What CIOs Most Want to Replace With AI Today
The discussion inside companies is no longer about whether Artificial Intelligence will replace software, but which software categories will be swapped out first – and how fast. CIOs are already reviewing contracts, questioning legacy licenses, and using the AI budget to rip old tools out of the stack in many cases.
A Redpoint survey with 141 CIOs in March 2026 asked a direct question: in which software categories did you seriously consider replacing your current vendor over the past year? The answers show where the replacement pressure is strongest and where incumbents still have room to breathe.
Category ranking: where CIOs are actually thinking about switching
In the survey, CIOs answered which categories they seriously thought about switching vendors in over the last 12 months. Here is the result:
- Customer Service Management: 26%
- Finance Ops: 21%
- Project Management: 20%
- Salesforce Automation / CRM: 19%
- HRIS (HR Systems): 17%
- Integration and Automation: 17%
- Business Intelligence: 14%
- Cybersecurity: 13%
- DevOps: 8%
- Collaboration: 7%
- ERP: 6%
- ITSM: 5%
- Procurement: 5%
- General Productivity (Office/Workspace-type tools): 2%
Behind this list, a very clear pattern emerges: categories built around work coordination and workflow visibility are much more vulnerable to AI than categories deeply rooted in finance, compliance, and critical business data.
Customer service: the most vulnerable category, right in the eye of the storm
Customer service is currently the most exposed point. One in four CIOs (26%) seriously considered switching their customer service vendor in the last year. And that matches what is happening in the market.
AI-native support tools such as Sierra, Decagon, and Fin/Intercom are closing deals with large enterprises and going head-to-head with established players. The reason is simple: the ROI case for moving from human-led flows assisted by software to AI agents on the front line is already mature. Lower cost per ticket, higher first-contact resolution, and 24/7 support have become standard arguments at the CIOs table.
Additional data from Gartner helps size this pressure. In a survey with 321 customer service leaders in October 2025:
- 91% said they are under pressure to implement AI in 2026;
- almost 80% plan to reallocate at least part of their frontline agents to other roles.
This is not a sector on the verge of disruption; it is a sector in the middle of disruption. Traditional help desk and call center software, focused only on ticket creation and routing, tends to be replaced or at least pushed into the back office while AI agents take over the customer interface.
Finance Ops: the surprising 21%
The big surprise in the survey is Finance Ops, at 21% of CIOs considering a vendor switch. Finance has always been very resistant to system changes: CFOs avoid touching what works, auditors value consistency, and integrations with ERP, banks, and regulators are heavy.
Even so, just over one fifth of CIOs seriously considered changing their finance operations software. This signals that AI is opening a real crack in a historically stable territory.
What AI is doing here is not throwing away the ERP, but attacking the operational flows around it: reconciliation, close, accounts payable/receivable, reviews, operational compliance. Language models that read documents, integrate data from multiple sources, and automate entries and reviews reduce the need for multiple niche solutions. The math starts to work for consolidating vendors, simplifying the finance stack and, in some cases, migrating to platforms that already bring AI natively embedded in these flows.
Project Management: 20% and direct pressure from AI agents
In project management, 20% of CIOs considered switching vendors in the last year. Here, the reason is very straightforward: the core value of most PM tools is coordinating who does what, when, and with what priority. And that is exactly the kind of problem AI agents are very good at solving.
When an agent can:
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- automatically create and assign tasks;
- update status based on messages, commits, and meetings;
- identify blockers and risks by looking at history;
- generate reports and status summaries in seconds;
it gets harder to justify a per-seat license for a system that only works if people update everything manually. In practice, AI turns the project manager into a high-level orchestrator, while it takes over repetitive work and data updates.
This helps explain what happened with Atlassian and Monday.com stocks in 2026: both were heavily punished in the middle of a broad tech sell-off. The market is not just anticipating slower growth; it is pricing in the specific risk that their main use case — work coordination and workflow visibility — is exactly what AI agents can do on top of any existing system of record.
