CIOs experiencing sticker shock from recent software bills should be questioning how they got there.

That’s because IT leaders at large enterprises are paying a huge so-called software tax for vendor-driven upgrades, migrations, and licensing changes they would not have chosen for their organizations.

About 28% of software budgets at large organizations — an average of nearly $12.9 million per year — are being eaten up by vendor-pushed initiatives, according to a survey commissioned by independent software maintenance partner Origina.

Ninety-five percent of IT leaders surveyed said their organizations have paid for a vendor-driven upgrade in the past three years that they believed would actually reduce performance, according to the survey, which covered US and UK organizations with annual revenues higher than $1 billion or with more than 10,000 employees.

The sheer size of this “software tax” surprised Tomás O’Leary, Origina’s CEO, even though the company expected to see substantial costs for vendor-driven upgrades.

“Software was supposed to make businesses better, and it does,” he says. “But it’s also imposing a hidden cost on companies, quite a significant one. I’m quite taken aback because we know this exists, but we never quantified it before.”

When vendors control your IT spend

Big vendors have several major advantages over software customers, with the cost of switching or refusing to upgrade topping the list, O’Leary notes. In many cases, CIOs are faced with a loss of support if they turn down vendor-driven upgrades, leaving them with little room to refuse, he says. CIOs dependent on VMware are familiar with this squeeze play, as are those facing SAP deadlines.

“CIOs are left in a situation where the alternative may be worse, so upgrading is the lesser of two evils,” O’Leary adds. “When people buy technology, they don’t realize how long this stuff is going to hang around. Nobody realized this thing was going to be embedded, and the dependency was going to be greater and greater with time.”

In addition, software vendors have an experience advantage when negotiating contracts, O’Leary says. CIOs and procurement officers may try to negotiate favorable terms for upgrades, but big software vendors are expert at writing contracts that give them an edge, he notes, adding that the survey results suggest IT leaders’ current approach to negotiating better contracts is a failed tactic.

“If you keep trying the same thing over and over again, and it doesn’t work, you’ve got to try something different,” O’Leary says. “There’s a relief on the buyer side when the negotiations are over, and on the seller side for sure. But the seller side has to get back up again and do it again the next morning with somebody else, and the buyers don’t.”

Omar Amassine, founder and technical director at TripleW Digital, says between 20% and 30% of the IT services firm’s software and maintenance budget goes to vendor-driven migrations he didn’t request.

The biggest culprits? CRM, marketing automation suites, and cloud infrastructure, he says.

“Vendors frequently bundle mandatory AI features or restructure seat-based pricing into usage tiers, driving effective 20% to 35% price jumps with zero incremental utility for the core workflow,” he says.

IT leaders can fight back, however, by using modular, open standards and headless architecture, he adds. “The less proprietary logic locked inside a vendor’s walled garden, the higher your leverage when they mandate expensive upgrades,” Amassine says.

TripleW Digital also runs migration feasibility studies six months before software contract renewals. Having a migration roadmap can bring the vendor back to the negotiating table offering multi-year price freezes, he notes.

Emphasize partnership — and a credible threat of defection

Zachary Lewis, CIO of University of Health Sciences and Pharmacy in St. Louis, hasn’t seen the same software spending mandates as the organizations reflected in the survey.

The university has negotiated many of its software contracts to ensure upgrades and security patches are handled by the vendor, either with Lewis’ approval or during an agreed-on maintenance window, he says.

Even without costly upgrades, there’s still a time tax, he adds.

“With the sheer volume of new vulnerabilities being discovered, we’re spending more time following up with vendors to make sure they’re applying patches in a timely manner,” Lewis says. “My team simply isn’t large enough to manually manage patching across every application and software component we use.”

Here, establishing a vendor management strategy that emphasizes partnership over provisioning can help. And if vendors still drive costly upgrades, IT leaders can always switch providers.

But Lewis cautions that, as tempting as that is, it’s often a complicated process.

“Switching vendors is always an option, but it’s rarely simple,” he says. “Depending on the application, you may have years of integrations, processes, and institutional knowledge built around it. Sometimes the cost of moving away from a vendor is significantly higher than the cost you’re trying to avoid.”

Customers of large ERP solutions in particular are facing a significant reckoning on decades of customizations.

Collective bargaining power comes with communication

To regain their purchasing power, Origina’s O’Leary advises CIOs and procurement officers to negotiate shorter contracts, which would enable them to renegotiate terms more often and exit more quickly if their vendor jacks up prices.

“You have to get to a point where you can have a more frequent engagement with the vendor,” he says. “Negotiate your exit, and negotiate more frequently.”

While short-term contracts may impose more up-front costs on customers, they can pay off with the additional flexibility they provide, he says.

CIOs can also turn to third-party software management firms or consider internal support of their software packages if they have the resources, O’Leary advises.

CIOs should also share their software purchasing success stories and nightmares with each other more than they do now, he says.

“We all benefit from having a little bit more collective bargaining power,” he adds. “CIOs just need to take that leap of faith that others have the same problems, and maybe we can have some sort of collective pushback on this.”

Sumit Johar has been modernizing BlackLine’s IT environment since becoming CIO of the software company in early 2024.

As a longtime IT leader, Johar has plenty of experience overhauling tech stacks, but he says the work has taken on new meaning — and urgency — in the AI era.

“The definition of modernization has literally switched in the last two to three years,” he says. “Suddenly everything that you built in the last few years looks like legacy, because the SaaS model, which we have been using for the last 10 to 15 years, there is an opportunity now to totally change that and modernize with AI and for AI.”

Johar is doing just that, surveying the company’s SaaS portfolio, particularly zeroing in on point solutions, asking whether each is worth the cost, whether it delivers true business value, or whether IT can use AI to build a service better suited to his company’s needs.

At the same time, AI is changing how workers interact with technology, he says, enabling people to query applications via natural language and chat, which has his IT team considering which applications may need to be modernized or abandoned altogether as a result.

Take, for example, dashboards. “We built dashboards because there was no other or better way to report on your data,” he says. “Now I can simply ask a question and get an answer, which is what I was interested in anyways. So if I have my ERP and CRM talk to me in a human language, I’m happy with that. That’s modernization.”

As a result, he adds, “some of us might be getting rid of [our dashboards], and some might be slowly reducing the dashboarding tools we have.”

As organizations remake and automate workflows with AI, software that enables those workflows could meet a similar fate, Johar says.

Even chatbot-building products that IT implemented a few years ago are prime targets for rationalization due to AI advances, he adds. “I still need chatbots, but I don’t think I need specialized software to build a chatbot anymore. Any generic AI platform that I have will give me the ability to basically build them,” he explains.

High-priority tasks

For Johar, the longstanding CIO tasks of modernization and rationalization remain make-or-break activities for IT.

Johar and other IT leaders see modernization and rationalization as vital to controlling IT spend — as high of a priority for CIOs as it’s ever been, freeing up dollars for innovation (the No. 1 objective for nearly every IT leader and their CEO’s top priority).

IT leaders also see modernization helping them create a future-ready IT environment, one that’s not encumbered by legacy technologies and complexities that don’t play nice with emerging technologies.

“CIOs don’t have much of a choice than to continue modernization; they’re in a perpetual state of modernization,” says Amar Aswatha, senior vice president for global business engineering at CGI, a consulting and services firm. “They’re trying to simplify yesterday’s tech state while creating resilience and the right environment for AI and to be ready for whatever will emerge.”

Other factors also drive the need for ongoing modernization, Aswatha notes. The rapid pace of innovation is reducing the shelf life of many technologies more quickly, necessitating more rapid overhaul cycles than in the past. Meanwhile, the past decade’s mass migration to the cloud has meant that CIOs “traded server sprawl for subscription sprawl,” he says. The rush to adopt AI is having a similar effect, leading to AI and agent sprawl — and the need for new and more widespread rationalization and modernization strategies.

