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How companies can harness AI technologies for data-driven green reporting

Artificial Intelligence
(Image credit: Image Credit: Razum / Shutterstock)

Despite emissions falling in 2020 at the fastest rate for nearly a century, scientists are worried they will rebound in 2021 as lockdown restrictions ease and ‘normal life’ resumes. Across the business community, growing concern about climate change is driving greater action: with the majority of UK business leaders planning to increase long-term investment in sustainability initiatives.

This is a shift in the right direction, but the tricky next step is making sure such green efforts actually drive change. 

While over half of company leaders recognize this calls for better green measurement, achieving that is difficult with limited frameworks for green reporting available both globally and locally. Additionally, business leaders are now responsible for the sustainability efforts of their entire network of suppliers, which means clear oversight is key in holding partners accountable for ‘greenwashing’ – where organizations claim to be green through use of renewable energy, but they do not have the necessary processes in place to offset their overall carbon footprint. 

One way to overcome these challenges lies with harnessing artificial intelligence (AI). Using AI technologies, companies can ensure green programs and investments are measurable and performance-driven from the outset. AI can also play an important role in monitoring and optimizing supply chains, keeping all partners aligned with net-zero policies. But what does this look like in practice? 

Start by harmonizing data 

With the climate crisis more urgent than ever before, every business in every industry has a role to play in minimizing their impact on the environment. The first priority for any business looking to improve its green footprint is to gain a unified view of corporate data. Historically, however, this has meant coming up against a familiar problem: data silos. 

It is no secret that company data is complex and often stored in disparate systems across different areas of the business. Each department within an organization will collect and hold its own data in a location of their choice, thus creating multiple pools of fragmented green knowledge. To date, making this disordered information comprehensible has proved time-consuming and costly. However, AI technologies now make it possible for companies to quickly and efficiently pull information together via API-based data integrations that can automatically plug into an array of sources and collect, merge and harmonize varied data sets.

By leveraging AI to connect isolated data sets within a single platform, organizations can gain a complete picture of their organization’s green portfolio - including energy investments and net-zero purchasing workflows, such as current power purchase agreements (PPAs). This information can then be combined with important outside data sets, such as real-time local generator data, weather, satellite and risk analysis insights, trends and market insights, and renewable energy certificate data.

Only when internal and external data sets are consolidated into a single platform will key stakeholders truly be able to forecast their organization’s carbon footprint. Key metrics to track on an ongoing basis include CO₂ saved Vs. targeted reduction, total cost savings, total contracted renewable energy, total energy production, and all uptime and downtime generators.

Data-driven green reporting 

Alongside bringing data under consolidated control, AI has the capacity to help make greater use of the intelligence companies collect on an ongoing basis. In particular, applying analytical models to holistic data sets will allow key stakeholders to continuously manage and measure the output of their green investments and initiatives efficiently. 

The form AI-generated intelligence takes depends on the preferences of each stakeholder within a business. For example, that might entail configuring custom dashboards to show real-time qualitative insights and reportable checklist-style scoring, or detailed instant qualitative summaries with in-depth commentary on progress. Either way, outcomes can then be cross-referenced against inter-connected targets to deliver short and long-term insight that’s transferred to relevant parties. For instance, a CEO may see top-line updates on CO2 saved versus target reduction, while total cost savings from renewable supplier changes are shared with the finance team. 

By streamlining analysis and enhancing data accessibility, businesses can implement a transparent and accountable approach to green reporting. Furthermore, with an endless supply of accurate and granular insight, key stakeholders will be able to make more informed decisions about where adjustments are required to reach specific net-zero goals.

Extending capabilities to the supply chain 

Although a harmonized and automated view of corporate data is an integral element of building a cohesive net-zero view, it is crucial not to leave suppliers out of the frame. As companies lay out sustainability policies or corporate social responsibility (CSR) initiatives, their network of third-party suppliers must be included to not only avoid accusations of greenwashing, but also to ensure compliance with green targets. 

Fortunately, AI intelligence can offer actionable insights that allow the relevant stakeholders to keep all links in their chain on the right track. Through integrating data feeds from satellite providers, for example, AI is capable of rapidly detecting and even predicting anomalies from suppliers. AI technologies that analyze persistent data streams can also send immediate notifications of any unexpected problems, thereby providing a greater understanding of risk and authenticating the sustainability of a whole supply chain.

Looking ahead  

Addressing climate change is not a simple or quick-fix task. For organizations looking to minimize their impact on the environment, gaining a single view of corporate data, net-zero investments, and the supply chain network is an essential starting point to establish where they are now and what actions they must take.

With the assistance of AI technologies, companies can set sustainability projects on the right and, more importantly, measurable path for lasting success, automating target checks and harnessing predictive capabilities to prevent them from running off course. Only with this level of transparency will business leaders have confidence that there is no obscurity around the output of their green investments and initiatives, as well as their network of suppliers. This comprehensive knowledge will be essential to keep pushing forward in the corporate fight against climate change.

Muhammad Malik, CEO and Founder, NeuerEnergy

Muhammad Malik is CEO and Founder of NeuerEnergy, which serves as an intelligent advisor for corporate, industrial and public entities on the best suited net-zero products for their operations.