Why AI Will Replace More Enterprise Software Than People

Katherine is the CEO of Creatio, an AI CRM and workflow platform where people and AI agents work together.

getty​Within a few years, people and AI agents will work side by side in every company and in every department. And the enterprise software supporting them will look almost nothing like the software that runs your company today.

That’s because legacy enterprise software, as many organizations know it, is being replaced by AI-native enterprise software. Understanding why this is happening is the key to charting a course and navigating through what will be the biggest shift in the enterprise software market in over 30 years. ​

The force behind this change is driven by technology, but it’s also driven by customers.

In the age of AI, business buyers and consumers expect answers in minutes, service that never closes and personalized experiences without sharing too much personal information. People will judge every company against the best experience they have had anywhere.

Companies are reinventing how they work to meet those expectations. When they map the new ways of working onto the software they own, they are reaching an elephantine conclusion: Their legacy software is never going to work the way it needs to work at a reasonable cost.

That conclusion, being discussed in organizations around the world, has set off what could become the largest software replacement cycle in decades.

And here’s what it means for the people working in enterprise organizations, as sentiment about AI swings back and forth from euphoria to doubt week to week. Underneath the noise, the direction is steady.

I lead a company that works with thousands of organizations in more than 100 countries, and the preference I’m consistently seeing is that, rather than putting AI on top of legacy software, organizations are replacing legacy software with AI-native platforms. This way, people and AI agents can work together to acquire and serve customers and drive organizational growth in totally new ways.

Legacy platforms were built for a world of data entered by people, rules configured by administrators and value metered by the seat.

AI agents that reason and act need a data model based on context, workflows that put their agentic capabilities to work and governance that keeps every AI and human action auditable. Bolt agents onto an architecture that was never built to accommodate them, and you get expensive AI assistants that summarize disconnected data and add minimal value.

The headlines about soaring enterprise license and AI costs are rooted in this story. Vendors with legacy architecture and years of acquisitions must recover the enormous cost of modernizing and integrating it before their AI can run at a reasonable cost, and their customers fund that recovery through price increases.

AI-native platforms carry less modernization debt. They were born modern, so automation arrives at a price that makes sense for every business case. When buyers compare the two paths and they find partially modernized legacy enterprise platforms with complex pricing that puts limits on their new ways of working, the arithmetic can do much of the deciding.

The new shape of work is already visible, and it sorts into autonomous, hybrid and human workflows.

Autonomous agentic workflows run with minimal input and oversight from people at a company. Think of a routine service request resolved from start to finish in minutes, paperwork and documents processed automatically or a quote for a large purchase order assembled and approved instantly.

Hybrid workflows combine AI agents with more input from people. For example, an agent assembles a renewal quote and flags the risks. A person makes the judgment call and takes the next steps.

Mostly human workflows remain where trust and relationships decide the outcome, such as leading a strategic account through a complex negotiation.

In every combination, the work reassembles into new workflows and new software applications in which people handle exceptions, judgment and relationships while agents handle technical complexity and volume.

The result meets customer expectations and business objectives better than before, at a cost better than before.

Early this year, my company surveyed over 560 organizations, and 86% said AI was the main conversation in their boardrooms. That conversation must now become a plan to move the organization’s processes into the new AI-native software era.

Organizations should start by sorting workflows into the three types above and keep the needs of the customer in focus. Then let ROI decide the platform choice and automation mix: Identify each workflow, baseline what it costs today and include the opportunity costs, then calculate the benefits of new-era automation.

Organizations should also consider platforms with built-in orchestration and governance tools to reach the lowest reasonable cost of automation, with every AI agent and human action visible. Frame the ROI as capacity and customer experience: work deflected, costs avoided and hours redirected toward customers and growth outcomes.

​For some organizations, transformation will be difficult because enterprise software and data schemas have become entrenched. Replacing legacy systems may require co-deploying new-era technology while the transformation is happening.

Leaders should go in with clear eyes about the potential friction that these changes will cause. When years of customizations, integrations and institutional knowledge live inside legacy technologies, moving them requires disciplined data migration, cleanup of processes and careful sequencing so that revenue-critical work continues without interruption. ​​

A phased approach works best: Start with a contained set of high-value use cases and agentic workflows, connected to the current data, prove the ROI, then expand. The friction is real, but so is the cost of standing still on platforms that are getting more expensive and less capable of supporting the way customers now expect to be served.

This monumental shift does not end with AI taking over. It ends with customers getting more of what they want, companies thriving on capacity they could never achieve before and people doing work they enjoy. ​

Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?