Still, CIOs must be more surgical than they’ve been in the past, using a scalpel not an ax to shed legacy technology and simplify IT environments, Aswatha advises.

That means accounting for both current and emerging business needs when determining what systems should be modernized — not simply relying on age or other such non-business-related factors. And IT leaders can’t see rationalization as an exercise in reducing application count to a set number; unnecessary complexity should instead be the target.

Such approaches require CIOs and their teams to understand current and future business needs, as well as how those needs, and the organization’s overarching strategy, shift over time, Aswatha says.

“CIOs have to watch for business signals on when and what to modernize and rationalize. It’s not about spring cleaning, it’s about what apps are slowing the business down,” he advises.

‘Best for the organization’

Rachelle Putnam, vice president and CIO of General Dynamics Land Systems, which manufactures military vehicles, is taking such an approach.

Putnam, who has led IT at the company since 2014 and managed a move off a mainframe about a decade ago, says modernization today means asking whether existing technology “allows us to have the flexibility and the functionality we need.”

Like many CIOs not on IT’s bleeding edge, for Putnam savvy modernization is about strategy, not technology. “Some might say we’re not on a modern tool set, but that doesn’t mean we don’t have the functionality we need,” she says.

For example, Putnam embraces a cloud-smart strategy, modernizing on the cloud where it makes sense and on-prem when that’s the better or required option based on government regulations.

She applies a similar lens to rationalization, asking whether any given application uniquely fulfills a business need or whether other apps in the portfolio can do the job. Such questioning helped her standardize the company on two CAD tools, down from 10, and standardize on one reporting tool instead of using three.

Putnam is also increasingly asking whether she even needs a vendor solution.

“With tools like Claude Code, when we look at [vendor-offered] apps, we ask if we even need them or whether we can create our own and not pay for maintenance,” she says. “Sometimes we want SaaS, where we want those updates, but there are others that we don’t need updates and won’t need to change the application much, so those are the ones we’re going to look at creating ourselves.”

Like other CIOs, Putnam believes modernization produces benefits for IT and the company as a whole, ensuring the organization not only has the technology necessary to perform but also a standardized data environment so that “everyone is looking at the same data, and it means the same thing,” she says.

In addition to cutting IT maintenance and management costs, modernization also reduces risks, by eliminating unsupported legacy tech and difficult-to-manage complexity.

And it makes IT talent more effective and efficient, by eliminating the need for outdated skills, which are typically hard to find and thus come at a premium. With rationalization, IT teams no longer must learn multiple vendor solutions or assign different workers to different solutions.

Modernization challenges

Of course, Putnam and other IT leaders acknowledge there are challenges to modernization and rationalization, too.

“Cost is certainly one. Sometimes it costs more to get off one than continuing to run multiples,” Putnam says.

Even in such cases, however, hard-to-quantify benefits make the move worth it, she adds. For example, rationalizing to one common system used throughout the company’s multiple geographic locations means workers anywhere can easily be assigned to help when one region faces a surge in work.

Data migration is another common challenge. But data issues can usually be overcome with “creativity, mostly, and having someone dig down to really get it done,” Putnam says. Sometimes it may mean shelving the data and only retrieving it if necessary.

Then there’s the challenge of limiting future rationalization by controlling what gets added to the IT environment today. To that end, deploying and using a common tool is the default standard now at General Dynamics Land Systems.

“That’s a rule that everyone abides by,” Putnam says, acknowledging some pushback. “Sometimes people will argue for that extra 15% that one tool might have that the existing tool doesn’t have. But we stress that standardization is best for the organization as a whole.”

A staple of CIO work

Krishna Prasad, CIO of UST, a digital transformation and IT services provider, similarly sees modernization through a business — not a technology — lens today.

Whereas modernization was once triggered by advancements that made existing tech outdated, obsolete, or no longer supported by the vendor, now modernization is triggered when business advancements render a deployed technology deficient, he says.

This new scenario has CIOs, including himself, modernizing faster than in past eras, Prasad says. And it’s why modernization remains a core component of the CIO role.

“Modernization means meeting today’s business needs, and that may mean we need to deploy a new version of [a technology] to get a better experience, speed, agility, or in a way that we can provide transparency,” he adds. “So, at UST we have always thought about modernization as a continuous process.”

For example, Prasad is currently modernizing the company’s CRM platform, even though the existing one would not be considered legacy tech using a traditional definition. Yet the deployed CRM wasn’t providing the capabilities UST needed for its sales department to deliver on the company’s vision.

“We weren’t having a good user experience, and sellers weren’t updating the information as they should, so we didn’t have real-time data and then the operations team had to do the data entry, so you had cost there, too, and we had reduced agility as a result,” Prasad explains.

Similar factors are at play when it comes to rationalization, which he believes should also be an ongoing concern for CIOs.

Despite the benefits these efforts bring, Prasad acknowledges the heavy lifts involved, ones that many organizations aren’t yet prepared to undertake. For example, UST still has a financial system running on premises, and because the complexity of “disentangling the financial systems from the guts of the business is challenging, it’s a change that the business isn’t willing to make right now,” he admits.

Such situations ensure modernization projects will remain a core IT task in the years ahead.

See also:

• 6 strategies for accelerating IT modernization
• 8 IT modernization traps CIOs must avoid
• Massive modernization: Tips for overhauling IT at scale

Oracle is adding a new execution layer to its Fusion Cloud Applications Suite that it says will help enterprises lower the costs of automating complex and long-running business processes with AI agents.

The execution runtime, Fusion Claw, uses a combination of a frontier model, deterministic policies, and governed execution capabilities to plan and carry out a given task or process, instead of relying for each step on AI inference, which can result in repeated model calls as the task progresses. That can help enterprises keep inference and compute costs under control, the company said.

The deterministic policies can include approved algorithms, business rules, calculations, optimization services, reconciliation logic, and transaction-processing capabilities. Enterprises can define or configure them via Fusion’s AI Agent Studio while building the agent or modifying existing agentic applications, Oracle said.

Claw then uses two built-in features, the Enterprise Operating Envelope and the Enterprise Trust Harness, to enforce those policies as controls during task execution, ensuring that the agent operates within its delegated authority and the required governance boundaries, while also generating an auditable record of agent actions and decisions, it further said.

Fusion Claw could help improve an agent’s unit economics

For Manoj Chandra Jha, principal analyst at Nord-IQ research, Fusion Claw’s approach to agentic execution is likely to help enterprises with the unit economics of deploying AI agents to automate business processes.

“By keeping the expensive model for planning and running high-volume work on cheap deterministic computation, Fusion Claw can make agentic costs both lower and more predictable for CIOs,” Jha said.

Beyond cost, Fusion Claw’s approach to separating AI reasoning from deterministic execution can also make agentic automation more reliable and repeatable, which could be “critically important” for CIOs trying to move agentic applications from prototype to production, according to Scott Bickley, advisory fellow at Info-Tech Research Group.

The deterministic controls combined with delegated authority, approvals, escalation rules and an auditable record of decisions and transactions can give enterprises a measure of “safe autonomy,” he said.

There are advantages for developers, too, especially in terms of productivity.

As the new execution layer packages up most of the underlying plumbing stack required to operationalize an agentic application, developers can focus on process design, offloading the mundane work of integrating and orchestrating the underlying components needed to put an agentic application into production, Bickley said.

That, in turn, is likely to result in business processes being automated faster, he added.

