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Key Research Findings

81%

Fragmentation Is the Operating Reality

62%

The Push Toward Unified Systems

8 in 10

Total Cost Defines Value

77%

Policy Should Decide the Routine

The two waves at a glance: single unified system 18% to 21%, held; broad total-cost view 78% to 82%, held; managers spend hours on routine decisions 62%, new; agree policy should decide the routine 77%, new.
Chapter 01

How Does System Fragmentation Shape the HR and Payroll Buying Decision?

Most organizations still run HR and payroll across more than one system, and manual work is what keeps them aligned. Across 428 interviews, 81% are not on a single unified system. This operational friction is the baseline shaping how buyers evaluate HR and payroll technology, and it is the root cause they feel everywhere else.

“From my experience, having everything in one system is much easier. It's a lot cleaner. Things operate smoother. Changes and modifications are instantaneous. It's always the preferred method to have things done.”

— Payroll Manager, communications

Listen
HR, payroll, time and benefits systems linked by manual re-keying. Second wave: 64% need manual work to keep HR and payroll aligned; 67% hold people data in two or more systems; 49% see records drift out of sync; 38% say someone spends hours a week reconciling.
Key Finding
Why Do Fragmented HR Stacks Create Demand for Unified Control?

System Architecture, Integration Friction, and Operational Control

33%

rely on fully manual synchronization and reconciliation

Key Takeaways
01
02
Strategic Implication
How HR and payroll data stays in sync
33%
Manual synchronization and reconciliation
Manual synchronization and reconciliation
33%
Mostly automated, with manual exceptions
31%
Single system or outsourced, nothing to sync
19%
Automatic, little manual work
17%
Listen

“We're pretty good at keeping it aligned. At the expense of one person that is basically focused on that. Which, again, is terrible use of people. That's why I think, going with a system that is integrated and more automated. Would be a big win for us.”

Chief Commercial Officer, professional services
when asked about what keeping systems aligned costs
Listen

“At least once a month, our information just gets all messed up, and we have to input it again.”

CEO, real estate investment
when asked about how often records fall out of sync
Alex Bradley, Chief Financial Officer, G2

“The real expense of a fragmented back office is the manual work no one prices at purchase. This research puts numbers to what finance leaders feel every close cycle: disconnected systems are a recurring tax, and consolidating onto one is as much a cost decision as an operational one.”

Alex Bradley — Chief Financial Officer, G2
Chapter 02

Why Do HR and Payroll Buyers Frame Consolidation as a Risk-Reduction Strategy?

Buyers consistently describe wanting a single system with one source of truth. They frame consolidation as risk reduction, not convenience: fewer integration points, fewer manual touch points, and a smaller surface area to secure. Asked directly in the second wave, 62% would welcome one unified system.

“I think that it would change probably for the better if we had one consistent system. Then it would be less chance of errors between the systems, and make our job easier.”

— Senior Finance Specialist, government

Separate HR, payroll, time, benefits and recruiting systems flowing into one system with one source of truth. 81% of 428 leaders across both waves are not yet on one system; in the second wave 62% would welcome one unified system, and 87% of those in fragmented setups would welcome it.
Key Finding
81% Have Not Consolidated, and Most Would Welcome One Unified System

Unified System Demand and Risk Reduction

62%

would welcome one unified system for HR and payroll

Key Takeaways
01
02
Strategic Implication
Reaction to one unified system
38%
Would welcome one unified system
Would welcome one unified system
38%
Would welcome it, with reservations
25%
Already unified or expect little practical change
30%
Would prefer to keep separate systems
6%
Neutral
2%
Listen

“So we wanted a solution that would be one platform that covered everything had one app that had all of those pieces in it so the employees didn't have to learn different systems and jump from one system to another to get their daily work done.”

Chief Information Officer, nonprofit social services
when asked about why one platform was the goal
Listen

“I generally agree. If our HR and our software were together, that would make those types of decisions automated. But because our systems are separate, we do have separate rules with regards to payroll and HR that are not automated because our systems do not do that. But I strongly agree that would be a good thing if they did.”

President and CEO, medical staffing
when asked about why separate systems hold automation back
Priti Patel, Chief People Officer, G2

“For years, HR and payroll were bought feature by feature. What stands out here is that leaders are done managing the seams between systems. The teams that feel in control are the ones who stopped reconciling by hand and moved to a single source of truth, and that is a people decision as much as a technology one.”

