Insight Partners share its AI predictions for 2025

The artificial intelligence and software investment landscape is poised for significant shifts in 2025, with investors forecasting changes that will reshape how companies develop, deploy and monetize AI technologies.

Core market dynamics: The integration of generative AI will transition from being a differentiator to becoming a standard expectation across industries.

• Companies will need to demonstrate concrete ROI and measurable business value from their AI implementations rather than simply touting AI capabilities
• Organizations will grapple with establishing sustainable pricing models for AI features as development costs continue to rise
• The emergence of agentic AI systems capable of handling complex business workflows represents a key area of anticipated breakthrough

Trust and security concerns: The widespread adoption of AI technologies will heighten focus on building user trust and maintaining robust cybersecurity measures.

• User involvement in AI system design and implementation of tight feedback loops will become crucial for building trust at scale
• Cybersecurity strategies are expected to shift back toward best-of-breed solutions to address emerging AI-specific vulnerabilities
• High-quality data needs and synthetic data generation will require increased attention from development teams

Industry transformation: Vertical SaaS solutions will continue expanding into traditionally underserved sectors.

• Education, healthcare, and legal industries are prime targets for vertical SaaS expansion
• The rise of new specialized roles like AI Engineer will reshape organizational structures
• Existing roles across industries will increasingly be augmented by AI assistants

Market conditions and investment outlook: A more favorable investment environment is expected to emerge.

• M&A activity is predicted to increase as market conditions improve
• The IPO market may see renewed activity
• Investors will prioritize founders who demonstrate resilience, customer focus, and ability to balance efficiency with growth

Technology evolution and adaptation: The development of AI capabilities will require new approaches to implementation and optimization.

• Reinforcement learning will gain increased attention as a key technology
• Companies will need to experiment with various pricing approaches for AI features
• The role of synthetic data in AI development will become increasingly important

Strategic implications: While AI advancement promises significant opportunities, success will increasingly depend on practical implementation and measurable outcomes rather than mere technological capability.