Vegard is an Associate Professor in Strategy at BI Norwegian Business School and a Senior Research Fellow with Accenture. He is researching and teaching on strategy, new organizational forms, digitalization, and business models. His areas of expertise also include governance and organization design, communities and crowdsourcing, open innovation, digital strategy as well as the impact of AI on management. Vegard is responsible for the National Top Management Program in Healthcare together with Bjørn Erik Mørk and Academic Coordinator for the Executive MBA Digital track.
Vegard has recently published in journals like Harvard Business Review, Strategic Organization, and Journal of Organization Design and his research has been covered in national and international news media such as Forbes, Socialter, Aftenposten, Dagens Næringsliv, NRK P1, and Kapital. He is a frequently used speaker at business and academic conferences and seminars in Norway and abroad.
Vegard has 16 years of strategy consulting experience from Accenture where he has done more than 30 strategy, business development, and improvement projects for clients across digital media, telecom, and IT/high tech industries, as well as in public administration.
Vegard holds a PhD in strategic management from BI Norwegian Business School (2014). His PhD project is on governance and organization of collaborative communities within the domains of enterprise IT analytics, sustainable products and services, drug discovery, and digital marketing and communication. Vegard also holds a “Siviløkonom” (1998) and Master of Science in Strategy (1999) degrees from the BI Norwegian Business School.
Publications
Reinsberger, Kathrin; Kolbjørnsrud, Vegard & Mehner, Barbara (2026)
Deliberate exploratory search in technology innovation: Discovering and developing need-solution pairs
Innovation involves matching needs and solutions to form need–solution pairs (NSPs). This study investigates how organizations systemically identify and develop NSPs when searching for novel applications of existing technologies through technology-market linking—a critical yet underexplored process in strategy and innovation research. Using a multiple case study design, we analyze four innovation projects drawing on 306 expert interviews, 89 innovation proposals, and longitudinal data from diaries and retrospective interviews with 18 search agents. Our findings show that searchers engage in recurring learning practices to acquire knowledge about unmet needs, potential solutions, and how they co-evolve. These practices structure the integration of different types of knowledge over time, giving rise to four distinct search patterns that guide the direction and evolution of innovation efforts. With this study, we advance research on problem solving in innovation by unpacking how NSPs can be deliberately discovered and developed through exploratory search, rather than emerging solely from spontaneous or serendipitous encounters. We expand the literature on organizational search and learning by empirically documenting the micro-level learning processes and behaviors enabling the dynamic coupling of need and solution spaces. Finally, we contribute to the open innovation perspective by demonstrating how external knowledge critically shapes emerging technology–market combinations.
Reinsberger, Kathrin; Kolbjørnsrud, Vegard & Mehner, Barbara (2026)
Deliberate exploratory search in technology innovation: Discovering and developing need-solution pairs
Innovation involves matching needs and solutions to form need–solution pairs (NSPs). This study investigates how organizations systemically identify and develop NSPs when searching for novel applications of existing technologies through technology-market linking—a critical yet underexplored process in strategy and innovation research. Using a multiple case study design, we analyze four innovation projects drawing on 306 expert interviews, 89 innovation proposals, and longitudinal data from diaries and retrospective interviews with 18 search agents. Our findings show that searchers engage in recurring learning practices to acquire knowledge about unmet needs, potential solutions, and how they co-evolve. These practices structure the integration of different types of knowledge over time, giving rise to four distinct search patterns that guide the direction and evolution of innovation efforts. With this study, we advance research on problem solving in innovation by unpacking how NSPs can be deliberately discovered and developed through exploratory search, rather than emerging solely from spontaneous or serendipitous encounters. We expand the literature on organizational search and learning by empirically documenting the micro-level learning processes and behaviors enabling the dynamic coupling of need and solution spaces. Finally, we contribute to the open innovation perspective by demonstrating how external knowledge critically shapes emerging technology–market combinations.
Kolbjørnsrud, Vegard (2023)
Designing the Intelligent Organization: Six Principles for Human-AI Collaboration
This article presents principles and practical guidelines for how managers can succeed in growing the intelligence of their organizations by harnessing the complementary strengths of humans and artificial intelligence (AI). Organizational intelligence is the ability of collectives of intelligent human and digital actors to solve problems and adapt. Six principles for human-AI collaboration in organizations are explored—addition, relevance, substitution, diversity, collaboration, and explanation—and how they play out in leading organizations is discussed. Finally, practical guidelines are outlined for how leaders can enable their organizations to successfully make the change.
