Can AI Cut Uncertainty in Europe’s ESG Reporting Reset 2026?
Regulatory change in Europe is shifting the goalposts for corporate sustainability reporting.
The European Commission’s Omnibus package signals a potential simplification of reporting obligations under the Corporate Sustainability Reporting Directive, but for organisations that have already invested heavily in ESG data and preparation, the renewed uncertainty creates difficult questions about deadlines, compliance strategy and business value.
To unpack what this could mean in practice, Markus Bauten, Manager Business Solution at Konica Minolta Business Solutions Europe, shares how companies are navigating an evolving ruleset and why technology is becoming central to keeping ESG programmes on track.
He also outlines how AI can help bridge widening data gaps and bring consistency to ESG management, particularly for businesses trying to build credible sustainability reporting capabilities.
Konica Minolta, known for digital transformation and data-led solutions, is expanding its focus into sustainability through tools such as ESG AI, a platform designed to help companies capture, structure and use ESG data more effectively.
Markus explains why some organisations are pausing ESG activity despite rising market expectations and how AI can make sustainability both measurable and manageable, including for companies not yet subject to mandatory reporting.
The ESG landscape in Europe is currently changing rapidly. How is this affecting companies?
Europe is currently in a phase of exceptionally high uncertainty. With the Omnibus package, the European sustainability agenda is being reconsidered, and as a result, reporting thresholds and compliance requirements are changing.
If Omnibus is finally adopted, many companies may suddenly no longer fall under the CSRD – even if they have already started their preparations. Regulatory changes are creating uncertainty for executives: they do not know what applies today, what will apply in two or three years, or whether they should pause or continue.
As a result, many organisations have temporarily slowed down or postponed their ESG activities, even though they know that the topic is not going away.
At the same time, market pressure is increasing. How do you explain this?
While regulation is shifting, market expectations are accelerating. Consumer behavior is one of the clearest indicators: 74% of consumers consider sustainability when making purchasing decisions, and 63% consider a brand’s promotion of sustainability important when buying.
This means that companies may have more regulatory flexibility, but significantly less commercial flexibility. Sustainability is becoming a competitive factor, regardless of legal obligations.
If the importance is so clear, why do companies still struggle to embed sustainability into their core business?
Because ESG is still treated as a parallel activity rather than as part of the business model. The majority of companies (55%) keep their sustainability strategy completely separate from their business — or do not even have a strategy. And only 5% say their sustainability strategies are fully integrated into their wider business.
This gap reveals a fundamental problem: companies understand that ESG matters, but they do not know which concrete drivers are behind it.
They cannot clearly answer questions such as “how does ESG impact EBIT?”, “how does it reduce risks?” or “how does it support growth?” Without this financial translation, ESG remains abstract — especially for companies that are no longer required to report. They ask entirely legitimate questions: What value does ESG create? Where does the business impact occur?
How do data challenges contribute to this hesitation?
Data is one of the biggest obstacles.
ESG requires large, complex sets of information – especially in Scope 3, which accounts for around 80% of a company’s total CO₂ footprint. Scope 3 data is extremely difficult to capture manually, particularly for companies that do not have sufficient personnel.
This is another reason why many non-obligated companies have postponed the start of their ESG reporting. They do not doubt the importance of sustainability – but they struggle with the data work and the complexity that comes with it.
Where can artificial intelligence help in this environment?
AI has the potential to fundamentally transform ESG.
It can predict emissions and resource consumption, identify risks, uncover CO₂ hotspots, and automatically map supply chains. Above all, it can capture large volumes of data with a level of granularity that manual methods simply cannot achieve.
It can clean, classify, and connect the data – instantly and reliably. This creates real-time transparency that makes reliable reporting possible in the first place.
AI helps companies move from fragmented information to a clear and consistent understanding of their sustainability performance. And importantly, AI can support both obligated and non-obligated companies – but the group of non-obligated companies is significantly larger. This is why AI plays such an important role in helping them get started.
Many companies still express concerns about AI. What questions do you hear most often?
Many companies worry about reliability and transparency. They are concerned about data quality, because inconsistent or incomplete ESG data can lead to errors – and if the underlying AI model is not robust enough, these errors could even be multiplied. Transparency is another major issue. Many AI systems appear like a black box, and companies want to understand what the AI is doing in the background. They also ask about governance and accountability: who is responsible if an AI produces incorrect or distorted results? Another recurring question concerns the energy consumption of AI – how much CO₂ is generated when AI systems run?
And finally, there is the concern about ethical or social bias: companies know that incomplete or uneven data can lead to unfair ESG ratings or even to discrimination within the supply chain. These concerns are absolutely legitimate – and they show that AI solutions must be transparent, traceable, and trustworthy.
How does Konica Minolta approach a solution under these conditions?
Konica Minolta developed ESG AI specifically to remove the barriers that are holding companies back from making progress.
Our goal is to support particularly those companies that are not required to report. Many of them ask when AI in sustainability reporting will become affordable, or when solutions will become accessible that can collect, structure and enhance data with the help of AI.
They do not know whether they can afford such a solution – and that is a decisive point. This is exactly why we designed ESG AI to be intentionally accessible and affordable. The entry barriers are low, allowing companies to begin their ESG journey without large teams, without complex processes, and without costly consulting support.
How does your solution help companies take the first step?
ESG AI was developed to make ESG manageable for companies that feel overwhelmed by reporting or data requirements.
The tool uses AI to automate large parts of the work – collecting, cleaning, structuring, and connecting data. It consolidates ESG data across suppliers, logistics, and product life cycles into a single, high-quality reporting environment. This allows companies, for example, to gain a complete overview of their CO₂ footprint, determine emissions, and then implement CO₂ reductions.
It creates transparency and enables companies to clearly understand their ESG situation without having to build a large internal ESG team. It also helps reduce the fear of complexity. Many companies simply need a realistic starting point – and ESG AI provides exactly that. Our focus is on motivating and supporting non-obligated companies, because without a clear, direct benefit, they would not start at all. ESG AI gives them that benefit by making ESG simpler, clearer, and more achievable.
Who benefits most from it?
Everyone, but especially CFOs, ESG managers, sustainability officers, and controlling departments. By automating data preparation and providing deep analytical capabilities, AI enables these professionals to focus on strategic decision-making rather than administrative tasks.
What is the most important message you would give European companies today?
ESG is no longer optional. It is a central component of resilience, competitiveness, and economic performance. Regulation may change, but the expectations of consumers, customers, and society continue to rise. And AI is the key to overcoming the biggest hurdles – data collection, data processing, and the ability to make this data visible and relevant.
With ESG AI, we provide companies with a practical solution that enables exactly that – clear insights, efficient processes, and real business value.