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Next year marks my 30th year in the software industry. It’s a journey that has taken me from the humblest of beginnings to witnessing the dawn of a new era powered by artificial intelligence. As a young engineer in the mid-1990s, I was immersed in building and extending in-house software systems for a manufacturing company. These systems were the organization’s lifeblood, managing everything from inventory tracking and manufacturing processes to customer relationships and human resources.
Back then, the architecture was straightforward but labor-intensive. At the heart of it all was a database, populated either by manual data entry—something most people dreaded—or by automated processes and machines. My days were filled with re-engineering data input methods to make data collection less of a chore and developing new reports to answer an ever-growing list of business questions. Despite their simplicity by today’s standards, these systems were revolutionary for their time.
Fast forward to today, and every conceivable business function has a specialized software solution. As a venture capitalist, I’ve spent the majority of my career funding companies that build these tools, which enhance worker productivity. Yet, despite their sophistication, these systems remain fundamentally similar to those I worked on decades ago: databases populated by people or machines, queried by users to make decisions. The same challenges still persist—poor data entry due to human laxity, bad data quality due to human subjectivity, and the constant need for ad-hoc reporting.
Take Salesforce, for example. Over the past decade, I’ve heard countless frustrations from users about the inefficiency of manual data input and the difficulty of extracting meaningful insights. This dissatisfaction has given rise to an entire ecosystem of companies aimed at easing data entry and retrieval; yet the core issues remain.
The Provocative Claim: Is SaaS Dead?
Recently, industry pundits have stirred the pot with declarations that “SaaS is dead.” Companies like Klarna have announced plans to replace major SaaS providers such as Salesforce and Workday with internally-built AI systems built on enterprise agentic platforms, like what Uniphore provides. On the surface, this move seems like a death knell for traditional software models. But declaring SaaS dead misses the larger narrative.
Instead, I see AI not as the demise of SaaS but as the catalyst propelling it into a new era by transforming it into something far more powerful and adaptable. This new generation of AI-enabled software is set to revolutionize industries, enhance productivity, and reshape not just the software industry but society as a whole.
From Collect and Report, to Collect and Act
The software systems of the past were “collect and report” platforms. Humans entered data, machines stored and analyzed it under human direction, and then humans acted on the output. This model was efficient for its time but is increasingly inadequate for today’s fast-paced, data-driven world. AI transforms these traditional “collect and report” systems into “collect and act” platforms. Here’s how:
- Objective and Continuous Data Collection: AI systems can autonomously collect data from various sources—emails, phone calls, sensors—without human intervention. This collection method leads to more accurate, timely, and unbiased data.
- Real-Time Analysis and Action: AI doesn’t just store data; it interprets it in real-time, identifying patterns and making decisions at a speed and scale unattainable by humans.
- Personalized User Experiences: AI adapts to individual user preferences, customizing interfaces and workflows to enhance productivity and satisfaction.
Consider the modern AI-enabled CRM. It listens to sales calls, reads emails, and updates customer profiles without a salesperson lifting a finger. It can predict customer behavior, automate follow-ups, and even close deals autonomously. This new CRM isn’t a replacement of SaaS but its evolution—a shift from static tools to dynamic, intelligent systems.
The Broader Impact: Transforming Society and the Economy
This evolution raises significant questions that extend far beyond software. If AI systems can collect data, analyze it, and act upon it without human intervention, where does it leave us as a society?
Historically, technological advancements have disrupted labor markets. The Industrial Revolution automated physical labor, displacing many jobs but also creating new opportunities. The Software Revolution of the late 20th century brought similar upheaval, automating clerical positions but spawning entirely new fields like software development and digital marketing.
The Autonomous AI Era
Today, we’re entering the Autonomous AI Era, which represents a fundamental shift. Unlike previous technological revolutions that primarily changed how humans performed work, AI has the potential to automate cognitive tasks traditionally performed by white-collar workers—data entry, basic analysis, and routine decision-making.
The Benefits: A More Efficient, Responsive World
Machine-to-machine interactions offer fundamental advantages. Businesses can expect increased productivity and efficiency with 24/7 operations, reduced operational costs, and more accurate decision-making based on richer, real-time, high-quality data. Meanwhile, customers will get instant, personalized service with consistent quality and lower prices due to reduced operational costs. Society as a whole benefits from more efficient use of resources, improved access to services, better healthcare outcomes, and enhanced environmental monitoring.
The Challenges: Workforce Displacement and Adaptation
These benefits may sound great, but they come with profound challenges as well. AI will impact the jobs of highly-educated and highly-paid knowledge workers—financial analysts, middle managers, marketers, attorneys, and healthcare administrators. The pace of change will be faster than previous transitions, leaving less time for workers and society to adapt.
As a result, we could face increases in both temporary and long-term unemployment; growing inequality as disparities between those who can adapt and those who cannot become more pronounced; and increasing social tensions as political and social unrest due to job displacement and shifting economic fortunes manifest themselves. Not to mention a need for substantial changes in education and workforce retraining programs.
Reimagining Education for the AI Age
Our educational systems will be forced to evolve to meet the needs of an economic system where autonomous machine-to-machine interactions replace the need for humans in many ways. The current focus on memorization, standardized testing, and subject-specific knowledge is insufficient for the demands of the Autonomous AI Era.
A Personal Reflection: The Road Ahead
Reflecting on my three decades in the industry, the pace of change is both exhilarating and daunting. The shift from in-house mainframes to cloud-based SaaS was significant, but the integration of AI into these systems is revolutionary. As an investor, I see immense opportunity in backing companies that leverage AI to create more adaptable and powerful software solutions.
Yet, I am also mindful of the societal implications. Businesses must navigate not just technological challenges but ethical ones—ensuring that AI is used responsibly and that the workforce is supported through this transition. The risks associated with autonomous systems—such as loss of human oversight or unintended consequences—must be carefully managed.
Embracing the Evolution
The declaration that “SaaS is dead” is an oversimplification. What we’re witnessing is not the end but the evolution of SaaS into AI-enabled adaptive software systems. These systems offer unparalleled efficiency, personalization, and real-time action. Companies that embrace this evolution will gain a competitive edge; those that do not risk obsolescence.
As for the workforce and society at large, the rise of AI is a call to adapt rather than despair. By focusing on what makes us uniquely human—creativity, empathy, and complex decision-making—we can find our place in this new landscape.
The future isn’t just about better software; it’s about understanding how machines will interact with each other and reimagining how humans and machines work together to create value. The organizations and societies that understand and embrace these shifts won’t just survive. They’ll thrive in ways we are only beginning to imagine.
In the end, the question isn’t whether humans have become obsolete but how we can harness AI to enhance our capabilities and create a more innovative, efficient society. SaaS isn’t dead. It’s evolving. It’s about time we embrace this change, prepare for its challenges, and shape the future for the betterment of all.
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