This article presents principles and practical guidelines for how managers can succeed in growing the intelligence of their organizations by harnessing the complementary strengths of humans and artificial intelligence (AI). Organizational intelligence is the ability of collectives of intelligent human and digital actors to solve problems and adapt. Six principles for human-AI collaboration in organizations are explored—addition, relevance, substitution, diversity, collaboration, and explanation—and how they play out in leading organizations is discussed. Finally, practical guidelines are outlined for how leaders can enable their organizations to successfully make the change.
Intelligent teknologi brukes i stadig større grad til å støtte problemløsing i organisasjoner. I denne studien utforsker vi hva som skjer med komplekse problemløsingsprosesser når kunstig intelligens introduseres og hvordan samhandlingen menneske-maskin kan organiseres. Vi følger bruken av programvaren Spacemaker i tidligfase eiendomsutvikling i to store nordiske virksomheter; OBOS og Nordr. Programvaren brukes til å støtte, akselerere og forbedre design- og analysearbeidet. Konkret fører dette til flere og raskere iterasjoner, åpnere og mer involverende prosesser og grundigere vurderinger på et tidligere stadium. Dette øker den kollektive intelligensen i team av mennesker og maskiner utover det hver av partene kan klare på egen hånd. Vi diskuterer hvilke implikasjoner funnene våre har for innføring av teknologi, hvordan AI kan brukes til å åpne lukkede ekspertdrevne problemløsingsprosesser samt begrensingene slike systemer har og menneskers rolle i hybrid menneske-maskinsamhandling. I tillegg drøfter vi hva dette kan bety for norsk BAE-næring.
Kolbjørnsrud, Vegard & Sannes, Ragnvald (2022)
Problemløsing med kunstig intelligens: Bruk av Spacemaker i tidligfase eiendomsutvikling
Intelligent teknologi brukes i stadig større grad til å støtte problemløsing i organisasjoner. I denne studien utforsker vi hva som skjer med komplekse problemløsingsprosesser når kunstig intelligens introduseres og hvordan samhandlingen menneske-maskin kan organiseres. Vi følger bruken av programvaren Spacemaker i tidligfase eiendomsutvikling i to store nordiske virksomheter; OBOS og Nordr. Programvaren brukes til å støtte, akselerere og forbedre design- og analysearbeidet. Konkret fører dette til flere og raskere iterasjoner, åpnere og mer involverende prosesser og grundigere vurderinger på et tidligere stadium. Dette øker den kollektive intelligensen i team av mennesker og maskiner utover det hver av partene kan klare på egen hånd. Vi diskuterer hvilke implikasjoner funnene våre har for innføring av teknologi, hvordan AI kan brukes til å åpne lukkede ekspertdrevne problemløsingsprosesser samt begrensingene slike systemer har og menneskers rolle i hybrid menneske-maskinsamhandling. I tillegg drøfter vi hva dette kan bety for norsk BAE-næring.
Digitalisering er på full fart inn i bygg- og anleggsnæringen (BA-næringen). Prosjektstyring, konstruksjon og byggeprosess digitaliseres og de analoge byggetegningene erstattes av interaktive, digitale modeller som kan deles på tvers av fag og organisasjoner. Ny teknologi gir mange muligheter for å organisere arbeidet annerledes. Tungt og farlig arbeid kan blant annet erstattes av roboter. Digitale tvillinger av byggerier kan bidra til mange muligheter med tanke på effektivisering av byggeprosessen, forenkling av drift og vedlikehold og støtte til mye annen teknologi som for eksempel bruk av roboter. Denne artikkelen fokuserer på muligheter og betingelser for mer bruk av roboter i BA-næringen. Robotisering i BA-næringen forventes å mer enn doble seg allerede innen 2023 til $166 millioner, så her går utviklingen veldig fort.1 Innovasjoner i semi- og fullautomatiserte roboter kan hjelpe BA-næringen til å bygge mer effektivt (mindre sløsing, til lavere kostnader, raskere) og sikrere. Spørsmålet er hvordan robotisering kan gi gevinster og hva som er betingelsene for å utnytte potensialet som ligger i automatisering og robotisering av byggeprosess. Vi vil derfor undersøke hva roboter kan brukes til i byggeprosessen og hva som kreves av omstilling for å utnytte og få effekter av roboter. Vi har gjort en undersøkelse av hvilke type roboter som finnes som kan støtte verdiskapingen i byggeprosessen. Studien baserer seg på gjennomgang av litteratur om robotisering med spesielt fokus på BA-næringen.
