Is SaaS Dead or Evolving? Dan MacDonald on Why AI Adoption Is Redefining the Future of Software for High-Stakes Industries

A recent moment in the markets prompted a question that many software leaders are now quietly asking. According to Dan MacDonald, founder and CEO of BIS Safety Software, the loss of roughly $1 trillion in SaaS valuations in a single day signaled more than volatility. It pointed to a deeper shift already underway.

From his perspective, the question is not whether SaaS is disappearing, but whether its traditional form can keep pace with what AI is making possible. “There’s a real conversation happening right now where people are asking if SaaS is dead,” MacDonald says. “For some companies, it absolutely could be, but for others, this is the moment where everything accelerates.”

This sense of urgency is reflected more broadly across the business landscape. According to a report, 78% of organizations reported using AI in 2024, up from 55% the year before, highlighting a rapid acceleration in enterprise adoption. The data suggests that AI is moving quickly from experimentation into core business functions, signaling a shift in expectations around how modern software is built and deployed.

At the center of the shift is what he explains as the illusion of AI adoption. Many organizations believe they are participating in the transformation simply by using tools occasionally. In practice, he suggests that level of engagement does not reflect meaningful change. “Using AI once in a while is not the same as being an AI-driven company,” he says. “Real adoption is when it becomes embedded in how your teams work every day.”

According to MacDonald, this distinction becomes more apparent as development timelines begin to shift. He suggests that AI-supported workflows are enabling teams to significantly reduce the time required to build and refine software, in some cases compressing efforts that once took months into much shorter cycles. From his perspective, the impact is not limited to speed alone but extends to how teams approach problem-solving, iteration, and continuous improvement within modern software environments.

He adds that this shift introduces a new kind of divide across the software landscape. “A portion of companies are beginning to integrate AI across departments, encouraging experimentation and continuous improvement,” he says. Others, he notes, are still approaching it cautiously or treating it as an add-on rather than a foundation. “There’s going to be a percentage of companies that fully embrace this and transform,” he believes. “And then there are those that are not paying attention in the same way.”

Within his own organization, MacDonald frames a structured approach to building that momentum. According to MacDonald, there are numerous initiatives that are required to make a significant change. One example he points to is his teams regularly sharing what he calls AI wins, highlighting how different departments are applying new tools to improve efficiency or solve problems. This practice, he suggests, helps create a culture where AI is not a one-time initiative but an ongoing process of refinement.

The implications extend beyond internal operations into how software itself is experienced by users. MacDonald points to a near-term future where interacting with software may feel less like navigating a fixed interface and more like having a conversation. “You are going to be able to talk to your software and communicate the changes you want to see, and it updates the application for you,” he says. “Dashboards, reports, workflows, all of it becomes something you can create just by asking.”

For industries where safety and compliance are critical, this shift could introduce new levels of adaptability. Systems may be able to respond more quickly to operational changes, generate insights in real time, and support decision-making in ways that were previously limited by static designs. According to MacDonald, this creates an opportunity for organizations that are willing to rethink how they use technology.

In that context, BIS Safety Software operates as an all-in-one health and safety management platform designed to help organizations track compliance, training, and workforce safety, particularly in industries such as construction, oil and gas, and mining. MacDonald notes that in these environments, the ability to adapt systems quickly while maintaining accuracy and accountability is becoming increasingly important.

At the same time, he emphasizes that progress must be balanced with responsibility. As AI capabilities expand, so do considerations around data privacy, security, and regulatory compliance. “We are pushing forward with AI, but we are also making sure we protect our customers’ data and meet all the standards that matter,” he says.

To illustrate the broader dynamic, MacDonald draws on a simple analogy. “Businesses that encounter new technology have a choice in how they respond,” he says. “Some adapt and integrate it into their offering, while others hesitate and risk being left behind.” In his view, the same principle applies to software companies navigating the rise of AI.

Ultimately, the question of whether SaaS is dead may be less important than how it evolves. The model itself is not disappearing, but its definition is changing as AI reshapes what software can do and how quickly it can adapt. For leaders, particularly in high-risk industries, the challenge is not just to adopt new tools but to understand how deeply they can be integrated.

“The real question is not whether this shift is happening,” MacDonald says. “It is whether you are prepared to rethink how your business operates, because the ones who do will not just keep pace, they will set the pace.”