Most popular AI software
Popular AI software in 2026: Key trends
Foundational models and writing assistants – such as those from OpenAI, Anthropic (creator of Claude) and Grammarly – continue to be mainstays across organizations. The consistent, top-tier performance of these companies shows that each has secured a durable foothold in widely accepted, general-purpose AI use cases.
At the same time, our data indicates an increasing willingness across businesses to experiment with other specialized tools. The rapid rise of generative media platforms, such as AI-powered video service Synthesia and the audio tool ElevenLabs, signals that organizations are now pursuing higher-production-value applications and expanding their exploration of what AI can enable.
Despite experimentation with these AI-native platforms, the relative stability among AI-enabled SaaS vendors suggests that applied AI is viewed primarily as an enhancement rather than a compelling enough driver to justify the operational complexity and cost of switching platforms.
While AI investments within these tools may not be prompting mass migration, it is subtly expanding beyond user-facing applications. There is a perceptible uptick in the popularity of tools in security and infrastructure, indicating that AI is increasingly moving into backend and developer tooling and operational domains.
Data source: These insights are derived from over $30bn of global processed spend managed by Vertice in 2026.
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The need-to-knows about Vertice
Vertice’s Q1 2026 data shows that growth is strongest in AI tools that extend beyond text into multimedia and technical workflows. This includes platforms like Synthesia for video generation and ElevenLabs for realistic voice synthesis, as well as continued adoption of general-purpose tools from OpenAI and Anthropic. Increasingly, companies are selecting tools based on specific use cases rather than relying on a single AI platform.
Current spend data from Vertice shows that businesses are no longer just “testing” generative AI; they are embedding it into the core of their operations. The 78% growth in OpenAI spend and 54% for Anthropic indicate that enterprises are heavily investing in the foundational models required for large-scale automation and intelligence.
As outlined in Vertice’s 2026 Buying AI report, the biggest risks when procuring AI tools include:
- Shadow spend: 44% of AI spending occurs without procurement oversight, leading to massive budget leakage.
- Data privacy: Vendor contracts often include clauses allowing your proprietary data to be used for model training.
- AI-washing: Many vendors rebrand legacy features as "AI" to justify premium pricing without adding true value.
- Shelfware: 13% of AI applications go entirely unused, and nearly half are underutilized across the enterprise.
To secure the best possible terms and pricing on any AI tool, procurement teams must trade experimental guesswork for hard data and ironclad contract protections. This includes:
- Peer benchmarking: Use real-world market data to verify what similar organizations are actually paying, ensuring you don’t pay a "first-mover" premium on inconsistent AI pricing.
- Usage-based leverage: Shift from flat-rate licenses to milestone-based payments and volume discounts that reflect your team's actual consumption patterns.
- Strategic clauses: Protect your budget by removing auto-renewal provisions and capping annual price increases at 3-5% to prevent long-term cost creep.
- Performance & data rights: Negotiate explicit "opt-out" rights for model training to protect your IP and establish clear credits for accuracy or latency underperformance.
Utilizing an intelligent procurement platform like Vertice is essential for gaining the real-time visibility and benchmarking power needed to manage these complex AI contracts at scale.
Download the full Buying AI: The Procurement Playbook to access the definitive manual for AI negotiation and risk management.