AI and transparency: A new age of corporate responsibility

In today’s corporate landscape, transparency isn’t just a buzzword—it provides a mandate. Investors are not satisfied with vague references; they demand clear, comprehensive disclosures. 

This demand for transparency over business use of AI is coming not just from investors but also from policymakers. Regulators worldwide are stepping in. The EU AI Act, for instance, requires businesses to adopt a risk-based approach, categorising AI systems into distinct risk levels. In the US, states, like Colorado and California, are leading the way with laws requiring internal governance and disclosures around consequential AI uses. In Asia, South Korea recently passed a wide-ranging national AI framework, while other countries such as China and Taiwan are developing targeted rules for generative and algorithmic technologies. 

Companies have a clear imperative to get ahead and tell their own story. Annual reports and standalone governance disclosures are avenues for disclosing this information, but sustainability reports offer a forward-looking, governance-focused platform.  

When companies consider AI initiatives alongside their sustainability goals, they can demonstrate how they are driving business model adjustments for long-term value creation. The strategic integration of AI innovation and sustainability considerations can position them as leaders in their sector, setting the pace for the market and industry reconfiguration.

Sustainability reporting frameworks such as the European Sustainability Reporting Standards and the IFRS Sustainability Disclosure Standards offer a structured avenue for disclosing AI strategies, governance, risks and opportunities. For example, the effects of AI on workforce dynamics, environmental impacts or broader communities can be reported on using the sustainability materiality lens. This will enable companies to demonstrate responsible oversight—reinforcing credibility and stakeholder trust.

For businesses developing or deploying AI at scale, pre-emptively integrating AI disclosures into sustainability reporting is not just a prudent move but places them ahead of the curve. This displays leadership in Responsible AI deployment, aligning with evolving expectations and underscoring a commitment to responsible innovation. 

We’re already seeing companies recognise this. PwC’s early analysis of 250 CSRD reports shows that reporters are already voluntarily disclosing impacts, risks and opportunities (IROs) from AI use, cybersecurity, and data governance in their sustainability reports through entity-specific content. 

A notable example of this shift comes from SAP, which identified Responsible AI as the most financially material topic in its 2024 SAP Integrated ReportOpens in a new window—reflecting its strategic role across products and services, and the associated risks around misinformation, human rights and regulatory exposure. The company then discloses dedicated governance structures, oversight mechanisms and AI-specific risk processes—demonstrating how Responsible AI can be addressed within a sustainability reporting framework.

Additionally, over 60% of investors say that clear and consistent disclosures aligned with reporting standards enhance their confidence in a company’s sustainability performance. This reinforces the role of sustainability reporting as a trusted channel for communicating how AI is governed and integrated across the business.

According to PwC's 2025 AI Business Predictions, artificial intelligence is expected to expedite the energy transition and generate substantial cost savings, thereby enabling organisations to become leaders in sustainable innovation. 

While the opportunities AI presents could fill an entire article, let’s explore a few notable examples: 

For further potential AI use cases, see Generative AI unleashed for sustainability. 

AI holds tremendous potential, and it introduces new layers of complexity and risks to manage. For example, design vulnerabilities, data security issues, and potential societal and environmental impacts.

As with any transformative technology, organisations need to define their risk appetite and proactively plan for mitigation in pursuit of innovation, efficiency or scale. Effective governance demands a structured understanding of AI-related risks, clear accountability across functions and alignment with strategic priorities, including sustainability objectives. 

Below, we explore examples of risks and how companies can assess these within their sustainability materiality assessments—considering impacts on both people and the environment, as well as risks or opportunities that could affect enterprise value. 

By adopting a comprehensive framework for Responsible AI, businesses can effectively manage the dual potential of AI’s opportunities and risks within their corporate strategies. Companies that proactively navigate these challenges will stand out as pioneers, confidently harnessing AI's transformative power while upholding integrity and trust across their operations. 

It’s clear AI presents companies with a transformative opportunity. Communicating how the associated dependencies/impacts, risks and opportunities are being managed enables companies to deepen stakeholder trust.

Consider these no-regret steps now to build stakeholder trust, as you pursue your AI adoption journey:

1. Leverage your actions categorising AI inventories for regulatory purposes  

Use the insights from your AI risk categorisation work to enhance your sustainability reporting materiality assessments. Take this as a starting point to capture a detailed view of dependencies/impacts, risks and opportunities to be managed and embedded in core strategy, systems and processes.  

2. Strengthen Responsible AI practices aligned with strategic goals

With a clearer understanding of your AI risks—strengthen your approach to Responsible AI. Develop and implement a robust framework for Responsible AI that encompasses oversight, transparent decision-making, proactive risk management, and targeted upskilling for workforce readiness. Embed these practices within your broader corporate strategy to mitigate risks, respond to emerging regulatory trends and drive value creation, thereby enhancing stakeholder trust. Explore further in AI rewrites the playbook: Is your business strategy keeping pace?

3. Enhance your corporate reporting to tell your own story 

Tie factual data to engaging narratives. Utilise both quantitative metrics (such as energy savings and emissions reduction) and qualitative insights. By considering disclosures in your corporate reporting—be it your annual report or sustainability report or integrated report—you can paint a more rounded picture of your organisation’s performance. This will reinforce stakeholder trust and leadership in your sector.

As AI continues to reshape how businesses operate, transparency becomes essential—not just to meet external expectations but to guide internal decision-making. Sustainability reporting provides a credible, structured avenue to disclose both how AI use in your business is governed and how it’s integrated into the business to support long-term value creation.

The authors wish to thank Superna Khosla, Monika Jonce, Caitlin McDonald, Ilana Golbin Blumenfeld, Monika Januszkiewicz, Brigham McNaughton, Kazi Islam and Joe Atkinson for thoughtful input and guidance throughout.