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How do we design sustainable business operations for the future with AI?


Artificial intelligence is increasingly being integrated into various sectors of business and society. At the same time, AI is also creating significant new opportunities. In this post, we’re going to take a closer look at how to make sure that we consider all aspects of sustainability when designing and building AI solutions for the future.  

Towards a smarter future: the role of AI in business transformation

When it comes to AI and growth opportunities, the EU Parliament's Think Tank has estimated that AI-assisted labor productivity will increase by 11-37% by 2035. Generative AI in particular is expected to have significant positive effects on economic and productivity growth. According to the report ‘The economic opportunity of AI in Finland’, the large-scale implementation of generative AI is estimated to increase Finland’s GDP by 8% over a decade [3]. 

This estimate is based on the assumption that generative AI will increase productivity in several sectors, especially in services. According to the report, this is because generative AI is well suited to improve service productivity by automating information-intensive tasks in administration, training, and personalized customer interactions and data processing.

Sustainable AI sets the foundation for responsible innovation

The development and use of sustainable AI rests on three pillars: social, environmental, and economic responsibility [1]. What this means is that sustainable business is a holistic approach that recognizes the importance of a balance of economic, social, and environmental responsibility in the company’s strategy [5]. 

Taking sustainability into account is key to successful transformation projects, especially in sectors where artificial intelligence is expected to lead to a significant replacement of routine and manual jobs. That’s why Vincit has drafted a set of generative AI principles that ensure new technologies integrate smoothly into existing business processes without leaving employees behind [4].

Supporting social sustainability in these situations is important and can include actions such as retraining, supporting employees during changes, and preserving the vitality of communities. For example, if AI replaces jobs in customer service, companies can redirect employees to new positions within the company or support them in their transition to new career paths by providing training and development opportunities. 

Sustainable AI in service and business design

Artificial intelligence creates a lot of new ways to design and develop services and products. Today, the starting point is that many organizations have experimented with AI to boost productivity. Design work is not isolated from the change brought about by AI. 

An internal survey of Vincit designers found that generative AI is perceived as a personal assistant. With new development tools, the benefits of AI in the design process include visual expressiveness, diversification of ideas, dialogue with a virtual sparring partner, and compilation of extensive sets of information. 

AI-assisted work will undoubtedly speed up the development process, and the idea of continuous improvement and faster lead times to solutions is appealing. However, as design work develops, designers should be aware of the types of questions that should be asked to take sustainability aspects into account in design. 

New AI-assisted working methods require designers to understand the role and impact of AI and to ensure that design solutions are sustainable. On this premise, development activities should be based on the following principles:

  • Social sustainability: services should be designed while keeping in mind how they impact social factors such as equality, employment, and employee well-being.
  • Environmental sustainability: the environmental impact of AI and data use, such as energy consumption should be minimized while the recyclability of materials should be taken into account. This may include implementing energy-efficient solutions.
  • Economic sustainability: ensuring the economic sustainability of services is important so that they are profitable in the long term. Leveraging AI can improve efficiency and reduce costs, but investment in new technology requires judgment.

The design and implementation of sustainable AI highlight complex challenges that require a multi-method approach and multi-professional collaboration to understand the role of AI and its implications. In this co-creation process, service design plays a central role, and three key perspectives emerge when integrating AI into services [2]:

  • Human-centered focus: integration of artificial intelligence into services should be carried out with a human-centered focus, which means understanding customers’ needs and behaviors. This can mean, for example, taking into account emotional states and personalizing services based on this information.
  • Ethical use of data: it’s important to ensure that user data is collected and processed ethically. This includes transparency in the use of data, collecting user consent, and ensuring data protection at all stages of the service.
  • Ensuring service quality: AI can be used to improve service quality, for example by optimizing the user experience and personalized service. AI can help identify users' needs in real time and provide them with tailored solutions.

The power of service design is to extract challenges and refine them into solutions through collaborative development. However, a successful outcome requires an organization to incorporate sustainability principles into their work in order to ensure that any solutions contribute to overall well-being and societal sustainability. Design through a sustainability perspective helps to identify vulnerabilities in companies' core processes in a proactive way. This can include for example critical infrastructure and logistics. 

Resilience – the ability to adapt business operations in a sustainable way in unexpected change situations – can be built into many of these processes through sustainable AI. For example, when a company launches a new service, a non-scalable customer service can become congested in an unexpected way. In such a situation, an AI-integrated customer service solution would have added much-needed additional capacity. For a company, a smooth customer service process is a major success factor as customers get their requests resolved within seconds and can then recommend the new product or service in their networks.

Working in business ecosystems builds bridges to a sustainable future

The EU’s regulatory framework – such as the AI Act – guides the development of safe AI systems, helping to safeguard people’s rights and make AI systems more reliable. Due to the systemic operating environment, the design of sustainable artificial intelligence in business ecosystems is essential.

Most organizations don’t have the means to meet the demands of sustainable AI alone. However, In ecosystems, companies can develop resource-wise innovative solutions that address current and future complex technological, societal, and economic challenges. This also strengthens the company's future competitiveness in challenging situations, which the World Economic Forum has listed in its risk report [6]. For example, stakeholders in ecosystems may co-create new knowledge, processes, and data through shared interfaces. And without high-quality data, there is no design work or services that can integrate AI in a sustainable way.

In 2022, we started cooperating with the University of Laurea Applied Sciences. Thanks to that cooperation, we’ve been able to build new knowledge through student projects and thesis work as well as applying for funding for our own research-oriented projects. In 2024 we also established a strategic partnership with Tampere University’s Sustainable Societies and Digitalization master’s program. This will allow us to focus on building sustainable ways of working in digital service and business development. These research-oriented activities will eventually create value for our customers, society, and also for the planet. 

The value of systemic activity is in the creation of shared value for all parties involved. Working with universities gives Vincit and our customers real-time access to the cutting edge of research and the innovative potential of students, which can lead to the development of new products and services. 

For companies, the cooperation provides the opportunity to modify and test services and products in partnership networks together with future designers and developers. This also benefits students who gain hands-on experience in real business challenges and can apply theory to practice. Systemic collaboration like this is Vincit’s way of building bridges to the future, where technology and humanity go hand in hand to create a more sustainable world.

[1] Elkington, John (1999). Cannibals with forks: the triple bottom line of 21st century business. Oxford: Capstone. ISBN 9780865713925. OCLC 963459936.
[2] Rjsé, V., Jylkäs, T., & Miettinen, S. (2023). AI Enabled Airline Cabin Services: AI Augmented Services for Emotional Values. Service Design for High‐Touch Solutions and Service Quality. Design Management Journal, 18 (1), 100-115.
[3] Implement Consulting Group. (2024). The economic opportunity of generative AI in Finland. Retrieved from (read 6 May 2024).
[4] Vincit. (n.d.). How we use generative AI at Vincit. Retrieved from (read 6 May 2024)
[5] Vincit. (2022). Sustainability report 2022. Retrieved from (read 6 May 2024).
[6] World Economic Forum. (2024). The Global Risks Report 2024. Retrieved from (read 6 May 2024).