2025 Work Intel Wrap-Up: What Insightful Revealed About Work in 2025 and What It Means for You

In 2025, AI became unavoidable. Software budgets expanded, pilots multiplied, and transformation roadmaps promised step-change gains. Yet work intel in 2025 suggests the answer to a question many executives are quietly asking: Are AI initiatives a failure?

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While most growth-oriented businesses increased AI and software spend last year, industry analysis indicates that only a fraction of initiatives reach production with measurable impact, exposing a gap between ideation and execution. This gap is colliding with a broader market reset that is continuing into 2026.

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Private equity firms are holding “dry powder” near all-time highs, amid a historic exit backlog, which is accelerating a shift from “buy and grow” strategies toward a tried-and-true PE strategy: audit, consolidate, and optimize. Simultaneously, non–AI-native software investment is receding, even as AI enthusiasm continues to dominate technology narratives.

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The constraint for enterprises remains in the lack of visibility into how work actually happens, also known as work intelligence. Enterprise work occurs across informal and unmanaged workflows, beyond the reach of traditional measurement. An Asana report suggests 90% of workers rely on informal networks, peers, and unspoken understandings to complete tasks. Those findings match closely with Insightful’s own data, which indicates that as much as 97% of revenue-generating or margin-protecting corporate workflows are unmapped. Adding AI onto this foundation often stalls because leaders lack a line of sight into the steps workers take to achieve their desired outcomes.

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Insightful’s work intelligence platform serves as an audit layer for this reality, illuminating the workflows where AI adoption and restructuring efforts succeed or quietly break down. In a year defined by hype, 2025 work intelligence data points to a more durable priority: scaled execution integrity. 

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The 2026 Shift From Hype to EBITDA

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2025 was defined by bold AI mandates: implement AI tools yesterday and sprint to unlock savings. 2026 AI themes are better defined: use AI productively and keep fiscal margin discipline.

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Companies are rapidly moving from the excitement of announcing initiatives to ensuring AI investments generate measurable financial impact. Insightful’s own data reflects this transition: buyers are increasingly prioritizing solutions with clear ROI over novelty.

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Metrics like net retention and account growth signal more discerning buyer behavior. For Insightful’s clients, the implication is straightforward: 2026 favors companies that combine AI innovation with operational rigor, turning experimentation into profitable, repeatable results. Vendors who fail to connect AI initiatives to concrete margins risk losing relevance in a market steadily shifting from excitement to measurable performance.

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The AI Adoption Mirage: Where Spend Evaporates

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The 2025 AI directive for enterprise boards: More AI spend equates to work efficiency and productivity. Larger AI and software budgets were approved, leadership narratives touted transformation, and enterprise tool stacks swelled with generative AI pilots and integrations.

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Insightful’s own data shows that AI tool use increased by 3X in 2025 compared to the prior year. This reflected a broad-based increase in the commercial use of LLM platforms such as ChatGPT, Gemini and Claude. However, evidence suggests that not all of this AI use is company approved, with many users continuing to use personal chatbot accounts during work hours as well. In fact, ChatGPT ranks only 84th in enterprise tool usage in 2025.

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Many decision‑makers equated an AI purchase in 2025 with value, expecting these technologies to move quickly from experimentation to everyday use. The reality didn’t match expectations: an MIT report found that despite $30-40 billion in GenAI enterprise investment, 95% of organizations are getting zero return.

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The hard fact is that AI may be adopted, but integration into workers’ actual daily tasks remains sluggish, with only 14% of workers reporting daily AI usage in workflows, according to PwC. This gap—dubbed the AI shelfware crisis—is on the rise.

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Traditional activity monitoring and surface‑level usage metrics aren’t enough to close this execution gap. Standard analytics often capture installations and log‑ins, but they fail to show whether AI tools are meaningfully integrated into core processes or driving real business outcomes. Work intelligence data measuring where time is spent, how workflows move, and where bottlenecks persist reveals a far more nuanced picture of real AI adoption: most enterprise work occurs in unmanaged spaces that remain invisible to conventional tracking. This makes it nearly impossible to track the value created by AI investments.

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Bringing awareness to a deeper level of work behavior can allow leaders to bridge the widening gap between spend and impact.

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Managing a Black Box: 97% of Workflows are Unmapped 

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Enterprise leaders often assume they understand how work gets done because core systems capture outputs and milestones. Insightful’s internal work intelligence data tells a different story: approximately 97% of enterprise work occurs through non-defined, unmanaged processes, leaving leaders with direct visibility into only a small fraction of day-to-day execution. This finding aligns with broader industry research showing extensive tool sprawl, fragmented workflows, and significant time spent coordinating work outside formal systems. The result is a persistent “black box” where most productivity, inefficiency, and risk actually reside.