Lower AI consumption does not necessarily mean lower costs

However, that reduction in development and orchestration work does not eliminate the work required to govern agentic applications, but rather adds to the governance work required, Jha cautioned: “Development teams must encode policies and approval rules, choose autonomy levels, and verify outcomes.”

That outcome verification will also be important for CIOs in determining whether the promised cost savings and cheaper unit economics actually translate into lower costs, rather than simply lower AI consumption, according to Bickley.

While Oracle’s architecture can reduce the amount of AI inference needed for a task, the actual cost of an agentic application can vary based on factors including the actions it performs, token consumption, model used, testing, human review, exception handling and ongoing operational support, Bickley said.

As a result, CIOs should measure the cost of successfully completing a business outcome, such as resolving an accounting exception or filling a staffing gap, rather than looking only at the cost of AI units or tokens, Bickley added.

The analyst also cautioned CIOs about Oracle’s AI unit policy, which he said could introduce additional considerations into the cost of running Fusion Claw-based applications: “Unused pooled units expire without reimbursement, while Oracle can modify its action and model tables with at least 30 days’ notice.”

CIOs should demand per-outcome pricing in writing and let a bounded pilot build the business case, said Jha.

Adoption will depend on process and governance maturity

Those considerations, combined with the added governance requirements, are also likely to shape which enterprises adopt Fusion Claw first, even among existing Oracle customers.

“Existing Oracle Fusion customers with standardized processes, reliable master data, mature controls and high-volume work with measurable outcomes are likely to be the initial adopters. Finance reconciliation, supply-chain planning, staffing and other constraint-heavy processes are logical candidates because they combine analysis with calculations and repeatable execution,” Bickley said.

On the flip side, adoption will be “slower” in enterprises with heavily customized Fusion estates, fragmented data, multiple ERP platforms, weak segregation of duties, or limited AI governance, he added.

For enterprises willing to try out Fusion Claw, the execution runtime is now available as part of the Suite, Oracle said.

The company is also making 25 pre-built Claw-powered agentic applications available, including Ledger, Workforce Staffing, Shipping Consolidation, and Sales Territory Planning, aimed at helping divisional leaders, such as CFOs, CSOs, supply chain heads, and CHROs, improve productivity and reduce costs.

The company will make the other 21 apps available in October, it said.

Enterprise software budgets haven’t shrunk this year, though we keep reading they have. Boardrooms are still approving spending on new tools at a consistent pace, and Gartner’s latest forecast puts global software spend at $1.43 trillion in 2026, up more than 15% year over year. What has changed is what buyers will tolerate to get that value, and SaaS vendors who miss this distinction will have a very bad renewal season.

Headlines call it the SaaSpocalypse. What’s really happening is a hard reset on what software charges for and how long it can lock a customer in. Three-year platform commitments made sense when the underlying technology moved slowly, but now AI models turn over every six months. Ask any CFO whether locking the business into one vendor’s roadmap still feels sensible under those conditions.

What buyers want now

Buyers want the freedom to adopt an AI capability this quarter and swap it out the next without tearing their stack apart. They want tools built to work inside an agentic environment, not bolted onto one after the fact, which in practice means proper API access, structured context handoff, and role-based permissions an agent can operate within safely. Buyers also want contract terms with genuine data portability clauses. And they want proof that a product does something genuinely beyond what an off-the-shelf agent could replicate over a weekend.

That third demand is keeping vendor product teams up at night. A thin workflow layered on top of a database used to be defensible. Today it’s a prototype an engineer could build before lunch.

At renewal time, every contract now faces the same three questions.

1. What work does this tool actually remove?
2. How well does it play with the rest of the estate?
3. How painful would it be to walk away?

Vendors with good answers are growing; the rest get folded into someone else’s platform.

Cost pressure is the excuse

It’s easy to blame this on cost pressure alone. CFOs have wanted to rationalize their software stacks for years; AI just gave them the excuse to do it finally. The last couple of years were a “try everything” era. Every business is now sitting on a waste heap of tools nobody’s had the discipline to evaluate since. Industry data on SaaS management puts the average large enterprise at around 660 SaaS applications in active use, with adoption largely flat over the past two years and per-app spend keeps climbing regardless. Nobody going back to clean houses is causing that sprawl.

Cost pressure is one driver. Tool sprawl is another, and it’s the direct hangover of that try-everything period. Software pricing has run on one assumption for two decades: value scales with the number of people using the tool, but agents break that assumption completely. Once part of a workflow runs without a human clicking through it, paying per seat starts to look like paying for headcount that no longer exists. Buyers spotted this before most vendors did, and they’re negotiating accordingly.

Vendors are responding, unevenly. Deloitte’s 2026 technology predictions point to seat-based licensing giving way to hybrid models that blend usage and outcome pricing. This is messier than the analyst reports suggest. Some vendors have moved to per-conversation or per-task credits. Others found customers wanted predictability more than they wanted to pay strictly for outcomes, and pulled back toward seat-based pricing with usage caps layered on top. Nobody has fully solved it yet, so treat any vendor who claims otherwise with some skepticism.

There’s also a lot of noise about agents replacing traditional interfaces outright. Talk to the people actually running mission-critical operations, and you get a different picture. Nobody serious is letting an autonomous agent operate freely inside a production SAP environment, and nobody serious is planning to any time soon. Instead, they’re asking two much narrower questions of every vendor: can this platform give an agent the context it needs and let it act safely within limits? Does the platform add value an agent couldn’t produce on its own? Strip away the AI framing, and this is an outcomes conversation wearing new clothes: fewer incidents, faster audits, and less unplanned weekend work.

The SAP deadline nobody can ignore

For the SAP ecosystem, there’s an added forcing function. Solution Manager exits mainstream maintenance at the end of 2027, and it isn’t going alone. SAP Process Integration and Process Orchestration, both still built on the older NetWeaver stack, are retiring on the same timeline, with Cloud ALM and the Signavio portfolio positioned as the replacement. That’s a genuine architectural change, moving from an on-premises, monolithic management layer to a modular set of cloud-native tools connected through SAP’s Business AI Platform.

Every enterprise running SAP has to rebuild part of its operations toolchain regardless of what else happens in the market. The smart ones are using that forced migration as cover to consolidate around fewer, more open platforms rather than replacing what they had piece for piece. The less smart ones are treating it as a like-for-like swap, migrating their old Solution Manager processes into Cloud ALM without questioning whether those processes should exist in their current form at all. That’s a wasted opportunity. When you’re forced to rebuild the toolchain anyway, that’s exactly the moment to ask which parts should stay proprietary to SAP and which parts should sit in an open, vendor-neutral layer instead.

Every agent needs eyes and hands

This is where the real opportunity sits, and it isn’t in defending the old per-seat model or racing to absorb everyone else into a smaller stack.

Both paths have a shelf life.

Being part of a smaller consolidated stack is fine if you’re the vendor doing the consolidating. For everyone else pulled into it, whoever now owns the relationship usually squeezes price and roadmap.

The lasting opportunity is the layer that sits across systems and gives agents the two things they never arrive with: trustworthy context about what’s happening across the estate, and a governed way to act on it. Observability and automation, in plain terms. Every agent needs eyes and hands, and almost none ship with either. That means structured telemetry an agent can actually reason over raw logs, and an action layer with approval gates, audit trails, and rollback built in rather than direct write access to production systems. Get either piece wrong, and you either have an agent that’s blind or one that’s dangerous.

That cross-system layer benefits from the very churn destabilizing everyone above it. The more customers want the freedom to swap AI tools quarter over quarter, the more they need a stable foundation underneath that doesn’t care which agent is asking.

