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Research Report
The ROI of Employee Experience
As enterprises navigate tightening budgets and shifting priorities in 2026, recent research from Metrigy's Workplace Collaboration MetriCast study suggests that overall spending on traditional collaboration technologies is expected to remain largely flat or even decline over the next 12 months. At the same time, investments in artificial intelligence and automation technologies continue to capture executive attention, with companies experimenting with generative AI to boost individual productivity even as many struggle to achieve measurable ROI from those tools.
It raises the question: Are organizations deprioritizing team collaboration in favor of machine-mediated work, or are they changing how, where and why they invest in collaboration tools?
The AI Budget Game
The answer, according to industry observers, may be less straightforward than either explanation suggests. Budget pressure alone doesn't explain the shift, said Neal Riley, AI innovation lead at The Adaptavist Group. "Gartner is projecting that overall IT spend is actually increasing by 40% in 2026, so budgets aren't necessarily pressured," he said.
Instead, Riley argues the flattening reflects multiple factors: slowing hiring throughout 2025, saturation in the unified communications market and a gradual shift in priorities toward AI initiatives and investment in AI infrastructure. "According to Gartner, servers are up 36.9%, data centers up 31.7% and AI spending overall is up 44% to $2.52 trillion, while collaboration spending is flattening,” he said.
Jonathan LaCour, Mission CTO, is more blunt about the tradeoffs involved: Organizations are choosing where to allocate finite resources, driven by market pressure to become AI-first businesses, he said.
"While IT leadership will communicate that the importance of collaboration platforms have not decreased, the fact of the matter is that the budget has to come from somewhere," LaCour said. Collaboration tools, as high-ticket items, become convenient targets when something has to give.
But LaCour's assessment carries a darker implication. Organizations are investing in AI because they want their workforce to be more productive and efficient. However, "if organizations are able to measurably do more with less thanks to AI, that can be used as a justification to reduce headcount."
The Pandemic Hangover
On the other hand, "The spending decline reflects a strategic reset, not AI reshaping work's companies cutting bloated tool stacks that weren't driving collaboration in the first place,” said Joshua Haghani, founder and CEO of Lumion.
Haghani describes consolidating six collaboration tools into three at his own organization, with the decline resulting from eliminating overlapping licenses rather than reduced teamwork.
Many companies, Haghani suggests, quickly adopted expensive collaboration suites during the pandemic with little consideration of what they actually needed. The current correction reflects organizations matching tools with workflows rather than stockpiling general-purpose platforms.
"We risk mistaking 'more tools' for 'better teamwork,’” he said.
Where Collaboration Happens
In the social benefit and nonprofit space, collaboration is a condition for survival rather than a productivity hack. Kevin Bussema, founder of The Collaborative Collective, is skeptical about framing the issue around software spending.
"The most valuable asset class organizations will carry into the future is not technology, but human capital and the ability of people to collaborate, build trust and form coalitions of action," Bussema said. Whether collaboration software needs a strategic reset misses the point by assuming collaboration that’s primarily enabled by tools.
As energy, compute and knowledge become abundant through AI, scarcity moves elsewhere, Bussema said. "What becomes harder to find is not information or execution capacity. It's judgment. Discernment. Human agency."
Bussema describes watching this play out in product development, where early-stage collaboration that once required dense networks of human knowledge transfer is increasingly handled by machines. Teams that used to spin up channels or pull engineers into early ideation sessions now start with AI instead. Engineers still matter, he said, but they show up later.
Collaboration, in Bussema's view, moves downstream into moments where tradeoffs can't be automated: ethics, risk, quality and long-term consequences. "Tools designed for constant, dial-tone coordination may slow not because collaboration matters less, but because growth increasingly depends on fewer, deeper, more consequential forms of human interaction."
The Meeting Problem
Riley's research from The Adaptavist Group indicate how AI is being used. Findings showed that 32% of workers are speaking to colleagues less since using generative AI, while one in four knowledge workers said they'd rather engage in small talk with an AI bot. That figure rises to 32% among leaders, suggesting a possible disconnect higher up the chain.
The introduction of AI-powered meeting summaries exposes assumptions many would rather not examine. "If you can skip a meeting and catch up via AI summary, did that meeting need you in the first place?" Riley asked. Fewer meetings and attendees improve meeting quality, with people collaborating rather than passing along information.
Yet 40% of knowledge workers in Adaptavist's research considered sending AI assistants to meetings as rude. The technology may be reducing meetings, but the cultural impact should not be overlooked, Riley warned.
AI doesn't change the fundamental requirements for effective meetings: clear agendas, supporting data and analysis and the right attendees, LaCour said. AI helps generate agendas, gather and summarize relevant data and automate scheduling. But whether this improves collaboration or masks deeper problems with meeting culture remains a question.
However, Haghani takes a more optimistic view, arguing that AI isn't reducing meetings but improving their quality by pre-curating information. "This isn't where AI is replacing collaboration; it's enabling better-informed collaboration," he said.
Culture Eats Strategy for Breakfast
Riley's research identifies what he calls an AI fault line in IT leadership between realists and skeptics. The skeptic cohort expected productivity gains through cost reduction, with fewer employees taking on the same or more workloads. Realists invested in output quality and explored new coordination and operating models, reporting increased throughput and quality.
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Organizations adopting cultures of experimentation and research saw double the ROI from AI investment compared to skeptics. "A healthy culture doesn't come from an app,” Riley concluded
Spending more on tools does not necessarily predict productive workforces, Riley’s research indicated. It's the culture and enablement around how technology is introduced that drives meaningful outcomes. The choice of tool matters less than the culture of the organization using them, he said.
The same is true for hybrid work environments, LaCour said. Organizations that want to use distributed workplaces will be most successful if employees use the same tools and processes regardless of team composition. He views "remote" work as an anti-pattern that creates two classes of employees.
A Question of Value
Much of the conversation influencing these discussions relies on research locked behind prohibitively expensive paywalls. The 2025 Metrigy study, for example, costs $15,000. When knowledge itself is being democratized through AI, Bussema asks whether our conceptual frameworks are keeping pace with the transformation underway.
The question of whether collaboration spending decline represents a strategic reset or AI reshaping work may present a false choice.
The evidence suggests both are happening simultaneously, with varying degrees of intentionality and success across organizations. What remains unclear is whether enterprises are making these shifts with sufficient understanding of what they're trading away.
Editor's Note: Catch up on more collaboration topics:
- Building a New Model for Better Collaboration Experiences — Being intentional about collaboration and designing teamwork requires a new approach.
- The Daily Behaviors That Turn Good Teams Into Great Ones — The path from functional to exceptional teams isn't mysterious. Most have the talent they need. What they lack are daily behaviors that create cohesion.
- The Future of Team Collaboration According to Coda, Microsoft Loop, Notion and Slite — A look at how four generative AI-powered collaboration platforms aim to transform team productivity.