Digitalisering er på full fart inn i bygg- og anleggsnæringen (BA-næringen). Prosjektstyring, konstruksjon og byggeprosess digitaliseres og de analoge byggetegningene erstattes av interaktive, digitale modeller som kan deles på tvers av fag og organisasjoner. Ny teknologi gir mange muligheter for å organisere arbeidet annerledes. Tungt og farlig arbeid kan blant annet erstattes av roboter. Digitale tvillinger av byggerier kan bidra til mange muligheter med tanke på effektivisering av byggeprosessen, forenkling av drift og vedlikehold og støtte til mye annen teknologi som for eksempel bruk av roboter. Denne artikkelen fokuserer på muligheter og betingelser for mer bruk av roboter i BA-næringen. Robotisering i BA-næringen forventes å mer enn doble seg allerede innen 2023 til $166 millioner, så her går utviklingen veldig fort.1 Innovasjoner i semi- og fullautomatiserte roboter kan hjelpe BA-næringen til å bygge mer effektivt (mindre sløsing, til lavere kostnader, raskere) og sikrere. Spørsmålet er hvordan robotisering kan gi gevinster og hva som er betingelsene for å utnytte potensialet som ligger i automatisering og robotisering av byggeprosess. Vi vil derfor undersøke hva roboter kan brukes til i byggeprosessen og hva som kreves av omstilling for å utnytte og få effekter av roboter. Vi har gjort en undersøkelse av hvilke type roboter som finnes som kan støtte verdiskapingen i byggeprosessen. Studien baserer seg på gjennomgang av litteratur om robotisering med spesielt fokus på BA-næringen.
Kolbjørnsrud, Vegard (2018)
Collaborative organizational forms: on communities, crowds, and new hybrids
In this article, I examine collaborative organizational forms in terms of their institutional properties and the mechanisms by which they solve the universal problems of organizing. Based on three ideal forms—markets, hierarchies, and communities—I propose a framework for analyzing and mapping organizational forms. The framework expands our understanding of the ideal forms and derives a set of analytically distinct hybrids at the intersection of the ideal types. The framework also specifies the main conditions that drive organizations to change form and move toward another hybrid or ideal form. The theoretical review of collaborative organizational forms is illustrated and informed by three empirical cases of new forms within the domains of drug discovery, software development, as well as professional services. Further, I discuss plural forms and the role of hierarchy in collaborative forms. Finally, I outline implications for research and practice in terms of comparative analysis of organizational forms, the role of crowds, as well as the interplay between new technologies and new organizational forms.
Evolving at an unprecedented pace, digital technologies promise to automate not only labor-intensive and repetitive work, but also the traditional and exclusive domain of educated humans—knowledge work. This is evident in the new ways of reaching customers and coordinating activities, as well as in the fact that companies conducting a business built on the new technologies now constitute the world’s largest enterprises. The presence and evolution of these companies challenge established divisions of labor between man and machine, and almost casually redraws the boundaries between industries. Machine learning and analytics challenge the managers leading and the managerial scientists studying organizations. Everybody says they want to be data driven—but what does a company really need to do to achieve that?
This article will explore the managerial, organizational, and strategic implications of allowing an ever increasing number of organizational decisions to be taken not by managers employing intuition and common sense, but by algorithms and learning systems based on massive amounts of data derived from electronically based customer interactions. We argue that these companies can be thought of as “intelligent enterprises” with enhanced abilities to sense, comprehend, act, learn and explain (SCALE) their environment and their interactions with it. To acquire these capabilities, managers need to cede authority over some decisions while acquiring new capabilities and roles for themselves.