There’s a catch, and vendors building that foundation need to hear it clearly. You cannot sell openness and quietly build your own version of lock-in. The rules buyers are now enforcing everywhere else apply here too: open integration, easy exit, price it on outcomes, not seats. Vendors who understand that distinction will define the next decade of enterprise software. The ones who don’t will become the next renewal casualty.

Last month’s Claudeforce announcement by Salesforce and Anthropic may be a harbinger of agentic AI’s looming impact on business as usual in the enterprise, as industry watchers are keeping their eyes peeled for a dramatic shift in enterprise software in its wake.

“What we are beginning to see is indicative of where the industry is heading,” says Daniel Newman, CEO and principal analyst of research firm The Futurum Group. “The era of usability has arrived, and it is a combination of frontier and leading AI intelligence being able to access the high-value data that often sits trapped inside of systems of record.”

Claudeforce allows joint Salesforce and Anthropic customers to leverage Salesforce data, workflows, business logic, actions, and governance within Claude. The expanded strategic partnership built on Salesforce’s Headless 360 announcement from the TDX 2026 developer conference earlier this year, which packaged Salesforce’s AI and developer tools into a headless, API-driven layer designed to help enterprise teams build agent-first workflows.

“That was really the introduction of a new way to consume CRM with Headless 360,” says David Menninger, executive director and distinguished analyst at research and advisory firm ISG. “The new world order will be how can enterprises stitch together various applications to support their own specific business processes.”

Agentic AI will serve as the glue between systems, Menninger explains. Enterprise software such as Salesforce becomes the application that owns the data and governs the workflows and the business, while AI models such as Claude provide the semantic interface used to access the data.

Futurum’s Newman agrees.

“Using tools like Claude with tools like Salesforce and Agentforce and Data360 is what the enterprise is going to look like in the future,” he says. “We’re going to be able to take advantage of the power of these probabilistic systems to create proposals and invoices and dashboards and views of our customers that have historically been more difficult than most enterprise users want to admit.”

Usability, customization in the crosshairs

The model presented by Claudeforce would solve two of the most common complaints about enterprise software: usability and customization.

And if Salesforce and Anthropic are right about this, Newman expects a wave of new partnerships and consolidation across the enterprise software industry in the coming months. Some tools will become databases with logic, some will remain core systems and may even become bigger and more important, and some niche software and SaaS applications may disappear as AI capabilities overtake them.

“Core ERP, core CRM, core HR, most of these tools are going to see a similar sort of realignment where the models will provide probabilistic capability that uses the best of breed from your intelligence coupled with the rich, proprietary data that businesses depend on to operate,” he says.

ISG’s Menninger agrees that change is coming to enterprise software but doesn’t expect organizations to throw the baby out with the bathwater.

“Our most recent AI research suggests that enterprises are considering ways to alter their consumption and even creation of certain business applications, including CRM,” he says. “My personal belief is that the hundreds of person years that have gone into the development of these applications has created some real value that cannot be easily duplicated despite the promise of vibe coding. Remember, vibe coding is only one part of the software development lifecycle. Why not leverage these applications by incorporating them into your agentic workflows rather than trying to replace them?”

Some IT leaders are already enlisting business users to vibe code their own apps, though challenges remain for replacing enterprise stalwarts with custom solutions. After all, moving such applications into production requires an organizational discipline that supersedes vibes.

Salesforce and Anthropic are expected to show off the first fruits of their expanded strategic partnership at Salesforce’s flagship Dreamforce Conference 2026 in San Francisco this week. In August, the partners said they would launch an open beta for Claudeforce in September, with additional prebuilt skills available starting in the third quarter.

The once stable era of IT service management (ITSM) has entered a period of disruption and uncertainty. At least if you’re an investor or enterprise customer with an interest in ITSM giant ServiceNow, the signals over recent months have been hard to ignore.

Last year, the category leader delivered market-pleasing AI announcements, a record share price, and good quarterly revenue growth, as well as an interesting pivot toward cybersecurity with the December acquisition of partner Armis for $7.75 billion in cash.

But as the calendar turned to 2026, the phrase “Saas apocalypse” started to gain traction, and market sentiment about SaaS incumbents suddenly melted away, causing ServiceNow’s share price to drop 30% by mid-2026, albeit from historic highs.

What’s driving anxiety is the perception that AI agents and vibe-coding tools will soon took over many of the previously complex workflow, automation, and software tasks carried out traditionally by subscription platforms, including ServiceNow’s. Customers will stop buying SaaS subscriptions because they won’t need employees or “seats” to do this work. Instead, cheaper internal AI tools, or larger cloud platforms doing the same job, will simply automate the market away.

While some enterprise IT leaders are in fact empowering business users to vibe code their own solutions, the model for replacing vendors with vibe-coded apps remains edgy business. As a result, SaaS isn’t likely dying any more than on-premises software, though CIOs are still reimagining software’s future as AI agents advance.

So too is ServiceNow, including how it expects IT leaders to finance that future. The company’s June Financial Analyst Day 2026 presentation confirmed a shift away from subscriptions based on seats is already under way, with only 50% of the company’s Net New Annual Contract Value (SaaS jargon for new revenue) in 2025 coming from this source. Instead, growth is increasingly generated by “consumed” services such as infrastructure, integrations and connectors, AI token consumption, and cybersecurity.

AI convergence

AI is causing previously distinct sectors such as ITSM and cybersecurity to converge, with AI itself turning into a unifying AIOps front end to diverse, specialized technologies sitting below it. In this, ServiceNow looks well-placed, having added the Virtual Agent chatbot system to its Now platform as long ago as 2018, later reinforced by acquisitions, including search outfit Element AI, chatbot company Passage AI, and AIOps pioneer Loom Systems. In 2025, this evolution crystalized as the ServiceNow AI Platform, a rebranded Now platform augmented by unifying features such as the AI Control Tower.

In traditional ITSM, the platform helps teams build workflows without the need for coding in a way that simplifies complex processes. AI takes this a step further; now it becomes possible not only to generate a workflow but reason and act on it. In this, AI and ITSM look like a natural combination as each enhances the usefulness of the other.

But building a better AI front end or adding automation to workflows gets you only so far, which makes the company’s Armis acquisition, its largest ever, intriguing. Unlike previous ServiceNow acquisitions with a cybersecurity theme — Veza in 2025, Mission Secure in 2024 — Armis’s agentless platform is more than an information gathering system. It can also orchestrate actions such as isolation and blocking across a wide range of devices, including workstations, routers, switches, firewalls, and the long tail of often forgotten medical scanners and IoT devices.

Nevertheless, it is the ability to build an accurate inventory that explains why the acquisition happened at an eye-watering 23 times annual revenue, says Brad LaPorte, a former Gartner analyst who now works with Lionfish Tech Advisors. ServiceNow didn’t buy Armis to sell it as a cybersecurity sideline because its $340 million annual revenue and annual growth rate are too small to justify that.

“Nobody pays 23 times revenue for a product. They pay for a position. That single financial fact explains most of what customers are about to experience, good and bad,” says LaPorte. The limitation of today’s ITSM and configuration management database (CMDB) systems is that workflows assume the CMDB is accurate when it’s often a work of fiction.

“Everyone reconciles to it. Nobody believes it. Every attack surface tool on the market can tell you what it found. Not one of them can tell you who is going to fix it by Friday,” LaPorte says.

So, buying Armis is less about adding cybersecurity than supercharging the company’s traditional ITSM workflows, which have recently been given an AI makeover. At the same time, by making its platform appealing to hospitals, utilities, and manufacturing, ServiceNow can attract customers in completely new sectors.

