Dorothy Maguire from EY reveals how tech innovation across sectors is helping to address sustainability challenges.
Data and AI will help companies to get to net zero.
Whether it’s helping companies design more sustainable operations with digital twins, reducing risks along supply chains with blockchain technology, or reimagining smart, energy efficient infrastructure with AI, data and analytics can transform businesses for a sustainable future in a way that is human-centred and ethical.
“The challenges that face society today are mounting, but AI and data and analytics offer a path to ‘innovate to zero’”
In this article we will showcase the role of the most promising innovations in tech for sustainability, highlighting what companies here in Ireland can do to improve their own sustainability agendas.
Embedding purpose in digital processes
By embracing the green and digital transitions, companies are equipping themselves with the tools to meet their sustainability challenges head on. Although AI and data themselves have an environmental impact because of the energy usage associated with data processing and storage, they also present exciting opportunities to help mitigate climate change.
Companies in Ireland are increasingly seeking to minimise their carbon footprints, and EY’s most recent State of Sustainability Report suggests this is not only for compliance, but also because companies want to do good for the environment. Increasingly, companies are seeking to embed purpose in their digital processes.
If companies approach sustainability strategically, they can unlock new opportunities from data, and create value from those insights.
There are four key areas where data can enable companies to be more sustainable, 1) designing a sustainability strategy, 2) transforming operations, 3) improving supply chains, and 4) reporting and assurance.
Designing a Sustainability Strategy
Setting a sustainability strategy requires companies to evaluate their current impacts across the full ESG spectrum, and to then set and measure progress against new targets. This work involves surveys of stakeholders, analyses of company reports, horizon scanning, and risk assessment.
These activities may be enhanced with data and insights using tools such as automation of surveys, web scraping for horizon scanning, and natural language processing to understand the sentiment of customers and stakeholders.
For example, technology like Al Gore’s ‘Climate Trace’ uses satellites, sensors, and machine learning to monitor the authenticity of a company’s sustainability claims by cross-checking their claims against actual environmental impacts.
2. Transforming Operations
Once companies have set their goals and targets to reduce their environmental impact, it is essential that they have the tools to design more efficient processes.
Companies like EC3 are using AI to visualise the carbon footprint of building materials as they design for low carbon housing and infrastructure including data centres. CIM and LoweConex are using AI to adjust heating and cooling in buildings to save energy.
In agriculture, AI tools are being harnessed to manage land more efficiently with in-field sensors and satellite imagery to optimise fertiliser usage.
Anomaly detection using AI is preventing shipments of damaged goods, and optimising transport emissions. Such tools enable us to reduce inefficiencies that are costly to the business and the environment.
3. Improving supply chains
The Covid-19 economic shock exposed vulnerabilities in the supply chains of firms all over the world.
An EY study found over 90% of institutional investors revise their investments if companies do not address their supply chain environmental risks. The sustainability of supply chains can be improved by technologies that increase control and transparency. For example, EY’s blockchain solutions provide transparency and provenance of products.
Companies are facing pressure to report their ‘scope 3’ emissions which are the result of activities from assets not owned or controlled by the organisation. Microsoft, for example, provides estimates of the footprint of their customers’ cloud storage to make scope 3 reporting easier on their customers. Such ‘sustainability as a service’ data propositions are helping mitigate supply chain risks.
4. Reporting and assurance
As reporting obligations for ESG intensify, there will be an increasing need for reporting and assurance. Like financial disclosures, this will involve integrations of data from across the business. However unlike financial data ESG data is not just reported in dollars and cents, but in a myriad of units from gigawatt hours to tonnes of CO2.
Data systems and AI can be used to integrate those data, automate their compilation across many frameworks. Companies such as Enablon, SAP, IBM, Service Now and Microsoft have built reporting platforms to aid in this effort. The benefit is that additional insights can be leveraged from these data in ways that can create additional value for companies.
The insights feed back into strategy and progress tracking, they also provide insight into areas where the business may want to invest in updating assets, or improving design of systems to enhance operational performance. It’s worth the investment, and there is mounting evidence that ESG compliance leads to good financial performance as well.
To conclude, the challenges that face society today are mounting, but AI and data and analytics offer a path to ‘innovate to zero’, and forms part of the solution to tackling climate change, while creating additional value for businesses and their stakeholders alike.