Kolbjørnsrud, Vegard (2018)
Collaborative organizational forms: on communities, crowds, and new hybrids
In this article, I examine collaborative organizational forms in terms of their institutional properties and the mechanisms by which they solve the universal problems of organizing. Based on three ideal forms—markets, hierarchies, and communities—I propose a framework for analyzing and mapping organizational forms. The framework expands our understanding of the ideal forms and derives a set of analytically distinct hybrids at the intersection of the ideal types. The framework also specifies the main conditions that drive organizations to change form and move toward another hybrid or ideal form. The theoretical review of collaborative organizational forms is illustrated and informed by three empirical cases of new forms within the domains of drug discovery, software development, as well as professional services. Further, I discuss plural forms and the role of hierarchy in collaborative forms. Finally, I outline implications for research and practice in terms of comparative analysis of organizational forms, the role of crowds, as well as the interplay between new technologies and new organizational forms.
Evolving at an unprecedented pace, digital technologies promise to automate not only labor-intensive and repetitive work, but also the traditional and exclusive domain of educated humans—knowledge work. This is evident in the new ways of reaching customers and coordinating activities, as well as in the fact that companies conducting a business built on the new technologies now constitute the world’s largest enterprises. The presence and evolution of these companies challenge established divisions of labor between man and machine, and almost casually redraws the boundaries between industries. Machine learning and analytics challenge the managers leading and the managerial scientists studying organizations. Everybody says they want to be data driven—but what does a company really need to do to achieve that?
This article will explore the managerial, organizational, and strategic implications of allowing an ever increasing number of organizational decisions to be taken not by managers employing intuition and common sense, but by algorithms and learning systems based on massive amounts of data derived from electronically based customer interactions. We argue that these companies can be thought of as “intelligent enterprises” with enhanced abilities to sense, comprehend, act, learn and explain (SCALE) their environment and their interactions with it. To acquire these capabilities, managers need to cede authority over some decisions while acquiring new capabilities and roles for themselves.
Kolbjørnsrud, Vegard; Amico, Richard & Thomas, Robert J. (2017)
Partnering with Al: How organizations can win over skeptical managers
Purpose: According to the authors’ research, while top-level executives look forward to the potential of artificial intelligent systems in their firms, line managers are much more skeptical. This article advises on implementation strategy. Design/methodology/approach: Drawing on findings from Accenture’s survey of 1,770 managers in 14 countries and interviews with 37 senior executives responsible for digital transformation, the authors have identified patterns in managers’ attitudes and offer strategies for effective adoption of the new technology. Findings: When managers have a say and involvement in initial training efforts, they gain a sense of ownership throughout the learning process as well as familiarity with intelligent systems. Practical implications: The introduction of AI will put a premium on “soft” skills such as collaboration, creativity and good judgment, which may be just as important, if not more important, than technical skills in the future. Originality/value: The emergence of artificial intelligence (AI) promises to transform the nature of work and the relationship among human beings and machines in organizations. When the authors asked whether leaders would be comfortable with AI monitoring and evaluating their work, 42 percent of the top managers in our survey strongly agreed, while only 15 percent of first-line managers shared the same sentiment.” This research discovered that top executives cannot assume that mid- and lower-level managers will share their appreciation for AI.
Kolbjørnsrud, Vegard (2017)
Agency problems and governance mechanisms in collaborative communities
Collaborative communities—where participants collaboratively solve problems and integrate their contributions—are increasingly popular organizational forms in a wide variety of domains. As with any cooperative effort, communities involve differential interests and information asymmetries, creating potential agency problems. I undertake an exploratory multiple-case study of four communities within the domains of enterprise information technology, sustainable products and services, drug discovery, and digital marketing and communication. I find that agency relationships in the collaborative communities are characterized by three distinct multiple-agency structures: commons, team production, and brokering. These are governed by four main categories of mechanism: (1) mutual monitoring, enabling self-regulation and peer-based control; (2) membership restrictions, regulating admission to the community; (3) values and rules, guiding member action and collaboration; and (4) property rights and incentives, regulating rights to community resources and distribution of rewards. I also identify contingencies between governance mechanisms and agency problems.
Kolbjørnsrud, Vegard (2017)
Kunstig intelligens og lederens nye jobb
Magma forskning og viten, 2017(6) , s. 33-42.
