aaSaaS

Don't worry, aaSaaS is not how we're going to describe it. But things in software will be massively different. We are on the cusp of a decisive shift in the SaaS industry. Traditionally, SaaS platforms have functioned as tools—assistive programs designed to amplify human productivity by streamlining workflows and providing insights.

However, the next evolution will see these platforms transform from tools into agents: autonomous entities capable of performing tasks, making decisions, and delivering outcomes without constant human intervention. In other words, the AI Agent element of SaaS will replace the human operator.

It's not going to be like before. Could this be a SaaS renaissance?

With SaaS AI Agents taking on operational tasks, the role of the human worker evolves. Instead of executing tasks, humans will oversee, direct, and manage these agents. They'll focus on setting objectives, handling exceptions, and strategising broader initiatives. This shift could redefine what we consider high-value work, placing greater emphasis on creativity, problem-solving, and oversight.

Advantages

Continuous Learning and Evolution

AI Agents continuously learn and improve through data-driven insights, adapting to changing conditions and refining their processes in real-time. The inflow of live data creates a feedback loop of optimisation that no static software tool can replicate. Single AI models will benefit from what they learn across thousands of operations and interactions, allowing them to iterate much faster and with real insight.

Infinite Scaling

Unlike human workers, AI Agents can scale operations instantly. Whether managing thousands of customer queries or processing terabytes of data, they can handle increased workloads without additional overhead. It's like having thousands of clones of your best-performing employees. Your productivity would reach the stars.

Cost Efficiency

AI agents hugely reduce costs by automating repetitive and labour-intensive tasks. They operate 24/7 without the need for breaks, holidays, or extensive training. Those thousands of your A-team players are making you money while you sleep. Worth $99 a month, right?

A Better Customer Experience?

AI Agents can provide real-time, personalised customer responses, potentially enhancing satisfaction. Their ability to learn customer preferences and patterns allows for more tailored interactions, though whether they can fully replicate the nuance of human empathy remains debatable.

Caveat: If we reach an age of ubiquitous AI agents in customer service, it's possible that companies ostensibly offer 'real human' interactions as a value-add.

Disadvantages

Trusting Agents

Relying on AI Agents introduces trust issues. It's always worth remembering that LLM outputs are deterministic (i.e., they don't always give the same output for a given input). This uncertainty allows plenty of room for crazy responses, bias, and ethical quandaries.

Remember that in some implementations, bad human actors will be able to influence the process. Organisations must ensure that these agents make ethical, unbiased, and accurate decisions—not an easy task given the complexity of AI systems.

Reduced Human Oversight

Organisations risk losing visibility into the decision-making process as tasks become fully automated. AI's "black box" nature can make it difficult to understand how or why specific outcomes were reached.

Bias

AI Agents inherit biases from their training data. If unchecked, these biases can lead to unfair or discriminatory actions, potentially leading to poor user outcomes and exposing organisations to reputational and legal risks.

What Happens to the People?

Automation raises questions about workforce displacement. What happens to the employees whose tasks are now handled by AI? Upskilling and reassigning workers will be crucial but could prove challenging at scale. What will happen to white-collar knowledge workers in a world of mass AI adoption is hugely unclear.

Data-Based Performance

AI's effectiveness depends on high-quality data. Inaccurate, incomplete, or biased data can compromise performance, leading to poor outcomes and undermining trust in the system. Data quality, quantity, and availability differ enormously from industry to industry. Training your AI on your internal data will lead to superior performance, but it will take time and investment upfront.

Vendor Lock-In

Relying on a single SaaS provider for mission-critical tasks creates dependency. Organisations may find it challenging to switch vendors or adapt if the provider changes its offerings or pricing models. After all, you won't have people to switch tools. Given that most AI API providers like ChatGPT are losing colossal amounts of money, expect price hikes once you've committed long-term to AI SaaS.

Error Blast-Radius at Speed & Scale

AI operates at a speed and scale that can amplify errors. A small mistake in an AI Agent's decision-making can cascade rapidly, causing widespread issues before human intervention is possible. Think of any Hollywood film featuring a powerful AI. Early successes lead humans to give it more responsibility until it suddenly turns sour. In AI SaaS, companies will shift more and more operations to AI, creating more extensive exposure to automation failures and unexpected outcomes.

How Soon Is This Happening?

The paradigm shift is already underway. Many SaaS providers are integrating AI-driven features, transitioning from augmenting human tasks to automating them entirely. We are approaching a tipping point where fully autonomous SaaS AI Agents become the norm.

However, widespread adoption faces hurdles. AI Agents require robust data pipelines and computing infrastructure, and many organisations still lack the resources or expertise to build and maintain these systems effectively.

The shift to AI-driven SaaS will become mainstream within 3-5 years, especially in industries with mature AI use cases like customer service, marketing, and HR. Other sectors with higher regulatory or complexity barriers may take longer to adopt this new model.

The rise of SaaS AI Agents represents both a thrilling opportunity and a profound challenge. Organisations must navigate this transition thoughtfully, balancing innovation with caution to ensure these powerful tools serve their business goals and broader societal needs.

What do you need to do?

Large organisations have a golden opportunity to enhance their capabilities by effectively implementing AI Agents within their operations. These companies have the most financial gain by reducing payroll and increasing operational efficiency. There is no need to wait for SaaS vendors to offer AI SaaS services. Managers in large companies should already be working on leveraging AI Agents.

Current SaaS tools should incorporate agents, as it is possible and necessary. This is an existential threat; in five years, software tools requiring humans to press buttons and operate things will be obsolete.

New startups are born AI-native and can steal a march on established players. Anyone creating a SaaS in 2025 should start where the LLMs go. It's a golden opportunity to grow fast and either establish a market presence or be acquired by an incumbent.

Finally, anyone who works on a computer should consider retraining as a plumber. There might not be much for you to do soon.

Temrel is an AI Automation and Workflow partner. We help companies implement AI to improve outcomes, lower costs, and increase efficiency. Start your conversation on how to get ahead of the AI revolution here.