Priti Patel — Chief People Officer, G2
Chapter 03

What Gives HR and Payroll Leaders Confidence in Compliance and Security?

Compliance and security are on every leader's mind, and keeping up takes constant effort. Where leaders feel exposed, fragmentation is the common thread: 24% of second-wave leaders in fragmented setups feel exposed on compliance, against none on a unified single system.

“I am very confident that our organization is meeting all the compliance that is required right now because it's on one system. We have not had any problems, so I'm very confident.”

— Vice President, healthcare

Listen
Three shields: in the second wave, 24% of leaders in fragmented setups feel exposed on compliance, 2% in partially unified environments, and 0% on a unified single system.
Key Finding
Compliance Takes Constant Effort, and Exposure Sits Where Data Is Fragmented

Compliance and Security Confidence Models

57%

still track at least some regulatory change by hand

Key Takeaways
01
02
Strategic Implication
Compliance takes constant effort
57%
Track at least some regulatory change by hand
Track at least some regulatory change by hand
57%
Manage compliance across several states or countries
52%
Have had a compliance scare, close call, or incident
45%
Name manual file transfers, disconnected-system errors, or integrations as the biggest risk
19%
Listen

“And then I think that having a lot of disparate systems like my current company does that are semi-connected [or] connected, but there's always going to be the risk of an integration not functioning properly.”

Research participant, global manufacturing
when asked about the risk of integrations
Listen

“I'm fairly confident that we're meeting our compliance requirements, but it's something that requires constant attention rather than something we can assume is handled automatically. That confidence comes from regular audits, established payroll controls, compliance reviews, system reporting, and staying current with regulatory changes.”

Head of Payroll, regional healthcare
when asked about confidence through internal controls and oversight
Priti Patel, Chief People Officer, G2

“The finding that stays with me is that most leaders' confidence in compliance is manual. It holds because people watch it constantly, not because the systems handle it. That is a heavy load to carry, and it is why moving to one unified system reads as risk reduction, not convenience.”

Priti Patel — Chief People Officer, G2
Chapter 04

How Do HR and Payroll Buyers Define and Evaluate Total Cost?

Buyers have moved past subscription price as the measure of value. In both waves, about eight in ten evaluate through a total-cost-of-ownership lens that includes implementation, services, and ongoing support, and dedicated human support is expected as part of the value, not an optional add-on.

“For us, that cost of ownership goes well beyond the subscription fee. We look at implementing your services, integrations and ongoing support and the internal resources required to maintain and optimize the platform over time.”

— Chief Human Resources Officer, technology

Listen
Buyers compare only the subscription, but total cost of ownership adds implementation, services and configuration, data migration, ongoing support and staff time. A broad total-cost view: 78% in the first wave, 82% in the second. In the second wave, 48% of those who could judge a past purchase underestimated the full cost, and 74% want a dedicated support contact.
Key Finding
Why Is Human Support a Core Part of the HR Software Value Equation?

Total Cost Framing and Support Expectations

74%

strongly prefer or consider essential a dedicated contact who knows their account

Key Takeaways
01
02
Strategic Implication
How much a dedicated contact matters
44%
Dedicated contact strongly preferred
Dedicated contact strongly preferred
44%
Dedicated, continuous support is essential
31%
Responsive general support is acceptable
11%
Speed and quality matter more than one named contact
8%
Useful, especially during implementation
7%
Listen

“What matters most is continued HR support. And payroll support, dedicated specialists that know my account, know the nature of our business, know the history of any issues or things that may come up.”

People Operations Director
when asked about what matters most after go-live
Listen

“For me, total cost of ownership goes well beyond the software subscription. The license fee is important. But it's often only one component of the overall investment. I would look at implementation costs, consulting, and configuration services.”

Executive Director of Financial Planning and Analysis
when asked about total cost of ownership
Alex Bradley, Chief Financial Officer, G2

“The clearest signal here is that buyers no longer equate price with value. Nearly eight in ten weigh total cost of ownership, the implementation, the services, the ongoing support, over the subscription line. On that math a fragmented stack carries a recurring tax in manual work, and consolidating onto one well-supported system is as much a finance decision as an operational one.”

Alex Bradley — Chief Financial Officer, G2
Chapter 05

Is Switching HR and Payroll Tools Feasible?

Switching HR and payroll platforms is feasible but high-stakes, with the fear centered on business disruption: the immediate impact on pay and benefits if anything goes wrong. The second wave put the cost on record: 54% of leaders who recently led an implementation met at least one hidden cost, and vendor support is what made the difference.

