Nearly four in ten organizations with ambitious climate commitments are struggling to hit their targets, and artificial intelligence is making the problem worse. A comprehensive study by BearingPoint surveyed 510 senior executives across Europe and the US, revealing a widening gap between what companies promise on climate and what they actually deliver. While 95% of organizations have committed to Science Based Targets initiative (SBTi) targets or structured climate action plans, 37% report delays in achieving them .

The core issue is straightforward: companies are deploying AI and digital technologies at scale without the governance structures, measurement tools, or strategic alignment needed to manage their environmental impact. As AI demand accelerates, the digital footprint of IT infrastructure is expected to grow significantly, yet most organizations remain unprepared to track or control it.

Why Are Companies Falling Behind on Climate Goals?

The BearingPoint research identifies several critical barriers preventing organizations from translating climate ambitions into measurable progress. Just over one third of businesses, 36%, say they have fully integrated their technology and sustainability strategies, meaning the majority are operating in silos . This fragmentation creates blind spots where AI infrastructure expands without corresponding sustainability oversight.

The governance problem runs deeper. Two fifths, or 40%, of Chief Information Officers (CIOs) and Chief Technology Officers (CTOs) report that they are not involved in sustainability decision-making at their firms . This exclusion is critical because technology leaders are the ones who understand infrastructure costs, energy consumption, and the real-world implications of deploying large-scale AI systems. Without their voice at the sustainability table, companies make decisions that inadvertently increase emissions.

Data transparency and measurement tools are also lacking. One third of respondents stated they have sufficient supplier data to commit credibly to reduction targets, while half said they lack the correct tools to manage sustainability objectives . Without visibility into their supply chains and without software platforms designed to track digital emissions, companies cannot identify where problems exist or measure whether their interventions are working.

How Can Organizations Bridge the Sustainability-Technology Divide?

Experts argue that the solution requires structural change, not just incremental improvements. Matthias Roeser, global leader of technology at BearingPoint, explained the core challenge: "Many organisations have set ambitious climate targets, but turning these commitments into operational reality remains difficult. AI is emerging as both a sustainability enabler and a new source of emissions, requiring stronger governance and measurement."

"AI can become one of the most powerful enablers of sustainability, but only if it is deployed responsibly. Organisations need a holistic approach that integrates sustainable technology architecture, transparent measurement of digital emissions, and stronger collaboration between CIOs and CTOs, sustainability leaders, and business executives," stated Rémy Sergent, global leader of people and strategy at BearingPoint.

Rémy Sergent, Global Leader of People and Strategy at BearingPoint

The research suggests several concrete steps that organizations should take to close the gap between climate ambition and execution:

• Integrate Technology and Sustainability Leadership: CIOs and CTOs must move beyond managing IT infrastructure and become active participants in sustainability governance, ensuring that technology decisions account for environmental impact from the start.
• Implement Transparent Digital Emissions Measurement: Organizations need dedicated tools and platforms to track the energy consumption and carbon footprint of their AI systems and digital infrastructure, creating accountability and enabling data-driven optimization.
• Adopt Specialized ESG Platforms: Two thirds of surveyed organizations believe that specialized digital sustainability platforms will be the right solution by 2030, suggesting a shift toward purpose-built software that integrates technology metrics with environmental, social, and governance reporting.
• Strengthen Supplier Data Collection: Companies must invest in supply chain transparency to understand the full scope of emissions from their technology vendors and partners, enabling credible reduction commitments.
• Align Business Strategy with Technology Architecture: Sustainable technology transformation requires collaboration between technology experts, sustainability leaders, and business executives to ensure that infrastructure decisions support rather than undermine climate goals.

What Does the Future Hold for AI and Corporate Sustainability?

The BearingPoint study paints a picture of an industry at an inflection point. While the digital footprint of IT remains low at most surveyed organizations, currently below 5%, it is expected to grow as AI demand accelerates . This trajectory suggests that the gap between climate commitments and execution will widen unless companies act now to build the governance and measurement infrastructure needed to manage AI responsibly.

The shift toward specialized ESG platforms reflects growing recognition that generic sustainability reporting tools are insufficient for the AI era. Two thirds of respondents believe that specialized digital sustainability platforms will be essential by 2030, indicating that organizations are beginning to invest in solutions designed specifically to track and optimize the environmental impact of technology .

The stakes are high. As AI infrastructure becomes increasingly central to business operations, the decisions companies make today about how to govern, measure, and optimize that infrastructure will determine whether artificial intelligence becomes a tool for accelerating climate progress or a new source of corporate emissions that undermines decades of sustainability work.