When 20% of CIOs consider switching PM tools within 12 months, the obvious question is: what is the long-term value of a purely seat-based project management product if AI can deliver a coordination layer on top of platforms the company already has?
General Productivity: 2% and a clear message to those betting on the fall of Microsoft 365 and Google Workspace
At the other end of the ranking, general productivity shows up at just 2%. In other words, practically no CIO is ready to replace Microsoft 365, Google Workspace, and equivalents.
This sends a very clear message: basic productivity is extremely sticky. The switching cost is too high, the cultural impact is huge, the integration surface is massive. On top of that, both Microsoft and Google are adding AI (Copilot, Gemini) directly into the package users already know. So what happens is not suite replacement, but AI being embedded into what already exists.
Salesforce Automation: 19% and the risk of CRM being rewritten in-house
With 19%, sales automation and CRM also appear highly exposed. A Recognize survey with more than 200 IT executives in the U.S., conducted at the end of 2025, showed that 55% expect to replace some part of their commercial software with AI-generated or AI-powered tools. The most cited examples:
- custom CRMs;
- internally built commercial workflow automation platforms.
In other words, CRM is not only at risk from AI-focused sales startups such as Attio and others. It is at risk of the company itself deciding to build its own CRM and automation layer on top of language models and internal databases, tailored to its specific sales process.
Three numbers that explain the landscape
The percentages by category only make full sense when we look at three numbers from the same survey:
- 54% of CIOs are actively pursuing vendor consolidation;
- 45% of the AI budget comes from cuts to other software, not from new money;
- only 3% of CIOs expect to have more vendors because of AI.
54% want consolidation: fewer tools, more platform
More than half of CIOs are running active programs to reduce their number of vendors. On average, an enterprise runs over 130 SaaS applications and typically finds 20% to 30% redundancy when it takes a careful look at the stack.
This redundancy has turned into a budget-cutting line. As AI ramps up, the trend is to concentrate usage on fewer platforms, each with multiple capabilities and intelligent layers, instead of exploding into endless point solutions.
45% of the AI budget is replacing existing budget
About 45% of CIOs say the money for AI is coming directly from existing software lines. It is not new budget; it is reallocation.
With IT budget growth slowing to around 3.4% in 2026, every dollar spent on a new AI tool tends to be taken from another piece of software. In other words, this is a zero-sum game: for an AI vendor to grow, someone else has to shrink.
Only 3% think AI will increase the number of vendors
Finally, only 3% of CIOs believe they will work with more vendors because of AI. This undermines the thesis that we will see an unlimited explosion of AI point solutions happily coexisting with the current stack.
The picture is the opposite: convergence. CIOs are choosing now the few ecosystems around which they will consolidate flows, data, and AI agents. Anyone who does not make that list risks facing a structural demand squeeze, no matter how good the product is on its own.
What makes a category vulnerable or protected
Looking at the ranking more closely, a clear pattern emerges.
Vulnerable categories: coordination and workflow visibility
The higher-risk categories share one core trait: they mainly deliver work coordination and workflow visibility. This is the case for:
- customer service;
- project management;
- sales automation and CRM;
- integration and automation tools;
- specific Business Intelligence layers focused on operational reporting.
These problems are highly aligned with what AI agents do well today:
- read tickets, documents, emails, and events;
- follow relatively clear rules;
- generate structured outputs (tickets, reports, plans, statuses);
- orchestrate actions across multiple systems.
In most cases, they do not require years of proprietary data to start generating value. When the CIO decides to migrate, the switching cost is not prohibitively high.
This lines up with a Gartner analysis on jobs most exposed to AI: service desk, business analysts, project managers — roles heavily based on organizing information into flows and recording status. The software that underpins these jobs naturally inherits the same level of exposure.
More protected categories: deep data, compliance, and historical dependency
On the other side are categories with low intention-to-switch rates, such as:
- ERP (6%);
- general productivity (2%);
- some collaboration tools (7%) and ITSM (5%).