“The staff time it takes to switch systems, the amount of money it takes to switch systems. It can just be a big project.”

— Chief Executive Officer, healthcare technology

A bridge from fragmented systems to one system, carried by a migration plan, a dedicated team and pay continuity. In the second wave, 64% need manual work to keep systems aligned and 54% of recent implementers met hidden costs; across both waves, 19% run on a single unified system.
Key Finding
How Difficult Is It to Switch HR or Payroll Systems?

Switching Burden and Transition Risk

54%

of recent implementers met at least one hidden cost

Key Takeaways
01
02
Strategic Implication
Hidden costs met in recent implementations
23%
Consultant, configuration, or support fees
Consultant, configuration, or support fees
23%
Integration, API, or data migration
12%
Internal labor and staff time
12%
Broader scope or ongoing maintenance
6%
No hidden costs reported
46%
Listen

“The biggest hesitation holding me back is the immense amount of work it takes to make a change, the cost to make a change, the hours to make a change, the investment of time, will we get it right? All of those concerns.”

HR and Payroll, transportation
when asked about what holds a switch back
Listen

“It was easier to do than we expected, and allowed us to automate things like payroll approval instead of having to have the bookkeeper prompt someone to approve payroll. So it was automated. It reduced errors a lot. And really streamlined our process.”

Executive Director, nonprofit
when asked about an implementation that went well
Chapter 06

Under What Conditions Do HR Buyers Trust AI and Automation?

Buyers do not reject AI and automation; they set conditions. In the second wave, 86% put reliability and predictability ahead of new AI features, and 40% name errors and payroll accuracy as their top concern. Trust in automation is inseparable from trust in the data underneath it.

“I would prefer that they draw from one unified data source because whenever you have multiple data sources, it introduces the possibility of uncertainty or error.”

— Director of People and Culture, healthcare

Listen
Gauge: in the second wave, 86% put reliability ahead of new AI features. What AI must prove: accuracy shown over time (39%), approval checkpoints with override (24%), testing on their own scenarios (20%), and one unified data source (30%). 89% raise at least one concern about AI in HR and payroll.
Key Finding
What Role Does Human Oversight Play in HR Automation Adoption?

AI and Automation Trust Boundaries

89%

raise at least one concern about AI in HR and payroll

Key Takeaways
01
02
Strategic Implication
AI concerns in HR and payroll
40%
Errors, hallucinations, and payroll accuracy
Errors, hallucinations, and payroll accuracy
40%
Bias, fairness, and explainability
20%
Data privacy and security
19%
Loss of human judgment or control
10%
Few or no AI concerns
11%
Listen

“There's a lot of things that have to be proven to me first. And I would have to have the vendor prove it to me with certainty because people don't like their paychecks being messed up.”

Human Resources Manager
when asked about trusting AI near payroll
Listen

“I want testing on our scenarios, clear audit trails, and human override before AI touches sensitive decisions. Not against it, just want the controls to mature first.”

HR Director, software
when asked about what AI must show before it touches sensitive decisions
Chapter 07

How Much Time Do Routine Workforce Decisions Take?

Time-off approvals, payroll exceptions, expense approvals, and employee changes land on managers every week. The second wave measured that load for the first time: at 62% of organizations, managers spend a few hours or more each week on these routine decisions.

Weekly manager time on routine decisions, second wave: less than an hour 30%, a few hours 37%, half a day or more 26%, varies 7%, largely automated 1%. At 62% of organizations, managers spend a few hours or more each week on routine decisions.
Key Finding
Routine Workforce Decisions Take Managers Hours Every Week

Routine Workforce Decisions and Manager Time

29%

name time-off, leave, or time-card approvals

Key Takeaways
01
02
Strategic Implication
Which routine decision creates the most friction
29%
Time-off, leave, or time-card approvals
Time-off, leave, or time-card approvals
29%
Expense approvals and reimbursements
23%
Payroll exceptions, corrections, and overtime
19%
Employee changes, scheduling, and staffing
17%
No single decision stands out
12%
Listen

“Probably 50% or more of my time is spent on all of those types of things time off approvals, payroll, expense, employee changes, It's a lot of time.”

Administration Manager, government
when asked about how much of a manager's week routine decisions take
Listen

“It's too much. Inefficient because it's not just one manager. It's multiple managers. By the time you compound it by the number of managers, you're talking days of wasted time.”

