Human efforts have long been the basis of technology services. Programmers are system integrators who create algorithms and data managers deploy infrastructure, and consultants who optimize business processes. However, the advent of artificial intelligence (AI) is reconstructing this landscape by shifting its focus from human-driven services to AILED software. Instead of relying on large teams of human experts, businesses are increasingly adopting platforms and tools powered by AI to automate complex tasks that previously automated immunity was thought to be immunized. The traditional software As-as-asssssssss-service (SAAS) model has already disrupt the world of enterprise IT by replacing expensive on-premises software with cloud-based applications. In this model, SAAS providers managed the database remotely, and businesses moved from per-software sheet payments to subscription fee payments, driving an increase in annual repeat revenue (ARR). For nearly 20 years, SaaS has dominated the world of technology. Today, AI is further driving this paradigm by transforming services once designed for human use into fully autonomous software solutions. This shift, often referred to as “service as software,” illustrates a fundamental shift in the way companies adopt technology. Unlike traditional SaaS, which complements human workers, these new AI-driven tools replace labor-intensive processes and produce results with minimal human intervention. AI-driven systems such as Harvey AI in the legal and compliance sector can now analyze case law and generate legal briefs to replace the work of research assistants. Similarly, AI chatbots and virtual agents have revolutionized customer support by processing a significant amount of queries without human involvement. Tools such as Open AI’s Code Interpreter have changed the industry’s landscape focused on data analytics and business intelligence by automating processes that once required manual data manipulation. Essentially, “Services as Software” eliminates the human-driven processes that are usually associated with SaaS and replaces them with full stack, AI-driven automation that delivers the same results.
Several factors have accelerated this shift towards AI-driven automation. Rapid advances in AI, particularly large-scale language models (LLMS) and generation AI, have made it possible for software to organize, infer, and execute tasks that were once human domain. Democratization of AI also plays an important role. Open source AI models and API-based solutions allow businesses of all sizes to access cutting-edge automation, but previously only large companies could access such advanced technologies. For example, Perplexity’s Deep Research launch offers enterprise calible AI services at retail prices, damaging subscriptions and paywall models, and further reducing costs. Additionally, companies are under pressure to adopt AI-driven tools to reduce operational costs, particularly in high-cost service functions that traditionally require important human labor. The impact of AI on labor-intensive services is already evident in several industries. For example, customer service, once reliant on a large team of call center human agents, is now being transformed by AI-powered chatbots and voice assistants. Bank of America’s Erica AI handles interactions with over 2 million customers every day, surpassing 2 billion interactions since its launch in 2018, significantly reducing the need for human agents. Similarly, airlines and e-commerce companies are increasingly relying on AI to autonomously process customer queries. As the Generated AI conversation agents continue to improve, the entire call center will be replaced by AI-driven agents, allowing human workers to manage only more complex tasks. In software development, AI tools like Github Co-Pilot help developers write code more efficiently and with less manual effort. A software engineer with AI, Cognitive AI’s Devin can build and debug applications that are in demand. AI isn’t going to completely replace developers, but it reduces the need for large engineering teams and translates software development into more automated workflows. In the legal and financial sector, AI-powered tools automate tasks that once required expensive professionals. Law firms use AI to draft research and contracts, traditionally the domain of junior associates. AI-driven financial models can now analyze balance sheets, detect fraud and generate investment analysis reports. These advances challenge the traditional view of professional services as AI increases and more takes over the tasks previously performed by professional workers in high-cost industries. The evolution of enterprise technology leads to new AI-driven business models. Traditionally, companies used software systems as platforms where human experts worked. These software systems became “systems of records” (SORS), and business knowledge was encapsulated within them, ensuring continuity through sustainability. Currently, AI is directly involved in these systems, shifting its focus from human-driven work to AILE LED processes. As a result, businesses don’t just replace SaaS with AI tools. We are redesigning our entire processes and systems to integrate AI. Instead of hiring marketing institutions, companies rely on AI to create dynamic campaigns. Quality assurance and control features are automated by AI to support support, cybersecurity, and HR processes. Transform the way enterprise resources are organized by deploying AI agents for real-time coordination, productivity monitoring and calendar management.
Despite the transition to AI, human expertise is important in some areas. Human intervention is required for AI monitoring, ethical governance and bias correction. Strategic decision-making and creativity remain human spheres, as well as relationship management and customer experiences, which involve complex problem solving and building trust. AI handles everyday tasks, but human workers still manage escalations and provide a high level of insight. AI systems also require human supervision in areas such as training, debugging, and maintaining AI models to ensure that AI models are accurate and effective. The shift from labor-intensive services to AI-driven automation is already underway, and has had a major impact on businesses and workers. Rather than completely replacing human roles, AI redefines them, complementing human judgment, creativity and surveillance.
Dr. Sharanpreet Kaur is an assistant professor of international relations in the Department of Social Sciences at Guru Nanak Dev University in Amritsar.
