This article first appeared in Forum, The Edge Malaysia Weekly on July 21, 2025 - July 27, 2025

The artificial intelligence (AI) revolution presents a critical dilemma: How do businesses leverage its immense power to drive profitability without compromising environmental responsibility and ethical integrity? The solution lies in consciously integrating AI as a twin-turbo engine, simultaneously accelerating financial growth and advancing sustainability goals, while meticulously managing its inherent trade-offs.

Everyone is talking about AI’s transformative potential for automation, optimisation and personalisation. But fewer are addressing what it is actually like to implement this game-changing technology in real-world businesses, or how to navigate the tension between the profit and purpose it creates.

Inside boardrooms, the promise is seductive: AI drives efficiency, accelerates growth, and supports environmental, social and governance (ESG) goals — all in one. But beneath the glossy decks and headlines lies a more nuanced truth. AI is indeed a twin-turbo engine for business success, supercharging profits and accelerating sustainability. Yet, the road to these rewards is not without its bumps. For every breakthrough, there’s a trade-off. Greater efficiency often comes at an environmental cost. AI can uncover data insights for more inclusive customer experiences, but it also raises questions of fairness and ethics.

So, once the strategy is approved and the systems are deployed, what then? How do organisations keep both engines — profit and purpose — running smoothly without burning out the system, or the planet?

The first engine of the AI advantage is squarely focused on profit, encompassing efficiency, productivity and growth. AI is redefining traditional metrics, automating time-consuming tasks and streamlining operations with impressive results.

Consider Maersk, the global logistics giant. By using AI-driven optimisation tools to refine routing and fuel consumption across its shipping fleet, Maersk achieved a remarkable 9.2% reduction in fuel use per container. This not only boosted efficiency but also significantly slashed Maersk’s carbon footprint.

Such AI-powered operational improvements are the very backbone of profitability. For every dollar invested in AI, companies are reportedly seeing returns as high as US$3.50. AI frees employees from mundane, repetitive tasks, saving them an average of 2½ hours a day — time that can be redirected towards higher value work.

However, challenges inevitably arise. While the savings and efficiency gains are clear, leaders often encounter unforeseen complexities in enterprise-wide AI implementation. Maersk’s fuel optimisation, for instance, demanded not just a technological shift but a complete cultural overhaul. Employees needed retraining, workflows had to be adjusted and expectations realigned. As one regional e-commerce chief operating officer aptly put it, “We saved 40% in customer service time, but the cultural adjustment to new AI systems was tougher than expected.”

The bottom line? AI is a productivity powerhouse, but businesses must proactively plan for the human and cultural factors that accompany it.

AI isn’t just about efficiency; it is a powerful growth engine. Its ability to analyse vast data sets at lightning speed uncovers previously hidden insights. This helps businesses stay ahead of market trends, deeply understand consumer behaviour, and create hyper-personalised customer experiences.

Hyundai Mobis, for example, leveraged AI in its manufacturing operations to detect defects before they even occurred, dramatically reducing waste and inefficiency. By deploying AI-powered defect detection, Hyundai Mobis slashed manufacturing waste by 28%, saving raw materials and significantly reducing its carbon emissions.

Beyond efficiency and quality control, AI fuels innovation by helping companies reimagine customer engagement. In retail, AI-powered chatbots are boosting conversion rates by as much as 15%. Businesses that strategically leverage AI in research and development can accelerate product development, reduce time-to-market and make smarter investments.

Yet, the biggest hurdle here is integration. AI’s insights are only valuable if businesses can act on them swiftly. Maersk’s fuel optimisation models delivered incredible results, but only because the company had the infrastructure to rapidly deploy those insights. Without the right tech ecosystem, AI can sometimes provide powerful data that simply fails to translate into immediate action. As a chief information officer from a global consumer goods company lamented, “The models gave us fantastic insights, but our legacy systems couldn’t execute at the speed we needed.”

The second engine of AI’s immense potential lies in its power to accelerate ESG outcomes. Whether it is cutting carbon emissions, enhancing transparency or ensuring ethical supply chains, AI has become a critical enabler of sustainability — especially in tackling the climate crisis.

Maersk’s use of AI for fuel optimisation is a prime example. By harnessing AI to understand and predict fuel consumption patterns across its global fleet, Maersk has made significant strides in reducing emissions. The 9.2% reduction in fuel usage not only directly lowers operational costs but also shrinks Maersk’s carbon footprint, making its shipping operations more sustainable. With sustainability becoming an increasingly vital metric for investors and consumers, Maersk’s AI-driven approach serves as a model for how technology can drive environmental leadership.

Similarly, Hyundai Mobis’ integration of AI-powered defect detection technology has reduced manufacturing waste and associated emissions by 28%. This shift towards smarter, more efficient manufacturing processes enables Hyundai to meet its ESG commitments while consistently delivering high quality products.

However, AI’s environmental benefits are not without their own costs. While AI can contribute to climate solutions, its operation consumes massive amounts of energy. For instance, training a single large language model can use more electricity than 120 homes do in an entire year. Moreover, AI data centres often require vast amounts of water and energy to operate. An ESG specialist from a technology solutions provider highlighted this tension: “AI can help reduce emissions, but it can also increase environmental footprints if not deployed responsibly.”

This dilemma is real: AI can help solve climate problems, but it can also exacerbate them if not carefully managed. Organisations must prioritise energy-efficient systems and renewable energy sources to mitigate the environmental impact of their AI infrastructure. Therefore, AI for sustainability isn’t just about reducing external emissions — it is also about proactively managing AI’s own carbon footprint.

AI has the potential to be the ultimate engine of progress, powering both profit and sustainability. To truly harness its full potential, companies need to strategically balance these two powerful forces:

* Build AI with sustainability in mind: Whether optimising shipping routes like Maersk, or improving manufacturing efficiency like Hyundai Mobis, AI’s power to drive ESG outcomes should be a core consideration when developing new solutions.

* Plan for integration, not just deployment: As Maersk and Hyundai Mobis learnt, AI isn’t a plug-and-play solution. Businesses must invest in the necessary infrastructure and foster a cultural readiness to support the seamless adoption and integration of AI.

* Account for AI’s environmental impact: While AI can drive sustainability, it is crucial to monitor its carbon footprint. Optimising data centres and AI systems for energy efficiency ensures that AI truly is a net-positive force.

For companies like Maersk and Hyundai Mobis, AI is no longer a futuristic concept; it is a present-day reality. It is a powerful, dual-purpose engine already delivering tangible business results and meeting critical sustainability goals. However, achieving this crucial balance — where profit doesn’t come at the expense of the planet — demands a strategic and conscious approach.

As AI continues its rapid evolution, the companies that thrive will be those capable of managing both engines simultaneously, steering confidently towards growth and ESG leadership without burning out in the process.

Akhil Gupta is the group CEO of a conglomerate delivering IT infrastructure, AI and talent solutions across 18 countries

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