Software Investments in a Gen AI World 

February 2025 

The Transition of SaaS to the Age of AI

The concept of Enterprise SaaS has undergone a profound transformation over the years, propelled by the revolutionary power of AI. Each generation, from traditional software to AI 1.0 and the current AI 2.0, represents a significant leap in how software interacts with data, intelligence, and automation. These advancements are reshaping the competitive landscape of modern business solutions, inspiring us with the potential of AI in the SaaS industry.

First, there were enterprise SaaS roles pioneered by Salesforce and Adobe and based on rule-based systems that acted much like static databases with strict separations between data and code. Then came AI 1.0, which included machine learning to analyze vast volumes of data to make predictions, automating most decision-making processes. Now, with AI 2.0, things are about to get interesting: autonomous, agentic solutions powered by large language models from companies such as OpenAI and Anthropic. These are the capabilities now making software truly dynamic, synthesizing data, acting as co-pilots in real-time, and even learning continuously of, which wasn't possible with earlier forms. While AI 1.0 and AI 2.0 share some technological foundations, the new generation makes AI more accessible and cost-effective, enabling startups to scale faster with higher returns than traditional SaaS.

Software has long been one of the most profitable technology sectors, but as it becomes more commoditized, its broader role in driving technological revolutions is becoming clearer. AI-powered SaaS is now influencing industries far beyond software, from robotics and biotechnology to manufacturing and even space exploration.

However, the rapid rise of AI is also changing the nature of opportunities in software. With so many companies adopting AI, venture-scale opportunities are becoming harder to find—unless they have strong network effects that create lasting competitive advantages. The SaaS market itself has grown crowded, with businesses now juggling an average of 371 different applications across areas like robotic process automation (RPA), business intelligence, and cybersecurity.

AI is expected to lower software development costs, but its real impact goes beyond just savings. It’s fundamentally reshaping how businesses use technology—allowing software to learn, adapt, and operate with greater autonomy. This shift is creating new opportunities but also new challenges for companies navigating an AI-driven future. AI-first companies have a major advantage in this new landscape. With cutting-edge technology and access to top talent, they can iterate faster and build more efficient solutions, giving them a competitive edge over traditional SaaS firms.

Historically, SaaS companies enjoyed high profit margins because developer talent was scarce, and software adoption was still in its early stages. This created a winner-take-all environment where early movers dominated the market. But as AI levels the playing field, making software development faster and more accessible, SaaS margins and valuations are shifting. Companies will need to rethink their strategies to stay competitive in an AI-powered world.

The Disruption of Traditional SaaS Models

For years, SaaS companies have focused on markets with the biggest revenue potential, often steering clear of smaller or niche industries where the costs outweighed the returns. The traditional SaaS model relied on selling software licenses or subscriptions on a per-seat basis, requiring heavy investments in sales, marketing, and customer support. As a result, industries with lower software budgets or limited tech adoption were largely overlooked.

AI is changing that. By automating labor-intensive tasks like sales, marketing, customer service, and operations, AI dramatically increases efficiency and lowers costs. This shift is making it possible for Value-added SaaS (VSaaS) companies to extract more value per customer, turning previously unappealing markets into viable opportunities. With AI-driven automation, SaaS providers can scale faster, offer better services, and reach industries that were once out of reach.

One of the biggest shifts in SaaS today is the rise of “Service-as-a-Software.” Unlike traditional software, which primarily relies on pattern matching, AI-powered workflows—often called “agentic workflows”—can reason through complex tasks with minimal human input. This means SaaS is evolving from static tools into intelligent, adaptive systems capable of solving real-world problems more effectively.

As software adoption becomes nearly universal and data center networks expand, the next big opportunities will come from industries and regions that have been largely ignored by traditional tech companies. The intersection of AI and infrastructure growth is paving the way for innovative business models and fresh applications of software.

AI is also opening doors for businesses that were once considered too small or low-margin for SaaS solutions.Small scale businesses such as dry cleaning, chiropractic offices, and veterinary clinics are now benefiting from AI automation. Low-revenue businesses like laundromats can use AI-driven automation to reduce labor costs, while higher-revenue businesses like veterinary clinics can integrate AI copilots to boost productivity. By tailoring AI solutions to specific operational needs, software is becoming more accessible to a wider range of businesses.

While some worry that AI could make SaaS obsolete, the reality is more nuanced. AI isn’t replacing SaaS—it’s reshaping and repurposing it. While highly specialized, niche software may become redundant, AI is more likely to replace certain modules within complex systems rather than entire platforms. In many cases, AI is actually filling gaps that were previously too costly or difficult to address, strengthening the SaaS ecosystem rather than dismantling it.

As software development becomes more commoditized, every market niche is maturing and saturating. The democratization of AI-driven software is making critical services like education, healthcare, and legal assistance more accessible than ever. This shift is not only transforming industries but also ensuring that advanced technology reaches a broader audience.

During the early cloud era, SaaS companies sold access to software tools, leaving customers responsible for figuring out how to use them effectively. This model was built around per-seat pricing. But AI is flipping the script—companies are no longer just selling access to software; they’re selling labor and outcomes. AI-powered businesses are moving toward per-outcome pricing, where customers pay for actual results rather than just gaining access to a tool.

The rise of AI-driven, agentic applications is lowering service costs while making AI-powered solutions more affordable. As AI continues to reshape SaaS, businesses across industries will benefit from reduced costs, increased efficiency, and entirely new revenue opportunities. The future of SaaS isn’t about replacing software—it’s about making it smarter, faster, and more accessible than ever.