According to LaPorte, ServiceNow customers should be alert to the ways this changes their relationship. Customers are likely to experience Armis being heavily marketed to them at contract renewal. In theory, this is good, assuming they can refuse. But they might find that the financial engineering and incentives behind this could be complex to untangle and don’t always work in their favor over the contract period.

Armis will also bring ServiceNow into competition with a new set of rivals, LaPorte notes, and bring into the fold a new buyer, the CISO, it has never previously had to win over. CISOs are skeptical by nature as well as sensitive to the occasional security weaknesses that have affected ServiceNow itself.

“Armis was Switzerland. It integrated with everybody, including every ITSM platform that competes with ServiceNow. That neutrality was part of the product,” LaPorte says. “That is gone now. This just moved everybody’s negotiating position.”

Consumption pricing

Several experts spoken to for this article agreed that the SaaS apocalypse idea is overblown in relation to ServiceNow. Its incumbency protects it from AI because reproducing ServiceNow’s capabilities using vibe-coded AI could prove more challenging than people assume. However, there is consensus that the convergence of AIOps and cybersecurity will be highly disruptive in the ITSM sector.

“ServiceNow is competing with Microsoft, which can bundle, and with the model vendors, who are climbing up into the application layer,” argues Lionfish Tech Advisors CEO Rob Smith, another ex-Gartner analyst. “ServiceNow’s defense is not that it has a better model, which it doesn’t. Its defense is that it knows the steps in your process, and that is expensive to re-create.”

Chris Selland, founder of research company Differential Factor, who lectures at Northeastern University on entrepreneurship and disruption (and has written on SaaS for CIO.com), agrees that ServiceNow’s Armis acquisition looks like an important piece of a puzzle.

“The Armis deal extends that map into everything that was never in the CMDB, such as IoT and medical devices. It’s a defense of their asset graph,” he says. And the company probably sees itself as having something to defend. “ServiceNow is in around 90% of the Fortune 500, so yes this is fundamentally a ‘sell more to the base’ strategy,” argues Selland.

“The threat was never that AI writes competing enterprise software; it’s seat compression and the collapse of per-seat pricing. That threatens the SaaS industry’s core revenue model,” Selland contends.

ServiceNow understands this, which is why it is moving toward a consumption-based model. The question is how this will change the balance of power with customers at a time when open-source and open-weight models are driving down AI pricing and competition is fierce, including from large cloud platforms.

With more players competing for business against specialists such as ServiceNow, this could give buyers a lot more leverage if they understand how to manage hidden cost traps.

“Consumption-based pricing is much better for both buyers and sellers than seat-based pricing, although it can lead to nasty surprises for buyers if they’re not careful about monitoring what their employees are doing,” Selland says.

A recent study conducted by Nitro found that 75-95% of the employees and executives surveyed use AI for document processing—including data extraction, PDF tasks, and contract summaries.

However, when these individuals don’t have access to the right kind of AI tools, they report turning to unapproved—or shadow IT—solutions to speed up workflows, which creates security and compliance risk.

Read the report

To reinforce the importance of providing teams with the right AI tool for the right job, let’s look at the difference between chatbots and functional AI in terms of automating document workflows.

Chatbots are great for ad hoc tasks that follow a pre-programmed set of actions, but they aren’t designed to enforce consistent rules for formatting, redaction, or compliance, or to extract data hidden deep in document tables, images, or free text.

Unlike chatbots, functional AI can physically execute redaction, conversion, and data extraction tasks directly within business processes and systems, rather than simply responding to prompts.

This guide explains why scaling document workflows requires both conversational AI to answer common questions and functional AI to perform repeatable tasks on a high volume of documents with consistency, control, and predictable cost.

Chatbots vs. functional AI: What’s the difference?

Chatbot AI and functional AI play distinct roles in document workflows: AI-assisted chatbots answer questions and help users understand documents through conversation. Functional AI performs tasks directly on documents, such as redaction, data extraction, and file conversion.

What chatbots and functional AI do best:

Chatbots:

• Respond to prompts and questions
• Help summarize or generate content
• Improve individual productivity

Functional AI:

• Execute document tasks automatically
• Process files at scale
• Integrate into workflows and systems

Benefits of using functional AI to automate document workflows at scale

Nitro

Functional AI tools autonomously execute editing, redaction, conversion, and data extraction tasks within workflows, not just through user prompts. This intelligent automation provides several benefits for teams that process a high volume of documents:

Improve redaction and compliance

AI can identify and remove sensitive information across large document sets, applying consistent rules without relying on manual review.

Simplify conversion and document handling

Users can reduce friction and save time using the same tool to convert files, edit PDFs, and standardize formats within a single workflow.

Extract structured and unstructured data

Functional AI can pull key data from contracts, forms, tables, handwritten notes, and PDFs, turning static documents into usable information.

Reduce tool sprawl and shadow IT

By consolidating document tasks into a single platform, functional AI reduces the need for multiple point solutions and unapproved tools.

Perfectly provision license utilization

Universal access to core document features allows organizations to align licenses with actual usage instead of over- or under-provisioning.

Create more predictable software costs

Replacing fragmented tools that incur usage-based overages with a functional AI solution that offers a controllable pricing structure makes costs easier to forecast and control.

How Nitro’s AI-powered tools fit into document workflows

Nitro understands the importance of giving your team the right AI tools at the right time. So, we offer both generative AI and functional AI solutions that support and simplify document workflow automation.

Nitro’s AI assistants improve how teams interact with documents

Nitro’s AI-assisted solutions, like Document Assistant and Knowledge Assistant, reduce time spent searching for information or learning how to use our solutions.

• Document Assistant: Allows users to ask questions about a PDF, summarize content, or translate information
• Knowledge Assistant: Provides real-time help with product features and workflows

Nitro’s functional AI tools automate document tasks at scale

Nitro’s functional AI tools reduce manual effort, improve accuracy, and allow teams to handle higher document volumes without increasing workload.

• Nitro Smart Redact: Identifies sensitive information in documents and flags it for removal, reducing manual review time
• Form Extract: Pulls key information from PDFs and converts it into structured data
• Table Extract: Transforms table data into clean, usable spreadsheets
• Form Create: Converts static documents into fillable forms
• Field Detection: Automatically places signature and input fields for document workflows

All Nitro AI-powered solutions include enterprise-grade security and compliance that safeguards sensitive data throughout the document lifecycle. Visit the Nitro Trust Center to learn more.

Functional AI is setting the standard for document workflow automation

Nitro

Our research is clear: When AI provides specific, measurable benefits to your document workflows, the results are high adoption, time savings, and measurable ROI.

If you want to transform and automate your document workflows, Nitro’s functional AI solutions are a top choice for high-volume document processing, consistent, rules-based automation, and reduced reliance on manual work.

Discover Nitro’s AI workflow tools.

Research shows that humans play a role in 60% of breaches that expose sensitive data. That “role” often involves an employee falling for a phishing scam or using PASSWORD for their login credentials, but data exposure can also be a result of how your business redacts sensitive and personally identifiable information (PII) in your documents.  

Historically, manual, “black-box” redaction was considered best-practice, but this approach only obscures data, it doesn’t permanently remove it. 

As regulations governing data security get stricter and AI-powered redaction solutions become more accessible, organizations—especially those in highly regulated industries—are re-evaluating their PDF redaction solutions.

How manual PDF redaction is different from AI-powered PDF redaction

The primary difference between manual and AI-powered PDF redaction is who (or what) you rely on to do the heavy lifting.

Manual redaction defined

Manual redaction is a human-driven process where individuals visually scan text, select content, and apply black boxes or remove the text before sharing or storing the file.

Manual redaction is only as effective as the reviewer, which makes outcomes highly variable, especially under time pressure or high document volume.

