How AI is reshaping the global software landscape

Artificial intelligence (AI) is reshaping the software sector, altering competitive dynamics, lowering barriers to entry, and forcing companies to rethink how value is created and defended. As AI capabilities accelerate, investor optimism has given way to more selective scrutiny of business models and long-term resilience.

Here, Joe Toscano, CFA^®, Investment Analyst at Mirova, examines how AI is changing the software ecosystem, where risks are emerging, and which company characteristics may matter most as the cycle evolves.

Key takeaways

• AI is reshaping software business models with generative and agentic AI accelerating disruption while also expanding long-term opportunities across the sector. 
• Investor sentiment has shifted from early AI optimism to concerns about structural risks, leaving many software stocks under pressure. 
• We focus on companies best positioned to adapt and capture value, including those with deep domain expertise, strong data, vertical integration across the stack, and sustained product innovation.

Where AI is creating long-term value in software

Global software companies are entering a phase of transition as AI reshapes digital business models, presenting both opportunities and challenges. Since the start of the generative AI cycle, software stocks have been under pressure as investor sentiment has shifted from optimism about AI's potential, to heightened concerns about the structural risks threatening software companies.

Recently, AI agents have allowed anyone to access autonomous systems that can analyze, plan, and complete tasks with little human supervision. Vibe coding allows people without programming experience to create any software application they can conceptualize. Meanwhile, venture capital and private equity investors with software exposure have warned the public that many software companies will be disrupted and need their valuations cut.

The software ecosystem is complex, and AI’s impact varies across categories, offering both benefits and risks. To navigate the changing landscape, we are focusing on the fundamentals and identifying companies that are positioned to benefit from AI’s momentum. We believe that adaptation is crucial for software companies in today’s market and the firms that fail to innovate risk being outpaced by competitors.

The introduction of AI-driven innovations has lowered the barrier to entry in the software ecosystem, allowing a new generation of AI-native companies to challenge established players as well. As a result, leading software firms are prioritizing AI integration throughout their operations and product offerings to maintain relevance and drive sustained growth. AI continues to stand out as a powerful, long-term theme offering opportunities across the technology sector. Our thematic approach focuses on companies that are positioned to benefit from long-term megatrends that are reshaping our economy.

Software ecosystem segments

As AI adoption accelerates, the software landscape is becoming increasingly segmented, with outcomes diverging across subsectors. Business models built on proprietary data, mission-critical systems, and infrastructure dependencies may prove more resilient, while others face heightened disruption. Key segments of the software ecosystem include:

• System of Record (SoR): The system that helps businesses manage and store their information. It is the most defensible software subsector, as the data in the SoR is the authoritative source on which AI systems rely for training and inference1. For this reason, companies increasingly looking to integrate AI on top of their core platform.
• Application software: Designed for end-users, these programs (e.g., productivity, communication, workflow tools) are the easiest to replace with vibe coding and agents1. While seat-based pricing models face risks, firms that leverage AI can expand their market and defend pricing.
• Vertical software: Purpose-built for specific industries or niche markets, offering specialized features that often serve as a system of record. AI enhances the value of these products by leveraging industry-specific datasets, regulatory compliance, and workflows, making them strong beneficiaries of the AI landscape. However, AI-native entrants may attempt to target this category with faster or cheaper alternatives.
• Infrastructure software: The backbone of an IT system, including operating systems, databases, networking, and security tools. A clear AI winner, as AI workloads require much more network traffic, storage, cloud migration, and data warehousing and observability compared to traditional workloads1. Risks come from open-source or vendor-neutral competitors.
• Cyber security software: Designed to protect information systems and data, cybersecurity software benefits structurally from AI. AI enhances defensive capabilities, detection, prediction, and automated containment. However, AI also increases attack surfaces and lowers the barriers for cybercriminals, requiring robust defense strategies.

Leading software companies are taking varied approaches to navigating the AI transition, shaped by their data assets, platform depth, and position within enterprise workflows. Some firms embedding AI across products and operations to reinforce their competitive positioning include:

• Salesforce: A well-established provider in CRM software and business processes, Salesforce has fully embraced AI with its Agentforce platform. Its decades of enterprise data acting as a system of record is a strong competitive advantage.
• Palo Alto Networks: Offers a comprehensive suite of security products, securing IT and AI ecosystems. The company seeks to maintain its competitive edge through M&A and has embedded generative AI in network security for faster detection and response.
• Microsoft: Diversified across the AI stack, including Copilot across office products, Github for code generation, the Dynamic 365system of record, an AI-native Windows OS, a cybersecurity suite, and Azure through GPU IaaS and companies transitioning to the cloud. Microsoft incorporates OpenAI into its service offering and hosts them as a client.

Responsible AI practices and ethical governance

The deployment of AI inevitably raises major questions regarding ethics, transparency, and governance. Its impact on work models, data management, and algorithmic biases necessitates a rigorous framework to ensure that it contributes to sustainable and inclusive progress.

We participate in collective initiatives and engage with companies directly to implement policies and mechanisms to ensure the ethical development and application of AI, guided by respect for human rights and the principle of leaving no one behind. We specifically ask that companies implement, demonstrate, and publicly disclose:

• A set of ethical principles that guide the company’s development, deployment, and/or procurement of AI tools;
• Strong AI governance and oversight across the value chain of AI development and use;
• How these responsible AI principles are implemented via specific tools and programs of action relevant to the company’s business model, including on the product and service level;
• Impact assessment processes applied to AI, emphasizing human rights impact assessments (HRIAs), especially in high-risk use cases.