Chief Commercial Officer, professional services
when asked about what routine approvals add up to
Chapter 08

Should Routine HR and Payroll Decisions Be Automated When Policy Defines the Outcome?

Leaders who want a human on high-stakes decisions are ready to let policy decide the routine. 77% agree routine HR and payroll decisions should be automated whenever company policy clearly defines the outcome, including 57% of those holding back on automation today. Only 24% have done it.

Second wave: 77% agree policy should decide routine decisions, 24% have automated any policy, a 53-point gap. Routine requests flow into company policy, which decides the routine automatically and sends exceptions to a person.
Key Finding
77% Want Policy-Defined Decisions Automated. Only 24% Have Done It.

Automated Decisioning and Policy Boundaries

33%

would let clear policy-defined decisions run end to end

Key Takeaways
01
02
Strategic Implication
Where leaders draw the line
33%
Let clear policy-defined decisions run end to end
Let clear policy-defined decisions run end to end
33%
Keep human review for exceptions, high-impact changes, and sensitive cases
34%
Automation recommends or routes, a person approves
16%
A person involved in every routine decision
17%
Listen

“100% agree. As long as it's aligned within the guidelines that we've set as an organization, a manager should never have to touch it.”

Chief Operating Officer, financial services
when asked about automating decisions inside policy
Shane Hadlock, President and Chief Client Officer, Paycom

“HR and payroll leaders are increasingly looking for software that automates decisions for them. They want to reduce the operational burden created by disconnected systems. They want data consolidation that enables full-solution automation through decisioning logic, reducing manual work, improving accuracy and giving organizations greater confidence in their data. When information flows through a single software, teams can automate routine processes, spend less time reconciling systems and focus more on supporting employees and driving business outcomes.”

Shane Hadlock — President and Chief Client Officer, Paycom
Strategic Patterns

Cross-Cutting Themes

PATTERN 01

The Fragmentation-To-Evaluation Chain

Because many organizations operate across fragmented systems with manual reconciliation, buyers assess solutions through a broad total-cost lens that includes support and services. Operational friction does not stay contained at the workflow level; it directly shapes commercial evaluation and perceived value.

PATTERN 02

Control as the Price of Trust

Security confidence and openness to automation both depend on preserved oversight. Buyers trust current environments through internal controls and safeguards, and they extend that same logic to AI by accepting automation only when human guardrails remain in place.

PATTERN 03

Change Is Possible, but Transition Risk Raises the Bar

Although most buyers say switching is feasible, they also describe it as time- and resource-intensive. Combined with a broad total-cost mindset, this suggests that willingness to change exists, but only when the benefits clearly outweigh transition burden and ongoing support demands.

PATTERN 04

Policy Is the On-Ramp to Automation

Leaders will not hand consequential decisions to a black box, but they will let their own policies make the routine ones. Where company policy already defines the outcome, agreement to automate is broad, rises with the weekly load, and holds even among those holding back on automation today.

FAQ

Common Questions

Question 01

How Widespread Is System Fragmentation in HR and Payroll Environments?

Strategic Recommendations

What Should HR and Payroll Leaders Do Next?

01
Critical

Evaluate on Operating Burden, Not Feature Lists

You are already paying a fragmentation tax in manual work, reconciliation, and risk. Compare platforms on how much of that burden they remove, not on feature checklists. That is the problem most worth solving. Evidence: 64% of second-wave leaders need manual work to keep HR and payroll aligned; at 38% of organizations it takes a few hours or more every week.

02
Critical

Treat Consolidation as Risk Reduction, Not Convenience

A single unified system, one database for HR, payroll, time, and benefits, cuts manual work, shrinks the compliance and security surface, and removes the gaps where data goes wrong. Weigh it as a risk decision, not a feature upgrade. Evidence: 81% of 428 leaders are not on one system; in the second wave, 24% of leaders in fragmented setups feel exposed on compliance, against none on a unified system.

03
High

Automate the Decisions Your Policies Already Make

Start with routine decisions that have a clearly defined expected response, such as time-off requests and standard approvals. Set the rules yourself, let the system apply them consistently, and route the exceptions to a manager. Evidence: 77% agree policy-defined decisions should be automated; only 24% have done it; agreement reaches 91% where the weekly load is heaviest.