AI-powered redaction defined

AI-powered redaction uses machine learning and natural language processing (NLP) to automatically detect and remove sensitive information from documents. The system is trained to recognize patterns, language cues, and contextual signals in PDFs as well as scanned images, handwritten notes, text-heavy documents, metadata, and embedded scripts.

For example, Nitro Smart Redact can identify structured data, like Social Security numbers and bank accounts in a payroll document, as well as unstructured, free-form data, like “in April 2022, Sarah was diagnosed with cardiovascular disease.”

How to choose the right redaction solution for your organization

Nitro

Manual redaction may work for small organizations that handle a low volume of documents. But for most businesses, an AI-powered PDF redaction solution that will scale as your needs change is a smart investment.

Here are six factors to consider when evaluating AI-powered redaction solutions:

Document volume and size: Look for a solution that can handle your current document load and scale to meet future demand without slowing down processing times or requiring additional manual effort.

Data type: YourPDF redaction tool must be able to accurately identify a wide range of sensitive information—from PII to financial data.

Data location: The solution should detect sensitive data in visible and hidden layers, like metadata, embedded text, annotations, comments, form fields, and image-based content.

Compliance requirements: Choose a solution that supports compliance with your industry’s regulatory obligations, such as GDPR, HIPAA, or other data protection standards.

Integration with existing systems: Pick a PDF redaction tool that integrates with your existing document management systems, cloud storage, and workflows to maintain productivity and reduce the need for additional tools.

Data security and AI training policies: Verify how the redaction solution handles your data. Look for clear policies that protect sensitive information, prevent data reuse, and keep your content private and secure.

Why Nitro is a top choice for AI-powered PDF redaction

Nitro

Nitro Smart Redact is an AI-powered PDF redaction solution that balances speed and accuracy with control and security, allowing teams to redact sensitive information quickly while maintaining full oversight and compliance.

• Detects over 30 categories of regulated PII in seconds
• Uses advanced NLP to identify unstructured PII that manual or pattern-based methods miss
• Finds and redacts PII in scanned documents, image files, and handwritten notes
• Gives users the ability to manually add, adjust, or remove redactions
• Integrates with existing tools, including Microsoft 365, Salesforce, and cloud storage
• Processes documents in secure, temporary sessions 
• Permanently removes hidden data, including metadata and embedded scripts
• Never uses your documents to train or improve external AI models

The best solution? AI-powered PDF redaction, but keep people in the loop

The most effective way to identify and permanently remove sensitive data from PDFs is a solution that uses AI to quickly find information hidden deep in documents and humans to manually review and adjust results for accuracy. 

Speak with a Nitro team member to learn how Nitro’s AI-driven Smart Redact technology provides a faster, safer way to prepare documents for secure sharing.

Why do so many PDF editing and eSignature tools fail to scale across teams? Three persistent problems stand out:

• Unpredictable pricing that becomes more expensive as usage increases
• Limited access to advanced PDF features
• Difficulty automating document workflows across teams

The good news is that even teams that process a high volume of documents can reduce their costs and get more value from their PDF solutions by selecting solutions with built-in AI, predictable pricing, flexible licensing, and scalable, automated document workflows.

In this article, we’ll cover:

• Why you’re paying too much for too few features
• How AI makes PDF editing, eSigning, and redaction tools accessible to everyone on your team
• What to look for in a scalable, cost-efficient PDF solution

Why many incumbent PDF tools are expensive and inefficient at scale

Many PDF tools were designed for individuals or small teams rather than scaling teams. As organizations expand usage, these tools become harder to manage, more expensive to maintain, and less effective at supporting high-volume document workflows.

Here are three ways PDF tools can impact your budget and your team’s productivity:

Unpredictable pricing increases total cost of ownership

If your PDF solutions rely on per-user licensing, feature-based tiers, or usage caps that trigger additional fees, as demand for the tool increases, your costs become harder to forecast and control.

Limited access to features reduces productivity

When full PDF editing functionality is restricted to a small group of licensed users, other team members start looking for (often unsanctioned) workarounds or waste time waiting to complete basic tasks like editing, converting, or compressing documents.

Rigid licensing leads to over- and under-provisioning

Legacy licensing models rarely align with how teams actually work. As a result, organizations often over-purchase licenses to avoid bottlenecks or under-provision and create access constraints.

How AI makes PDF tools more scalable (and more affordable)

Nitro

AI-powered PDF tools improve scalability by automating repetitive tasks, simplifying complex workflows, and making advanced features accessible to all users.

Automated document workflows reduce manual effort

These tools automate tasks like table and data extraction, form processing, and file conversion, allowing teams to process higher document volumes without increasing headcount.

Natural language document interaction removes complexity

Natural language processing (NLP) lets business users edit, summarize, or extract information from PDFs using simple prompts. This eliminates the need for specialized expertise and reduces reliance on a small group of advanced users.

Intelligent data recognition and redaction improves efficiency and security

Advanced AI tools can identify, extract, and redact sensitive information from structured and unstructured data sources. This speeds up document review and compliance workflows while reducing the risk of human error.

How Nitro’s PDF solutions reduce cost and increase scalability with AI

Nitro’s AI-powered PDF solutions are designed to solve the cost and scalability challenges tools like Adobe Acrobat create.

Key benefits of Nitro’s AI-driven PDF solutions

• Predictable pricing models: WithNitro’s flexible pricing plans there are no overerages, no forced bundles, and no per-seat penalties.
• Flexible licensing: Nitro’s licensing models are designed to match how people actually use PDF tools, so it’s easier to give everyone the access they need without paying for unused capacity.
• Built-in AI: Every Nitro plan includes AI tools, so your whole team gets AI-powered document capabilities without increasing cost or training requirements.
• Administrative control: The Nitro Admin Portal lets IT provision users, reassign licenses, and manage feature and AI access by department in real time, so entitlements move as fast as the business does.
• Expert support: Whether you’re a five-person team or a global enterprise, our dedicated support specialists are available 24/7—from deployment planning to daily troubleshooting.
• Enterprise-grade security and compliance: Built-in protections such as encryption, access controls, and audit trails help safeguard sensitive data throughout the document lifecycle. Visit the Nitro Trust Center to learn more.
• Proven customer satisfaction: Nitro has a 95%+ customer satisfaction rate and was selected as a TechRadar #1 PDF Editor for Businesses. 

Professional PDF tools don’t have to blow your budget

Nitro

You don’t have to choose between affordable PDF tools and scalability. Nitro’s AI-powered PDF tools give you cost control and the features you need. Replacing your legacy PDF tools with Nitro solutions that are designed for high-volume document workflows, your team can reduce costs, improve productivity, and expand access to essential tools without adding complexity.

Let the Nitro team show you why 67% of the Fortune 500 trust our AI-powered PDF editing, eSign, and redaction solutions. See plans and pricing or get in touch with sales today.

Docusign may be the most widely used eSignature platform, but many teams run into the same issue as they scale—the more documents they send, the harder it is to predict what they’ll actually pay. The risk of high overage costs paired with complex pricing structure is driving teams to look for an alternative to Docusign in 2026.

This buyer’s guide breaks down why those challenges matter, what to look for in an eSignature solution, and how leading Docusign alternatives—like Nitro Sign—compare for teams that send a high volume of documents but want simpler pricing and fewer surprises.

Nitro

Why some teams are looking for alternatives to Docusign

Three trends drive teams to look beyond Docusign:

• Bills that increase unpredictably as usage grows
• Difficulty understanding what features are included vs. which are paid add-ons
• Pricing models that don’t scale well with high document volume

Here’s a more detailed look at each of these challenges.