Kunstig intelligens (Artificial Intelligence, AI), IT-applikasjoner som kan sanse, forstå, handle og lære, forventes å få stor innvirkning på alle deler av arbeidslivet, også for ledere på alle nivåer. Denne studien fokuserer på hvordan kunstig intelligens kommer til å påvirke lederes jobb, og hvordan ledere og virksomheter kan forberede seg. Den er basert på en spørreundersøkelse blant 1 770 ledere i 14 land og intervjuer med 37 toppledere med ansvar for digitalisering. Vi finner at ledere bruker over halvparten av tiden sin på administrative oppgaver som intelligente maskiner kan gjøre for dem i fremtiden. Etter hvert som administrative rutineoppgaver automatiseres, blir oppgaver som krever dømmekraft, kreativitet og sosial kompetanse, stadig viktigere. Intelligente systemer vil spille en viktig rolle her også, men da som støtte, korrektiv og sparringpartner. Vi finner signifikante variasjoner i holdninger og forventninger til AI på tvers av ledernivåer og geografi, noe som kan få betydelige implikasjoner for hvordan virksomheter kan og bør ta i bruk slike teknologier. Nordiske ledere er blant de mest skeptiske til å ta i bruk og stole på kunstig intelligens. Implikasjonene oppsummeres i fem konkrete råd til ledere og virksomheter.
Kolbjørnsrud, Vegard; Amico, Richard & Thomas, Robert J. (2017)
Partnering with Al: How organizations can win over skeptical managers
Purpose: According to the authors’ research, while top-level executives look forward to the potential of artificial intelligent systems in their firms, line managers are much more skeptical. This article advises on implementation strategy. Design/methodology/approach: Drawing on findings from Accenture’s survey of 1,770 managers in 14 countries and interviews with 37 senior executives responsible for digital transformation, the authors have identified patterns in managers’ attitudes and offer strategies for effective adoption of the new technology. Findings: When managers have a say and involvement in initial training efforts, they gain a sense of ownership throughout the learning process as well as familiarity with intelligent systems. Practical implications: The introduction of AI will put a premium on “soft” skills such as collaboration, creativity and good judgment, which may be just as important, if not more important, than technical skills in the future. Originality/value: The emergence of artificial intelligence (AI) promises to transform the nature of work and the relationship among human beings and machines in organizations. When the authors asked whether leaders would be comfortable with AI monitoring and evaluating their work, 42 percent of the top managers in our survey strongly agreed, while only 15 percent of first-line managers shared the same sentiment.” This research discovered that top executives cannot assume that mid- and lower-level managers will share their appreciation for AI.
Kolbjørnsrud, Vegard (2017)
Agency problems and governance mechanisms in collaborative communities
Collaborative communities—where participants collaboratively solve problems and integrate their contributions—are increasingly popular organizational forms in a wide variety of domains. As with any cooperative effort, communities involve differential interests and information asymmetries, creating potential agency problems. I undertake an exploratory multiple-case study of four communities within the domains of enterprise information technology, sustainable products and services, drug discovery, and digital marketing and communication. I find that agency relationships in the collaborative communities are characterized by three distinct multiple-agency structures: commons, team production, and brokering. These are governed by four main categories of mechanism: (1) mutual monitoring, enabling self-regulation and peer-based control; (2) membership restrictions, regulating admission to the community; (3) values and rules, guiding member action and collaboration; and (4) property rights and incentives, regulating rights to community resources and distribution of rewards. I also identify contingencies between governance mechanisms and agency problems.
Kolbjørnsrud, Vegard (2017)
Kunstig intelligens og lederens nye jobb
Magma forskning og viten, 2017(6) , s. 33-42.
Kunstig intelligens (Artificial Intelligence, AI), IT-applikasjoner som kan sanse, forstå, handle og lære, forventes å få stor innvirkning på alle deler av arbeidslivet, også for ledere på alle nivåer. Denne studien fokuserer på hvordan kunstig intelligens kommer til å påvirke lederes jobb, og hvordan ledere og virksomheter kan forberede seg. Den er basert på en spørreundersøkelse blant 1 770 ledere i 14 land og intervjuer med 37 toppledere med ansvar for digitalisering. Vi finner at ledere bruker over halvparten av tiden sin på administrative oppgaver som intelligente maskiner kan gjøre for dem i fremtiden. Etter hvert som administrative rutineoppgaver automatiseres, blir oppgaver som krever dømmekraft, kreativitet og sosial kompetanse, stadig viktigere. Intelligente systemer vil spille en viktig rolle her også, men da som støtte, korrektiv og sparringpartner. Vi finner signifikante variasjoner i holdninger og forventninger til AI på tvers av ledernivåer og geografi, noe som kan få betydelige implikasjoner for hvordan virksomheter kan og bør ta i bruk slike teknologier. Nordiske ledere er blant de mest skeptiske til å ta i bruk og stole på kunstig intelligens. Implikasjonene oppsummeres i fem konkrete råd til ledere og virksomheter.
