Per Andersson is Professor at Stockholm School of Economics (SSE) and his research is early 2000s focused on digital transformation processes, and since 2018 now including the impact of artificial intelligence (AI). His present AI focused research is focused on the effects on organizations and business of AI being implemented in different types of operations. This research aims to investigate business consequences and challenges of AI, with a focus on business strategy, business models, organization and work, and how they are connected. In focus are the outcomes of AI development on both effectiveness and customer value, and on organizational and operational efficiency and profitability. His analyses of digital transformation projects show that the challenges are significant, and many of the effects and consequences are still uncertain. His previous research on digital transformation and ongoing research of AI implementation have shown that there are three types of challenges. These are presently in focus of his research 2023: 

Firstly, one challenge concerns the issue of effectiveness and service outputs from AI based operations. More efficient internal operations with reduced operational costs is one thing. How AI based analyses and operations can be transformed into new revenues for business and into (new) value creating services for customers is still a challenge for many enterprises. AI insights can create value for business by creating insights in line with business objectives, but more challenging is how AI can be used to develop the business by supporting the creation of new value based offerings attractive to customers and the market. Secondly, as regards organizational challenges and impacts of AI, research on AI adoption in business has shown that among early adopters in business, AI has had it its biggest internal impact on these firms' back-office functions of IT and finance/accounting etc., many of which involve computer-to-computer interactions. Although being predicted as the target for early implementation, companies are still in the very early phases of adopting AI in front-office operations and organizational functions, and in areas of marketing, sales, and services. Thirdly, companies are beginning to understand the implications of the evolving AI-driven automation ecosystem far beyond narrow artificial intelligence applications. While businesses across industries and nations are at a different level of AI adoption, the current approach to AI strategy is still often overly narrow as businesses mainly focus on using AI for analyzing data, predict performance to automate workloads, etc. But AI is also the foundation for structural changes in industries, power shifts between users and suppliers of AI services, new patterns of cooperation and competition and radical shifts in companies' business models. 

Understanding the mechanisms associated with the three challenges described and developing more detailed knowledge on how they are connected, and finally how they can be and are managed in complex cross-industry contexts is in focus of Per Andersson's research from 2021 and onwards. He is also responsible for several new PhD projects in the same field.

Per Andersson is also teaching in the MSc program Master in Business Management (MBM) including the course Business Creation and Development.