oversight, and upskilled governance professionals are necessary to ensure that AI's transformative potential is realised equitably, sustainably, and profitably, truly reflecting the principles of People, Planet, and Profit.

Conclusion

Artificial Intelligence is more than just a technological innovation; it is a transformative force that has the potential to shape a future where people, the planet, and profit coexist in harmony. By enhancing access to education, healthcare, and essential services, AI is creating opportunities for inclusivity and social equity. At the same time, its applications in environmental monitoring, sustainable resource management, and climate change mitigation highlight its ability to protect and preserve our planet. Meanwhile, AI continues to drive economic growth and innovation, enabling organisations and startups to develop solutions that are not only profitable but also sustainable in the long term.

Governance emerges as a critical enabler in this AI-driven landscape. Transparent, accountable, and participatory governance frameworks, supported by informed professionals, can ensure that AI delivers societal benefits while mitigating ethical, legal, and social risks. Yet, as research gaps remain, particularly in understanding AI's systemic impact on governance, its socio-cultural implications, and the strategies for responsible integration, there is a clear need for ongoing study, interdisciplinary collaboration, and proactive policy-making.

Thus, realising AI's full potential requires a collaborative approach: governments, organisations, researchers, and governance professionals must work together to design frameworks that align innovation with ethical standards and public interest. By doing so, AI can become a catalyst for inclusive development, sustainable environmental stewardship, and economic progress, truly embodying the principles of People, Planet, and Profit.

Footnotes

1 Ghosh, A., Saini, A. & Barad, H. Artificial intelligence in governance: recent trends, risks, challenges, innovative frameworks and future directions. AI & Soc (2025). https://doi.org/10.1007/s00146-025-02312-y.

2 Straub VJ, Morgan D, Bright J, Margetts H (2023) Artificial intelligence in government: concepts, standards, and a unified framework. Gov Inf Q 40(4):101881

3 B.D. MacArthur et al. Resilient government requires data science reform Nature Human Behaviour (2022)

4 Pulijala S (2024) Artificial intelligence in governance: opportunities, challenges, and ethical implications for public administration. Int J Multidiscip Res.

5 Saura JR, Ribeiro-Soriano D, Palacios-Marqués D (2022) Assessing behavioral data science privacy issues in government artificial intelligence deployment. Gov Inf Q 39(4):101679

6 Abulkassova, D., Muldasheva, G., Nurtazin, M. et al. The phenomenon of artificial intelligence in modern transformational socio-cultural processes: Socio-philosophical analysis. AI & Soc 40, 4283–4293 (2025). https://doi.org/10.1007/s00146-025-02195-z.

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