04
High

Demand Migration Confidence Before You Commit

Switching is feared because HR and payroll touch every employee. De-risk it directly: require a structured implementation program, a dedicated team that owns the move, and explicit continuity safeguards for pay and benefits. Evidence: 54% of recent implementers met hidden costs and 49% needed more time, staff, or budget; 66% say vendor support made the move easier.

04
High

Compare on Total Cost of Ownership, With Support Included

Do the all-in math: implementation, services, configuration, and ongoing support, not just the subscription line. Expect continuous, named support to be part of the value, not an upsell. Evidence: About eight in ten take a broad total-cost view; 74% of second-wave leaders want a dedicated contact; 55% have been slowed by generic support.

05
Moderate

Adopt AI Human-In-The-Loop First, on a Unified Foundation

Keep humans in control of high-stakes decisions and let automation prove its accuracy in lower-stakes workflows first. Then weigh the architecture: automation is only as trustworthy as the source of truth it runs on. Evidence: 86% put reliability first, 89% raise at least one concern, and 30% say one unified data source would earn more trust.

Conclusion

Two waves and 428 interviews point to the same shift in how organizations buy HR, payroll, and HCM technology: the category is moving from feature evaluation to burden evaluation. Fragmentation is the starting condition for most buyers, and that operational reality shapes everything that follows, from how they define total cost to how much transition risk they are willing to absorb. This reinforces the fragmentation-to-evaluation chain: workflow complexity does not stay in operations; it directly influences commercial judgment and perceived value. **Challenges.** The obstacle is not desire but risk. Buyers want consolidation, cleaner compliance, lower cost, and more automation. But HR and payroll touch every employee, so they will not trade a fragmented status quo for a risky transition or for automation they cannot verify. Recent implementations bring hidden costs and extra effort, and trust in AI depends on proof of accuracy and human oversight. **Looking ahead.** The second wave shows where the next step lies. Routine workforce decisions take managers a few hours or more every week at 62% of organizations, and 77% of leaders agree those decisions should be automated when policy clearly defines the outcome, yet only 24% have done it. That is automation leaders control: their own rules, applied consistently on one system, with people reviewing the exceptions. Paired with a unified source of truth, dedicated support through the move, and proof that the automation is accurate, it turns the feared switch into a practical one. **In HR and payroll, buyers do not reward innovation that adds uncertainty; they reward platforms that turn complexity into control.**

G2 Research

G2 is the world's largest and most trusted software marketplace. G2 AI Custom Research builds original studies from real buyer interviews, conducted by G2's AI interviewer and reviewed by G2's research team. This report combines two waves of The New Buying Logic for HR and Payroll, June to October 2026, 428 interviews in all.

Methodology

This research combines two waves of G2 AI Custom Research on HR and payroll buying logic, both commissioned by Paycom: 211 in-depth interviews in June 2026 and 217 in September and October 2026, 428 in all.

The first wave drew on business professionals across technology, financial services, healthcare, manufacturing, and retail, from small businesses to large enterprises, all selected for direct experience with software evaluation, implementation, integration, and operational risk management.

The second wave drew on HR, payroll, finance, IT, and executive leaders at US organizations. Participants were screened for roles with responsibility for HR, payroll, or HCM technology and for owning or significantly influencing those decisions; consultants and advisors were excluded. Interviews lasted 10 to 70 minutes, 37 minutes on average. The guide repeated the first wave's questions and added two: how much time managers spend each week on routine workforce decisions, and whether routine HR and payroll decisions should be automated whenever company policy clearly defines the outcome.

In both waves, G2's AI interviewer conducted the conversations in an open format so leaders could describe their actual systems, costs, and attitudes rather than select from preset options. Transcripts were analyzed with AI for semantic understanding, with multi-iteration validation and cross-verification, and reviewed by G2's AI Custom Research team. Each answer was assigned to one category per question. Figures are percentages of the respondents who answered each question; follow-up questions put only to a subgroup, such as leaders who recently led an implementation, are based on that subgroup. Figures are rounded and may not total exactly 100%. Quotations are verbatim and attributed by role and industry.

The two waves interviewed different people. Two figures draw on both waves because both asked the question the same way, with the same answer categories: the share on a single unified system, pooled across all 428 interviews (83 of 428, or 19%), and the broad total-cost view (164 of 211 in the first wave and 168 of 204 in the second, about eight in ten in each). All other figures come from the second wave alone.

G2 Research, October 2026

This report was originally published in June 2026, updated in August 2026, and refreshed with a second wave of research in October 2026.

This article was originally published in October 2026 and updated in October 2026.

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