Docusign bills become unpredictable as usage grows

Many organizations encounter unexpected costs as usage increases. Envelope limits, counting methods, and per-transaction pricing can quickly turn a straightforward Docusign subscription into an unpredictable expense.

Impacts may include:

• Budget overruns tied directly to business growth
• Paying for documents that are sent but never completed
• Difficulty forecasting total cost at scale

Docusign pricing doesn’t clearly indicate which features are included

As platforms expand into broader “agreement management” offerings, pricing and packaging become harder to navigate.

Common issues include:

• Paying for features that aren’t widely used across the business
• Add-ons or higher tiers required for AI-enabled capabilities
• More complex setup, onboarding, and contract evaluation

Docusign pricing models don’t scale as volume increases

For teams that process a high volume of documents, how usage is counted matters as much as price. Counting envelopes when sent, rather than when completed, accelerates usage limits and increases costs.

This often leads to:

• Rising costs as document volume grows
• Paying for incomplete or abandoned agreements
• Misalignment between pricing and actual business value

What to Look for in a Docusign Alternative

When evaluating alternatives to Docusign, focus on eSignature solutions that offer these four capabilities:

Pricing that scales with your usage

Look for pricing models that:

• Don’t penalize you for sending more documents
• Scale efficiently as adoption increases
• Are based on completed agreements where possible

Transparent licensing and contract terms

Choose platforms where:

• Pricing is easy to understand upfront
• Key features—such as SSO, support, and analytics—are included
• Renewal terms are clear and unambiguous

The right level of functionality (not just the most features)

Your eSignature platform should match how your team actually works—whether that’s simple document signing or more complex workflows.

Security and compliance you can trust

Any alternative must meet eSignature security standards, including:

• Secure document handling and encryption
• Audit trails for tracking activity
• Compliance with relevant regulations and standards

Nitro

Docusign alternatives for teams in 2026

 How to choose the right Docusign alternative for your organization

Here are five specific factors to consider when evaluating alternatives to Docusign:

• How does the platform charge for usage?
• How predictable are costs as your volume grows?
• Are essential features included, or sold separately?
• Does the platform match how your team actually uses eSignature today?
• How easy is it to scale across teams without increasing complexity?

Nitro Sign offers a full suite of eSigning features at a lower price than Docusign, plus:

• Only completed agreements count
• Twice as many envelopes allowed per user
• SSO, support, and analytics are included without add-on fees
• Pricing is designed for high volumes and predictable costs
• No penalties for exceeding usage limits

Nitro

Curious why teams that want to control costs without sacrificing features or security choose Nitro Sign a top alternative to Docusign?

Speak with one of our eSignature experts or sign up for a free trial of Nitro Sign.

Too many businesses in highly regulated industries—such as healthcare, government, legal services, and insurance—still rely on manual, “black-box” redaction workflows.

This approach may obscure sensitive information, but it doesn’t permanently remove it, which can lead to compliance violations, potential litigation, or regulatory fines.

Nitro Smart Redact is an AI-powered solution that removes sensitive data from documents with permanent, untraceable redactions. It combines automated PII detection to surface regulated data along with manual controls for sensitive business information, allowing teams to flag content, automatically redact documents, and manually customize reviews that need human oversight.

In this guide we explore how Smart Redact:

• Simplifies permanent, irreversible redaction
• Identifies sensitive structured and unstructured data
• Provides enterprise-grade security
• Reduces turnaround times with automation
• Minimizes human error

How is Smart Redact different from other automated AI redaction solutions?

Pattern-based matching tools, like those used in Adobe Acrobat, use predefined formats and keyword matching to locate sensitive data. This approach often misses information in free-form text, like “John lives on Main Street” or “her social ends in 5678.” Smart Redact catches it because it understands context.

AI-only platforms—like Redactable—offer automation, but they require teams to maintain a separate redaction tool. That means two subscriptions, two interfaces, and double the work.

Nitro Smart Redact does things differently, with built-in features that support the full document lifecycle all in one place:

• Instantly detects over 30 categories of regulated Personally Identifiable Information (PII)
• Uses advanced natural language processing (NLP) to detect unstructured PII that manual or basic pattern searches miss
• Automatically finds and redacts sensitive PII from scanned documents, image files, and handwriting
• Groups suggested redaction by category and quality-tests them for precision
• Provides total visibility and complete control to instantly add, adjust, or remove redactions
• Integrates with the tools your team already uses, including Microsoft 365, Salesforce, and cloud storage
• Manages AI documents in a temporary session with no storage or data retention
• Removes visible and hidden data, like metadata and scripts

Nitro

Does Smart Redact provide enterprise-grade security and compliance?

Absolutely. Smart Redact has security built into every layer to support companies operating under strict regulatory oversight:

• Processes documents in temporary sessions
• Encrypts files in transit and at rest
• Deletes document data after processing
• Never uses content for generative AI training
• Identifies and removes hidden metadata, annotations, and scripts
• Adheres to international security standards: ISO 27001, SOC 2, HIPAA, and the EU-U.S. Data Privacy Framework

Visit the Trust Center to learn more about Nitro’s commitment to responsible AI development and data privacy.

Why is Smart Redact the best automated AI redaction solution for regulated industries?

Nitro Smart Redact is built on the same trusted Nitro infrastructure that powers the document workflows of over 67% of Fortune 500 firms.

Legal

Legal teams use Smart Redact to maintain privilege, meet discovery deadlines, and reduce manual review time by:

• Using NLP to find PII buried in extensive legal documents
• Automatically identifying sensitive data, even in scanned documents or images
• Validating redactions with confidence scoring
• Supporting manual edits when required

Government

Public sector organizations rely on Smart Redact to balance information transparency with data protection by:

• Automating detection of over 30 PII categories
• Using NLP to understand context, not just patterns
• Grouping results by category and confidence level to quickly isolate high-risk items
• Providing manual override tools and real-time previews

Healthcare

Smart Redact helps healthcare professionals protect patient privacy without disrupting care by:

• Automating de-identification of direct identifiers like names, addresses, and dates of birth
• Permanently and irreversibly redacting Safe Harbor elements, such as full dates of treatment and precise geography
• Integrating OCR to redact structured and unstructured content, including handwritten notes and image files

Insurance

Smart Redact helps insurance teams act quickly while maintaining visibility and control of sensitive data by:

• Automatically identifying and redacting account numbers, birthdates, and contact information
• Centralizing litigation preparation, internal reviews, and regulatory reporting
• Accelerating processing time and reducing risk

AI-powered redaction is changing how we handle sensitive information

Nitro

From legal confidentiality to sunshine laws to HIPAA compliance, Smart Redact is built for accurate, fast, and secure data redaction. By combining AI automation, NLP, OCR, and manual control, Smart Redact helps businesses in highly regulated industries avoid compliance violations, regulatory fines, or litigation.

Learn how Nitro’s AI-driven Smart Redact technology provides a faster, safer way to prepare documents for secure sharing, or contact a Nitro expert to get started.

If your team is re-evaluating Adobe Acrobat’s place in your 2026 tech stack, the question isn’t just what the software can do, but whether it aligns with your evolving budget and productivity goals.

Including Acrobat in your stack is becoming increasingly expensive and difficult to manage due to:

• Frequent price increases
• Overlapping licenses that add overhead
• Underutilized features that waste resources

As a result, the conversation is shifting away from “How do we navigate rising costs, complexity, and AI compliance requirements?” to, simply, “Is there a better alternative to Adobe Acrobat?”