AI is shifting the balance of power and creating new opportunities for both established players and emerging competitors. By democratizing software development, AI is equipping engineers worldwide with powerful tools that reduce time to market, dismantle traditional barriers to entry, and enable rapid innovation in a highly competitive industry.

One of the most game-changing shifts in tech today is the rise of AI Agents as a Service (AAaaS). These AI-powered agents go beyond traditional software delivery, offering outcome-based solutions that automate complex workflows and redefine service delivery. Instead of simply selling software, AI-first companies are providing flexible, intelligent services that integrate automation directly into business operations. This shift is rapidly transforming the SaaS ecosystem and reshaping how businesses operate.

As AI drives down software development costs, the SaaS market is becoming more competitive than ever. Lower barriers to entry mean that new players can challenge established companies—especially those that fail to adapt. Businesses that don’t embrace AI risk falling behind competitors who are using automation to optimize operations and scale faster.

At the same time, AI is unlocking new revenue opportunities for SaaS providers. Companies are embedding AI-driven agents into their platforms to handle tasks like lead generation, hyper-personalized marketing, 24/7 customer support, and automated invoicing. This new wave of Virtual SaaS (VSaaS) is more than just efficient—it strengthens customer relationships by delivering smarter, AI-powered interactions that turn casual users into long-term partners.

One of AI’s biggest advantages in SaaS is its ability to lower Customer Acquisition Costs (CAC) while boosting Lifetime Value (LTV). AI-powered voice agents can handle customer inquiries at any time, reducing the need for human sales teams and cutting acquisition expenses. At the same time, AI enhances retention by personalizing customer experiences, optimizing sales funnels, and seamlessly integrating services.

Different organizations are adopting AI at their own pace—some are making bold, AI-first moves, while others are introducing AI gradually. Enterprises are starting to shift from traditional SaaS tools like Workday and Salesforce toward custom AI-driven solutions, though the more common trend is integrating AI across different business functions. AI-powered assistants are automating tasks, improving decision-making, and providing real-time insights, completely reimagining how businesses engage with their customers.

This shift is also changing the core business model of SaaS. The traditional per-seat licensing model is losing relevance as AI automates many roles, reducing the number of employees who need direct software access. Instead, businesses are moving toward AI-powered workflows, where thin-client interfaces allow employees to manage processes by exception, focusing on strategy rather than routine tasks.

Automating repetitive development tasks means small teams can compete with enterprise-scale companies, allowing them to focus their resources on innovation, product architecture, and strategic growth. This democratization of AI is fueling a new wave of agile startups that are disrupting legacy players.

That said, while AI is advancing rapidly, skilled engineers are still essential. Large language models (LLMs) can accelerate development, but they can’t solve entirely new problems or ensure strong system architecture. The companies that succeed will be those that combine human expertise with AI fluency, using AI as a tool to enhance rather than replace human ingenuity.

In today’s world, mastering AI isn’t optional—it’s a survival skill. Businesses and developers that fully integrate AI into their operations will lead the next generation of smart, adaptive SaaS solutions, while those that delay risk becoming obsolete. AI isn’t just changing how software is built—it’s transforming how businesses interact with customers, vendors, and employees, defining the future of SaaS as we know it.

AI Changing Economic Reality: Dislocation in Software Investing

SaaS was originally built for human interaction, with intuitive interfaces and per-user pricing. Software acted as a tool, requiring manual inputs and decision-making. Today, AI is automating tasks and augmenting human capabilities within these ecosystems. While AI assists, humans still control critical decisions. Over the next decade, AI will take the lead, engaging autonomously with digital systems to optimize business processes and make real-time decisions. Human involvement will be limited to high-level oversight via intuitive interfaces.

The commodification of software and AI is fueling rapid advancements in biotechnology, robotics, additive manufacturing, and space systems—mirroring the past two decades of software-driven growth. AI is not just automating tasks but increasingly exhibiting human-like intelligence, enabling machines to sense, react, and execute operations independently.

AI is also transforming software development. Large language models (LLMs) now write, debug, and optimize code, shifting software production from a manual craft to an automated process. As AI-driven development advances, costs will plummet, accelerating deployment timelines and integrating AI seamlessly into digital infrastructure.

Unlike Moore’s Law, AI costs are declining at an even faster rate—halving approximately every four months. This rapid drop is making AI solutions more accessible, allowing startups to compete with industry giants in ways previously unimaginable.

While the traditional software market is valued at $1 trillion, AI’s impact extends far beyond, disrupting the $10 trillion global services market. SaaS 2 replaces per-user pricing with per-outcome models, shifting software from IT budgets to labor budgets. AI-powered labor solutions, such as AI-driven sales reps and customer support agents, are set to capture billions from labor-intensive industries. As AI lowers development costs and enables hyper-customization, legacy enterprise software may lose value. At the same time, AI is expanding the total addressable market by automating labor-intensive tasks, creating new opportunities.

Venture capital faces a major shakeup. Traditional VC models, reliant on funding high-growth software startups, are under pressure as AI reduces development costs and barriers to entry. Investors must pivot to funding AI-native businesses that leverage automation rather than conventional software startups.

The software industry is at an inflection point. AI is not just enhancing software, it’s redefining it. As we move from human-driven applications to AI-led automation, business models, investment strategies, and market dynamics will be fundamentally reshaped. Whether this marks the decline of traditional software businesses, or an unprecedented expansion of software’s influence depends on how AI is integrated and monetized. One thing is clear: software investing will become more nuanced in the coming years.