Hitachi Digital Services: How can AI Empower Sustainability?
AI is becoming increasingly difficult to avoid in any industry.
The technology is not a one-size-fits-all solution, however, is starting to be embedded into sustainability strategies around the world.
As a result, concerns are increasingly being raised at the high energy requirements of the technology, with data centres, undersea wiring and other infrastructure being expanded to accommodate AI’s increased use.
Hitachi: Technology driving sustainability
Founded in 1910, Hitachi is a Japanese multinational conglomerate. Originally created as an electrical engineering company, it has evolved and expanded into a global company that describes itself as ‘driving social innovation business, creating a sustainable society with data and technology.’
- Aerospace and Defense
- Automotive
- Banking, Financial Services and Insurance
- Communication, Media and High Tech
- Energy and Utilities
- Healthcare
- Manufacturing
Leading sustainability strategy for Hitachi Digital is Pablo Orvananos, Global Sustainability Practice Lead. Having worked in sustainability and strategy in both mature and emerging markets, like Spain, China, UK, Australia, Vietnam and Mexico for more than 18 years, Pablo is adept at adapting to new sustainability challenges and opportunities like AI.
In his role at Hitachi Digital he has initiated and developed a comprehensive sustainability offering from the ground up, as well as collaboratively working with innovative sustainability startups to help clients achieve their sustainability ambitions.
He shares his expertise with Sustainability Magazine about how AI can be harnessed for sustainability good – and the risks if it isn’t.
We know that AI has a huge impact on carbon emissions – is AI really good for sustainability?
AI has often been critiqued for its substantial carbon footprint, yet its potential for driving sustainability is profound.
The paradox lies in AI’s dual role as both a contributor to and a solution for environmental challenges. To fully grasp this dynamic, it is essential to delve into how AI can foster innovation, enhance sustainable practices, and address the myriad challenges organisations face when implementing AI-driven sustainability initiatives
How can AI drive innovation and sustainable solutions across various industries?
Despite concerns about its carbon emissions, AI has the capability to significantly advance sustainability.
A recent IPCCC report has uncovered that using AI for environmental applications has the potential to boost global GDP by 3.1–4.4% while also reducing global GHG emissions by around 1.5–4.0% by 2030 relative to Business as Usual (BAU).
AI’s potential for sustainability lies in its ability to analyse vast amounts of data quickly and accurately, uncovering patterns and insights that can lead to optimise resource use, reduce waste, and improve energy efficiency across various sectors.
For instance, in agriculture, AI-driven precision farming techniques allow for the precise application of water, fertilisers, and pesticides, reducing environmental impact while maximising crop yields. Similarly, in energy management, AI systems can predict demand and manage distribution more efficiently, minimising waste and reducing greenhouse gas emissions.
AI’s impact on innovation spans multiple industries, revolutionising processes and creating sustainable solutions. In manufacturing, AI-powered predictive maintenance reduces downtime and extends the life of machinery, contributing to less waste and more efficient use of resources.
Transportation systems benefit from AI through optimised routing and traffic management, which lower fuel consumption and emissions. Additionally, AI aids in developing advanced materials with lower environmental impact, fostering more sustainable production practices.
What challenges do organisations face when implementing AI for sustainability, and how can they overcome them?
Implementing AI for sustainability is not without its challenges. One significant hurdle is the high energy consumption of AI systems, which can offset the environmental benefits if not managed properly.
Organisations must invest in renewable energy sources to power AI technologies sustainably. Additionally, there are concerns about data privacy, security, and the ethical implications of AI. Overcoming these challenges requires a collaborative effort across sectors, involving policymakers, businesses, and communities to establish robust frameworks and guidelines for AI deployment.
To overcome these challenges, businesses can adopt a multi-faceted approach. Investing in renewable energy to power AI operations, enhancing data management practices to ensure privacy and security, and developing interdisciplinary teams that combine expertise in AI and sustainability are essential steps.
Additionally, fostering collaboration between stakeholders, including governments, academia, and industry, can facilitate the sharing of best practices and drive the collective advancement of AI for sustainability.
- Integrating AI with other emerging technologies like the Internet of Things (IoT), blockchain, and robotics. This integration can enhance data collection, improve decision-making processes, and foster innovation.
- Combining AI with IoT in smart cities can lead to better traffic management, waste reduction, and improved air quality.
- A holistic approach can ensure businesses not only achieve sustainability goals, but can gain a competitive edge in the market.
What steps are necessary to democratise action on sustainability using AI?
To democratise action on sustainability using AI, several steps are necessary. Firstly, increasing access to AI technology and education is crucial. Providing training and resources to diverse communities ensures that more people can contribute to and benefit from AI-driven solutions.
Secondly, fostering partnerships between governments, academia, and the private sector can drive research and development in AI for sustainability. Collaborative efforts can lead to the creation of open-source AI tools and platforms, making it easier for organisations of all sizes to implement sustainable practices.
While AI poses certain environmental challenges, its potential to drive sustainable innovation across industries is immense. By addressing implementation hurdles and adopting holistic strategies, businesses can harness AI to create substantial environmental and economic value.
Democratising access to AI tools further ensures that these benefits are realised on a global scale, paving the way for a sustainable future where technology and ecology harmoniously coexist.
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