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02.07.202608:29 विदेशी मुद्रा विश्लेषण और समीक्षा: The Second Wave of the AI Boom: Which Software Companies (SaaS) Will Monetize the Technology in 2027?

Brief Overview: Will Crypto Become a New "Safe Haven"?

The corporate software market (SaaS) is undergoing a comprehensive structural restructuring as it shifts from purchasing basic AI hardware to directly monetizing ready-made business solutions. Following the significant correction in technology sector valuations in the first half of 2026, when investors began demanding tangible returns from deploying generative models, the focus shifted to companies capable of converting technology into net profit. The widespread adoption of autonomous AI agents is reshaping established business models, forcing the entire software sector to transition rapidly to new pricing models.

Key Growth Factors:

• Collapse of Per-Seat Pricing and Shift to Performance-Based Payment: The traditional model of selling software "per seat" is rapidly becoming ineffective as autonomous AI agents begin to replace humans at the task execution level. Software providers are compelled to adopt hybrid schemes and transition to usage- or outcome-based pricing. More than 55% of cloud companies are already restructuring their pricing models due to high volatility in client budgets, which temporarily constrains growth margins.
• Scaling Ecosystems of Autonomous Agents (Agentic AI): Major players in the sector are moving from simple AI assistants to launching full-fledged execution systems. Business process automation is reaching record levels: specialized AI modules in major CRM systems autonomously close tens of thousands of deals, increasing the segment's annual recurring revenue (ARR) to $850–$900 million. Clients are willing to extend long-term contracts only with software providers that deliver a real 45–50% reduction in processing times.
• Compression of Multiples as an Entry Point for Long-Term Capital: Market sober reflection has led to a significant compression of valuation multiples for software companies. Average business valuations relative to revenue have fallen into a conservative range of 1.2x–4.0x, making the SaaS sector fundamentally attractive after a prolonged period of overheating. Companies with strong balance sheets and ready AI products continue to maintain operating margins above 30%, proving their ability to absorb high computational costs.

Forecast: Which Software Companies (SaaS) Will Monetize Technology in 2026–2027?

Answer: In 2026, financial results will be restrained due to the transition of business models; in 2027, explosive growth in net profit will begin for automation leaders.

The restructuring of the pricing policy and the launch of autonomous platforms will create a sustainable base for the second wave of the technology rally. In the medium term, this software monetization cycle will be divided into two phases:

• 2026 Horizon (Restructuring and Adaptation): By the end of the year, the financial performance of SaaS giants will remain under pressure during the transitional period. The annual revenue of IT automation leaders will be recorded within a narrow range of $14.2–$14.6 billion, while targeted revenue benchmarks for the pure AI segment will be around $1.3 billion. Investors will price in the risk of margin decline due to high infrastructure costs, keeping most software companies' shares within a broad horizontal corridor.
• 2027 Horizon (Full-Scale Monetization): By the beginning of 2027, new performance-based payment models will begin generating steadily increasing cash flows. Focus will shift to tech giants whose aggregate revenue will approach $41–$43 billion as AI products mature. Companies that successfully implement AI controllers and next-generation corporate databases will demonstrate accelerated profit growth, attracting capital back to the sector and pushing the stock prices of quality SaaS issuers out of the depressed zone.

*यहां पर लिखा गया बाजार विश्लेषण आपकी जागरूकता बढ़ाने के लिए किया है, लेकिन व्यापार करने के लिए निर्देश देने के लिए नहीं |

Dean Leo,
Analytical expert of InstaSpot
© 2007-2026

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