What these areas have in common:
- strong grounding in financial, tax, or workforce data;
- heavy compliance, audit, and traceability requirements;
- years of customization and surgical integrations with dozens of other systems.
In these cases, the switching cost is almost existential. You do not abandon your entire ERP stack because you saw an impressive AI agent demo. The tendency is to plug AI around it: copilots to generate reports, automate entries, summarize data, and assist navigation. But the transactional core tends to remain.
Redpoint suggests a useful way to frame this: vertical software that has accumulated years of proprietary, industry-specific data carries such a high switching cost that you only touch it in cases of extreme disruption.
Collaboration: 7% and the real cost of trying to replace Slack
Collaboration, at 7%, also stands out. For years people said tools like Slack would be quickly swallowed by AI-native alternatives. So far, the data does not show that happening at scale.
The economics weigh heavily here. Using a Redpoint example: for a 1,000-person company, replacing Slack costs about 220,000 dollars per year in licenses. But building a minimally decent internal alternative can easily exceed 2 million dollars per year in development, maintenance, and infrastructure — and still deliver an inferior product.
Even in an AI-first scenario, the numbers simply do not work out for replacing deeply entrenched collaboration tools. The natural move is to bring AI into them (channel summaries, smarter search, drafted replies) instead of trying to rewrite everything from scratch.
The incumbent paradox: real advantage, weak execution
There is an important detail in the survey: while 54% of CIOs are consolidating vendors, 61% prefer to buy AI capabilities from vendors they already use, whenever possible.
In other words, incumbents have a very real advantage: customers generally want to stay with them, if the AI offering makes sense in terms of capability and price. The relationship is already there, the integration is done, and governance is in place.
The problem is that many are wasting this advantage:
- Salesforce Agentforce is perceived by many enterprise buyers as overpromised and underdelivered;
- the price of Microsoft Copilot, which practically doubles the cost of an E3 license, has led some large companies to slow down broad rollouts;
- ServiceNow is viewed as so expensive that several CIOs say they would not hesitate to switch if a truly competitive AI alternative emerged.
For AI-native startups, this opens a rare window of opportunity. Customers would prefer the incumbent to solve their problem with AI, but many feel this is not happening at the speed or quality they expect. However, this window will not stay open forever: once a major player launches a truly competent AI layer at an acceptable price, consolidation logic starts working against the new entrant.
If you operate in one of these categories
For teams building products in:
- customer service management;
- finance ops;
- project management;
- sales automation and CRM;
the message from the numbers is straightforward: the intent to switch vendors has never been this high, with 19% to 26% of CIOs actively evaluating alternatives. Right now the game is about speed: companies that have already seen concrete results with AI are cutting excess tools, shutting down pilots, and betting on a small set of winning platforms.
In 2025, many organizations ran four or five experiments in parallel. In 2026, they are deciding who stays. Anyone who shows up late may find the AI budget already committed to another player.
If your product is in lower-risk categories — collaboration, ERP, ITSM, general productivity — the pressure for direct replacement by AI is smaller, but the pressure for consolidation is the same. The risk here is not necessarily that an AI competitor shows up and wipes you out, but that you become the fourth or fifth tool in a segment where the CIO has decided to keep only one or two platforms.
AI rises, everything else compresses
The overall picture is one of real software budgets shrinking while AI spend grows. Since total IT budgets are not expanding at the same pace, every new dollar for AI means a dollar less in some other software line.
CIOs have already made it clear where this money is coming from:
- customer service is now the most hotly contested arena in the enterprise;
- finance ops and project management are far more exposed than many expected;
- ERP and general productivity remain extremely sticky and hard to dislodge.
And with 54% of CIOs running consolidation programs, even categories that do not top the direct replacement list still face churn risk simply for being redundant in a stack that is being deliberately slimmed down.
In the end, the movement is clear: fewer tools, more AI, more platform. And the decisions CIOs are making now are likely to determine which players remain relevant in the next decade and which ones become just another line cut from the budget spreadsheet.
