Gen AI will disrupt the overwhelming majority of the software market, but its relative impacts will differ across a wide range of industry categories.
Market size, 2023, $ billion
Industry overview
Impact detail
Industry overview
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Information services/data aggregation
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.
Collaboration and communication
Adoption of gen AI use cases (incl. co-pilots, auto-generation, personalization etc.) changes how customers are likely to engage and use solutions.
Net impact
Content creation
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.
Net impact
Impact detail
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
Customer relationship management (CRM) and enterprise resource management (ERM)
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.
Net impact
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
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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
Data and AI development
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.
Net impact
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
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McKinsey & Company
Source: IDC, McKinsey Gen AI CIO Survey, October 2023 (n = 250), McKinsey analysis
McKinsey & Company
Source: IDC, McKinsey analysis
Level of disruption
Medium
High
Very High
Med-High
Cybersecurity
93
System infrastructure
129
Analytics/
visualization
32
Customer service
31
Enterprise automation
18
120
Information services/data aggregation
39
Collaboration and communi-cation
118
Data and AI development
57
Application develop-
ment and integration
268
Customer relationship management (CRM) and Enterprise resource management (ERM)
130
Content creation
Net impact
Net impact
Net impact
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.
Smaller impact to OS, computing, and IT Services due to their essential nature to technology operations, but key innovations are likely to continue.
System infrastructure
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Net impact
Net impact
Net impact
Net impact