Kolbjørnsrud, Vegard; Amico, Richard & Thomas, Robert J. (2016)
How Artificial Intelligence Will Redefine Management
Harvard Business Review,
Kolbjørnsrud, Vegard; Amico, Richard & Thomas, Robert J. (2016)
How Artificial Intelligence Will Redefine Management
Harvard Business Review,
Kolbjørnsrud, Vegard (2023)
BI-forsker: Slik vil kunstig intelligens forandre lederrollen, 3 råd til ledere
[Journal]
Kolbjørnsrud, Vegard & Bang, Tor (2023)
Kunstig intelligens i utdanning: Hvordan bør vi forholde oss til AI? Podkast i serien "Aktualitet og samfunn"
De som skal lykkes med å tiltrekke seg talentene, må tilby fleksibilitet – én løsning passer ikke alle. Lederne må evne å skape gode fellesskap også i en digital, grenseløs arbeidshverdag.
Kolbjørnsrud, Vegard; Lund, Kristin Skogen & Borgen, Thomas (2022)
De som skal lykkes med å tiltrekke seg talentene, må tilby fleksibilitet – én løsning passer ikke alle. Lederne må evne å skape gode fellesskap også i en digital, grenseløs arbeidshverdag.
Kolbjørnsrud, Vegard (2021)
Roboter overtar bankene
[Journal]
Kolbjørnsrud, Vegard (2021)
Roboter overtar bankene
[Journal]
Kolbjørnsrud, Vegard (2019)
Fra stive strukturer til raske team
[Journal]
Kolbjørnsrud, Vegard (2019)
- Kan vi forvente at offentlig sektor blir smidig og smart?
[Internet]
Kolbjørnsrud, Vegard (2019)
Designe smidige og smarte organisasjoner
[Internet]
Kolbjørnsrud, Vegard (2019)
Hvordan designe smidige og smarte organisasjoner?
[Internet]
Kolbjørnsrud, Vegard (2019)
Slik gjør du organisasjonen smidigere
[Internet]
Kolbjørnsrud, Vegard (2019)
Samfunnet trenger smidigere bedrifter der ansatte får mer frihet
[Journal]
Kolbjørnsrud, Vegard (2019)
Fra stive strukturer til raske team
[Journal]
Kolbjørnsrud, Vegard (2019)
- Kan vi forvente at offentlig sektor blir smidig og smart?
[Internet]
Kolbjørnsrud, Vegard (2019)
Designe smidige og smarte organisasjoner
[Internet]
Kolbjørnsrud, Vegard (2019)
Hvordan designe smidige og smarte organisasjoner?
[Internet]
Kolbjørnsrud, Vegard (2019)
Slik gjør du organisasjonen smidigere
[Internet]
Kolbjørnsrud, Vegard (2019)
Samfunnet trenger smidigere bedrifter der ansatte får mer frihet
[Journal]
Kolbjørnsrud, Vegard (2018)
How artificial intelligence will change leadership
[Internet]
Kolbjørnsrud, Vegard (2018)
Digitalisering utfordrer lederne i kraftnæringen
[Internet]
Kolbjørnsrud, Vegard (2018)
Emerging Economies 'More Open' To AI For Business Management
[Journal]
Kolbjørnsrud, Vegard (2018)
Oslo Legal Tech Meetup: Hvilke applikasjonsområder har kunstig intelliges for jus?
[Internet]
Kolbjørnsrud, Vegard (2018)
Hvordan endrer kunstig intelligens lederjobben?
[Internet]
Kolbjørnsrud, Vegard (2018)
Mon RH est une machine
[Journal]
Kolbjørnsrud, Vegard (2018)
Digitization opens vast opportunities for agile businesses, but most are rigged for stability and control
