Why CFOs Should Rethink Corporate AI investment

For finance leaders AI is still a dual-edged investment: it delivers substantial operational efficiencies but still demands careful consideration around its environmental and financial costs.

To understand the balance of AI's business value against its sustainability implications, SAP has released a whitepaper exploring how AI can be deployed responsibly whilst supporting corporate decarbonisation strategies. 

The company's research coincides with the World Economic Forum's prediction that AI could reduce annual emissions by three to six gigatons of carbon dioxide equivalent by 2035.

Optimising AI's energy footprint

SAP's approach centres on reducing the environmental impact of AI, particularly energy consumption, whilst addressing social and ethical considerations. 

The company has committed to enhancing the energy efficiency of its AI offerings, which could lead to emission reductions and optimised costs across the value chain.

According to the whitepaper, ‘AI and Sustainability at SAP’, all AI assets and processes developed under the company's direct operational control are optimised for energy consumption.

The document emphasises that continued monitoring and proactive management of AI-related emissions will be essential to sustaining efficiency gains alongside declining costs.

To address growing ethical concerns around the effective deployment of AI, SAP has also established a Global AI Ethics Policy outlining rules for the development, deployment, use and sale of AI systems. 

This framework aims to ensure that AI solutions are created with social and ethical sustainability in mind, potentially avoiding economic, political or societal challenges.

SAP says it wants to create responsible AI data supply chains by engaging partners and its external network, ensuring models implemented are sourced and developed responsibly.

Matthias Medert, Global Head of Sustainability at SAP, said on LinkedIn: "AI is reshaping how the world works. But as its impact grows, so does our responsibility to ensure it scales sustainably. As AI becomes more powerful, it must evolve within planetary boundaries and be guided by strong ethical principles. Together, we are rethinking how AI is built, deployed and governed, balancing performance with efficiency and innovation with accountability."

Why CFOs should connect carbon and financial data

For chief financial officers, the whitepaper highlights how SAP Business AI can automate the processing of internal and external data sources to transform insights into actionable strategies. 

The technology can assist CFOs and chief sustainability officers in generating sustainability reports in 80% less time than without AI.

The application extends beyond reporting. Chief operating officers can use AI to build efficient supply chains through optimisation algorithms that provide accurate demand forecasts and improved demand sensing in production plants and warehouses.

Dominik Asam, Chief Financial Officer at SAP, says: "The future of sustainability lies in connecting carbon and financial data in the Green Ledger: managing cash and carbon with the same rigour. 

“With AI, we can raise data quality, automate compliance across hundreds of global regulations and identify the smartest investments for decarbonisation. This is how we move from reporting sustainability to steering it as real business value."

Microsoft has outlined a parallel approach through its Community-First AI Infrastructure initiative, which details how the company plans to build, own and operate data centres whilst protecting local communities. 

The plan involves covering electricity costs, replenishing water used by data centres, creating jobs for local residents and investing in local AI training.

Microsoft argues that large-scale infrastructure expansion is vital to economic growth and everyday improvements in people's lives. 

Melanie Nakagawa, Chief Sustainability Officer at Microsoft, says on LinkedIn: "AI is changing the world faster than any other innovation in history. The speed of its adoption, the surge in its demand and the rapid evolution of its capabilities are unlike anything we've seen before. 

“And like breakthrough technologies that have come before, including electricity, cars, aviation and the Internet, building the AI economy requires investments in new infrastructure."