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McKinsey & Company

Industry overview

Impact detail

Information services/

New business models may emerge, as incumbents offer access to insights based on their underlying data assets; focus on new modes of consumption and discovery/ingestion of data is likely to grow.

Adoption of gen AI use cases (incl. co-pilots, auto-generation, personalization etc.) changes how customers are likely to engage and use solutions.

Collaboration and communication

Re-imagining of core product, increased accessibility, and broadening of addressable user base, including the rise of semi-expert users, alters how customers leverage the software and their likelihood of switching.

Content creation

Automation streamlines staffing and reshapes customer engagement via gen AI assistants. At the same time, reductions in the number of “expert” users along with growing in-house development and rates of switching vendors will counteract some of the impact.

Customer service

New use cases such as the automation of labor-intensive efforts and workflows, as well as low switching rates and the rise of semi-expert users, will drive higher usage of cloud-based solutions. The relative ease of shifting to the cloud will also quicken the pace of migration from on-premises solutions.

Customer relationship management (CRM) and enterprise resource management (ERM)

Gen AI changes the mandate and unique value of ad-hoc software by taking over querying, forcing incumbents to re-invent themselves against platform players.

Analytics/visualization

Gen AI provides an opportunity for incumbents to re-invent how they handle traditional (eg robotic process automation) tasks while exploring more end-to-end AI automation tasks and becoming an AI automation platform.

Enterprise automation

This AI sub-segment is likely to see continued investment and innovation as companies build gen AI tools; existing data solutions may continue to be leveraged if they can stay competitive.

Data and AI development

Rising demand for gen AI and AI features in application development, but existing solutions are likely to be leveraged if they can stay competitive.

Application development
and integration

System infrastructure

Smaller impact to OS, computing, and IT Services due to their essential nature to technology operations, but key innovations are likely to continue.

Cybersecurity

As gen AI increases the level of threats, including AI-generated deep fakes, providers will need to implement new features for prevention and remediation.

Net impact

Software categories

Impact detail

Source: IDC, McKinsey Gen AI CIO Survey, October 2023 (n = 250), McKinsey analysis

Source: IDC, McKinsey analysis

130

Content creation

39

Collaboration and communication

118

Data and AI development

57

Application development

32

Analytics/visualization

93

Cybersecurity

18

Enterprise automation 

129

System infrastructure

31

Customer service

120

Information services/

268

Customer relationship management (CRM) and Enterprise resource management (ERM)

Software categories by market size and level of disruption/reimagining

Industry overview

Gen AI will disrupt the overwhelming majority of the software market, but its relative impacts will differ across a wide range of industry categories.

Level of disruption/reimagining

Very High

Medium

High

Med-High

Market size, 2023, $ billion