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This visibility gap becomes a critical constraint when organizations attempt to deploy AI, scale output, or restructure teams. Automation struggles to blossom when workflows are informal, variable, and poorly measured. Insightful’s workflow optimization capabilities address this challenge by transforming real execution into measurable intelligence—capturing time-on-task, workflow variation, and bottlenecks across complex roles.

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In industries such as insurance, where underwriters and claims adjusters must balance accuracy, compliance, and speed amid growing backlogs, this visibility enables teams to optimize output responsibly and identify where AI can realistically deliver impact. By illuminating the unmanaged majority of work, Insightful provides the foundation required for security assurance, effective AI adoption, operational optimization, and durable productivity gains.

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Emerging Market Trends in Software and Private Equity

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After a decade of sustained expansion, software growth outside AI-native categories is steadily declining. Simultaneously, AI enthusiasm continues to dominate technology narratives. The AI fervor masks the reality that traditional SaaS businesses are now growing at more modest, operationally constrained rates. This divergence has sharpened the focus away from investment aimed at growth towards durable margin improvement.

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These dynamics are unfolding against a difficult exit environment for private equity. Extended holding periods, a backlog of unsold portfolio companies, and large amounts of sidelined capital have accelerated the rise of secondary sales, continuation vehicles, and sponsor-to-sponsor transactions. In response, PE firms are shifting away from a pure “buy and grow” model toward audit, consolidation, and optimization strategies that emphasize operational discipline.

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Value creation is increasingly tied to the ability to identify inefficiencies, eliminate overlapping operations, and enforce consistent execution across platforms. In this hyper-focused environment, PE operating partners need enterprise-wide work intelligence, showing how work is performed across teams, tools, and portfolio companies.

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Verifying execution integrity during integrations, restructurings, or EBITDA optimization efforts requires evidence that productivity gains are real and repeatable. Work intelligence enables investors and operators to move from anecdotal performance claims to measurable, defensible execution outcomes across their portfolio.

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The RTO Visibility Paradox: High-Speed Side Hustles

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Return-to-office mandates regained momentum in 2025, often justified as a corrective to perceived productivity losses in distributed teams. The assumption was straightforward: physical presence would restore focus, collaboration, and accountability. Yet work intelligence and location data reveal a more complicated reality.

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First, despite the increase in RTO mandates, some companies appear to be embracing location-freedom permanently. In a March 2025 survey, 57% of Manhattan office workers are at their workplace on an average weekday, which is 24% less than the pre-pandemic rate.

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What location and productivity data consistently show is that outcomes vary sharply by role, work context, and task type. Deep, individual work and highly collaborative functions respond differently to office presence, and blanket RTO policies often obscure these nuances.

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Insightful’s work intel data in 2025 surfaced these dynamics, backed up by stories of successful remote work rollouts such as Peach Payments, where outcomes depended less on where work happened and more on how it was structured and measured.

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This variability is why a more sophisticated hybrid approach is emerging—one grounded in work intelligence data rather than attendance mandates. If you’re curious to learn more, Insightful’s Hybrid Work Playbook provides a blueprint for organizations seeking to design RTO strategies that align location, workflow, and productivity, replacing assumptions with measurable outcomes, security priorities, and restoring visibility where it actually matters.

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How to Hyperscale in 2026: A Work Intel Blueprint

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The next phase of enterprise scaling is not about speed alone, but rather verifiable outcomes at scale. As organizations expand large, distributed, and often contracted workforces, traditional management signals will continue to break down in 2026. Output metrics are lagging indicators of success, but companies need real-time telemetry to know if process adherence becomes inconsistent or if strategic plans are failing to be adopted at the individual contributor level. This is where leading hyperscalers are installing an audit layer for work itself.

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Mercor provides a clear example. As the company scaled to support over 30,000 active users, leadership faced a familiar challenge: validating work quality while managing a massive workforce. In 2025, Insightful became the system of record for this transition, enabling Mercor to observe time-on-task, workflow adoption, and execution consistency across a highly dynamic, contracted workforce. The result was better integrity in execution from Mercor’s contractor workforce, leading to higher contract values and more satisfied clients.

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This model gained traction in 2025 because it solves a structural problem across modern enterprises. 2026 will be a year that rewards companies that are proactively using work intelligence data to verify and automate processes at scale, like Mercor does.

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Whether scaling AI-augmented teams, global operations, or flexible labor pools, companies need proof that work aligns with intent. Insightful functions as that proof layer, allowing leaders to move fast without losing control, and to scale without sacrificing accountability.

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Final Thoughts

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Work intel from 2025 points to a clear inflection point. AI investments are failing, software portfolios are being re-evaluated, and private equity and enterprise leaders are simultaneously under pressure to defend margins with proof rather than hyped-up narratives.

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Work intelligence has emerged as the missing foundation. By making the invisible visible—across tools, locations, roles, and workflows—Insightful enables organizations to move from activity to outcomes, from spend to impact, and from strategy to execution.

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