In this guide, we break down:

• How to stop overpaying for licenses that aren’t being used
• How to select a PDF editing solution that does exactly what you need it to do
• Why Nitro PDF is emerging as a leading choice for organizations focused on experience, value, and scalability for IT and procurement-led buying decisions

Nitro

Why teams are looking for Adobe Acrobat alternatives in 2026

For organizations that use Adobe Acrobat, frustrations tend to build over time—and they usually come down to the same three things:

Rising costs that keep climbing

What starts as a manageable per-seat subscription becomes harder to justify as Adobe raises prices and layers in paid add-ons. The AI tools, advanced features, and admin tools that should be standard all require extra cost or higher priced plans.

Licenses that are hard to manage

Adding or removing users, adjusting seat counts, or untangling Adobe from a broader Creative Cloud agreement is rarely straightforward. The result is overspend on unused seats and a licensing structure that doesn’t flex with the business.

Tools that take time to master

Adobe has its own unique UI, meaning new users need training. This inevitably extends onboarding and impacts productivity when teams grow or employees leave.

Adobe Acrobat alternatives for teams in 2026

Why Nitro PDF is the smart alternative to Adobe Acrobat

Nitro

Nitro PDF eliminates the high costs, confusing licensing, and forced bundling often associated with Adobe Acrobat:

Transparent pricing without overage surprises

Nitro addresses one of the biggest Acrobat pain points—cost unpredictability—with clearer, more controllable pricing structures that often save businesses up to 30% compared to Adobe.

Simplified licensing and reduced vendor sprawl

By combining PDF and eSignature capabilities with AI intelligence in every plan, Nitro makes it easy to provision users, reassign licenses, and control feature access by department with no minimum seat commitments, reducing the need for multiple vendors and minimizing license sprawl.

Intuitive interface that accelerates time to value

Nitro PDF’s user-friendly interface mirrors the Microsoft Office ribbon UI and Apple toolbar, providing an intuitive experience for both Windows and Mac users.

Strong governance/data privacy

Nitro meets internationally recognized data protection standards and certifications, including ISO 27001, SOC 2, HIPAA, and the EU–U.S. Data Privacy Framework. Visit the Nitro Trust Center to learn more.

Administrative control and expert support included

With powerful analytics, admin tools, and 24/7 expert support included in every plan, you can track ROI, turn document data into actionable insights, and manage licenses, users, and services with no separate admin console fees required.

Nitro

Proven customer satisfaction

With Nitro’s 95% customer satisfaction rate and distinction as a TechRadar #1 PDF Editor for Businesses, we’re proud to be the trusted choice for 67% of the Fortune 500.

How to choose the right Adobe Acrobat alternative for 2026 and beyond

If your team is looking for an alternative to Adobe Acrobat in 2026, Nitro PDF can help you balance PDF editing capabilities with long-term affordability and ease of growth. To discover how Nitro PDF’s straightforward licensing, simplified tech stack, and AI-powered automation can lower costs, boost workflow efficiency, and provide greater control over how documents move through your business, speak with one of our PDF experts or sign up for a free trial of Nitro PDF.

The first wave of quarterly earnings from major enterprise software vendors suggests that while AI is beginning to reshape enterprise technology spending, it has yet to produce the sharp decline in software demand that some industry observers have dubbed the “SaaSpocalypse.”

The latest results (Q2) from ServiceNow, SAP, and IBM, read against several prior quarters, showed continued growth in cloud and software businesses, though IBM reported that some software transactions slipped as customers prioritized spending on AI infrastructure instead.

Executives at all three companies said enterprises continue to invest in core software platforms while embedding AI capabilities into those environments.

SAP addressed the debate directly during its earnings call.

“While there has been… massive noise around the alleged SaaS apocalypse over the last quarters, the underlying trajectory of our business remains fully intact,” CFO Dominik Asam said, citing continued growth in SAP’s cloud backlog.

Enterprise software demand continues

ServiceNow’s subscription revenue growth has risen for five straight quarters, from a low of 19% in early 2025 to 23% in constant currency in the quarter reported July 22, according to the company’s earnings releases.

Current remaining performance obligations grew 21.5%, AI annual contract value exceeded $1 billion for the first time, and the company’s renewal rate held at 98%, executives said during the company’s earnings call.

Similarly, SAP reported 24% cloud revenue growth, 26% growth in current cloud backlog and 27% growth in Cloud ERP Suite revenue. Its cloud revenue has remained in a narrow band of 25% to 27% growth at constant currency for four straight quarters. SAP’s CEO Christian Klein said AI and SAP Business Data Cloud were included in more than 90% of the company’s 50 largest customer deals during the quarter, while Asam said SaaS and platform-as-a-service revenue continued to grow “far above the overall market.”

IBM’s software revenue growth, however, decelerated the sharpest of the three, slowing to 5% after peaking at 14% in the fourth quarter of 2025. That softness traced to one product line: Transaction Processing revenue, the license-based software tied to IBM’s Z mainframe line, fell during the quarter, while Data revenue grew 19% and Hybrid Cloud, which includes Red Hat, grew 11%, the company said in its Q2 results statement.

“The vast majority of our software business, about 80% of that revenue, is recurring in nature and delivered healthy growth in the quarter, reflecting the demand for our offerings and giving us confidence in our growth opportunity,” IBM CEO Arvind Krishna said during the earnings analyst call.

The earnings also showed increasing adoption of AI capabilities within existing enterprise software platforms.

ServiceNow said the number of customers with agentic AI in production increased ninefold over the past nine months. Its CEO Bill McDermott said the percentage of renewal customers purchasing agentic AI for the first time doubled both sequentially and year over year.

“When will customer deployment of AI mark an inflection point for ServiceNow’s growth? Here’s the answer. It already has,” McDermott said during the analyst call.

SAP said customer demand for its autonomous enterprise strategy expanded following its Sapphire conference, while beta programs for Business AI Platform and Joule Work were oversubscribed shortly after launch.

The earnings, however, do not necessarily mean enterprise software consumption is unchanged, according to George Brocklehurst, managing vice president at Gartner.

“The market should not confuse stable SaaS revenue with stable SaaS business models,” Brocklehurst said. “Agentic AI changes how value is consumed, and that transition can begin well before it becomes visible in aggregate revenue numbers.”

AI changes enterprise buying patterns

IBM’s earnings offered an early indication of how AI infrastructure investments are beginning to influence enterprise purchasing decisions.

The company’s chief financial officer Jim Kavanaugh said some customers redirected spending toward servers, storage and memory to secure AI infrastructure, delaying enterprise licence agreements that are typically treated as capital expenditure. Subscription and consumption-based software, which customers generally classify as operating expenditure, continued to perform well, he said during the call.

Krishna said IBM expects long-term enterprise value to shift toward software that orchestrates AI models, governs enterprise data and manages AI deployments across hybrid environments rather than toward foundation models themselves.

Sanchit Vir Gogia, founder and chief analyst at Greyhound Research, said IBM’s quarter illustrates changing technology spending priorities rather than a broad decline in enterprise software demand.

“Infrastructure spending is growing several times faster, yet software expenditure keeps rising,” Gogia said. “The sharper reallocation is happening inside the application estate itself. Strategic systems of record are being protected. Duplicate copilots, marginal point tools and unused licences are being challenged.”

Gogia said traditional SaaS metrics such as backlog and renewal rates should be interpreted alongside measures of AI adoption and software utilization because they reflect contractual commitments rather than how enterprises ultimately consume software.

“Strong backlog proves commitment rather than fresh demand, and a 98% renewal rate does not reveal what was conceded to win it,” he said. “The decisive measure is no longer how many people log into software; it is how much governed work the software completes.”

Brocklehurst said the industry’s transition is likely to unfold over several years rather than through a sudden collapse in enterprise software demand.

“The ‘SaaSpocalypse’ will not begin when enterprises stop buying software,” he said. “It will begin when enterprises stop paying for access and start paying for execution.”