Sustainable AI

The time to act on sustainable use of AI is now.

Sustainable thinking is the only way forward if we want to keep building responsible business and solutions for a thriving world. Use of Artificial Intelligence (AI) is no exception. Sustainable AI methods aim to ensure ethical and responsible use of AI through increased awareness and management of the risks and impacts of AI systems.

AI is widely used across virtually all industries to automate tasks, improve operational excellence, and create innovative services. These unprecedented opportunities come with risks, such as perpetuating discrimination or causing environmental harm. Sustainable AI means capturing the potential of AI while carefully managing the risks and impacts. With our unique combination of expertise in data science, social sciences, engineering, design, and business, we will enable you to make the most of your AI investments responsibly and sustainably.

AI systems differ from traditional IT systems in how they reach their outcomes. Complex AI systems typically contain randomness that can lead to unexpected outcomes, and often the functioning logic of AI systems is not transparent or easily understandable. This lack of transparency, combined with the role of AI in supporting human decision-making, or even making decisions autonomously, makes it increasingly important to recognise and manage the impacts of AI. The unique features of AI systems require us to be more conscious of their social, environmental, and economic effects, making work on sustainable AI more important than ever.

Sustainable AI refers to creating and using trustworthy AI systems that deliver long-term benefit to business, people, and the planet.

Sustainable AI methods aim to ensure the ethical and responsible use of AI through increased awareness and management of the risks and impacts of AI systems. Sustainable AI work includes building appropriate measures for transparency, security, accountability, and auditability of AI systems while ensuring that their intended benefits are realised.

We’ll help you raise awareness, adopt AI governance practices and tools, and align the use of AI with your values and strategy. This will help you realise your business goals responsibly, ensure customer and employee satisfaction, and attract top talent – turning sustainable AI into a competitive advantage.

Sustainable value creation with AI – How we can help

Path to sustainable use of AI

What sustainable AI means and what your goals are

Hazy terms like “AI” and “sustainable AI” need to be defined and mutually understood before the organisation can move forward. We will help your leadership team set clear focus and direction, and upskill your workforce to start building a culture of AI sustainability.

Executive AI education to give the leadership team a shared understanding and enable them to steer the work
Data, analytics, and AI education across the organisation to upskill and empower your employees
High-level AI maturity assessment to identify objectives, focus areas, and next steps
Vision, objectives, and success metrics to communicate the desired direction
Sustainable AI strategy as part of your data strategy

Read how we helped DNA leadership teams get on the same page with AI skills and opportunities and how we orchestrated an AI Masterclass tailored for NATO. Check out also what are the significant opportunities for Kela through AI.

Adopt sustainable AI processes and practices

Turn sustainable AI principles into practices

Many organisations already have principles of responsible use of AI in place, but few can tell how the principles are realised in daily work. We will help you move from good intentions to pragmatic action by enriching your existing processes and practices with the requirements of sustainable use of AI.

AI sustainability assessment to clarify the current state and identify gaps to the desired state
AI governance model to help prepare for the requirements of the EU AI Act and other relevant laws and regulations
Integrating human-centric design principles across the lifecycle of AI systems
Enhancing ways of working to enable effective cross-functional collaboration

Build future-proof AI solutions and avoid algorithmic debt

Sustainable AI solutions require design thinking, focus on value and risk, and solid engineering practices

With our interdisciplinary teams combining design, business, data science, and engineering expertise, we will help you ensure that your AI solutions deliver the intended value while carefully managing risks. With our deep understanding of MLOps technologies and best practices, we will help you create and use AI systems in a way that reduces technical debt and frees your data science team to focus on creating new solutions instead of fixing and supporting old ones.

Sustainable AI use case identification and assessment, to find the most valuable ways to use AI for the good of your business, customers, society, and the environment
AI innovation program to set up structures for continuous impactful AI innovation
AI system sustainability assessment to identify and mitigate risks and increase transparency of AI systems
MLOps technical solutions, best practices, and AI operating model for embedding sustainability into the development and use of AI systems, such as bias monitoring and correction, improved transparency, explainability and auditability, and automated monitoring, logging and alerts

Handbook of leading sustainable value with AI

Get pragmatic approaches for utilising AI for the good of your organisation and customers, while minimising negative impacts to people and the planet. You’ll also gain insights into best practices through case studies from industry leaders who have successfully implemented sustainable AI practices.

Get the handbook