But beneath the appearance of enhanced productivity, something isn't adding up.

A finance manager reviews an AI-generated forecast before sharing it — just to be sure. She spots an error in the underlying data and corrects the output, only to realize the same figure runs through three other reports that now need to be rebuilt from scratch.

New research from The Harris Poll, conducted globally on behalf of Workday , surveyed 6,100 professionals in HR, finance, IT and operations. Among midsize organizations — those with 500 to 3,499 employees — more than two-thirds report regularly having to redo work due to system and data issues, nine points above the rate of their large-enterprise peers.

That is the paradox many midsize organizations face: AI adoption is happening, but the promised productivity gains and business outcomes are not.

Below, discover how this problem manifests across the enterprise — and how Workday GO , an all-in-one HR, payroll and finance solution built for midsize organizations, closes the gap.

The research shows the barrier to AI value is structural — and it shows up in three distinct ways.

Hybrid Systems Create Friction

For many organizations, AI wasn’t built into the business from the ground up; it was bolted onto HR, payroll and finance systems accumulated over years of growth, acquisitions and software purchasing decisions. Nearly three-quarters of midsize organizations (75%) run AI outside their core systems — 48% with some features built in, the rest entirely separate.

Systems that aren’t designed to work together often define, store and update information differently, and AI inherits those inconsistencies when generating its outputs. This helps explain why 44% of midsize employees say AI has increased the checking, correction and oversight their work requires .

Elders — a 3,000-employee agribusiness — faced that challenge directly before consolidating on Workday. Rapid organic and acquisition-driven growth had expanded its workforce while leaving the business with disconnected systems and a disjointed employee experience.

Trust In AI Is Conditional

Employees of midsize organizations are not skeptical of AI itself: 82% say it has improved their day-to-day experience, and just 18% say a lack of trust in AI limits its value.

But they are highly aware of the data driving AI: 89% say AI boosts their confidence only when they trust the underlying data , five points higher than employees at large enterprises. That conditional trust is even more pronounced among C-suite and senior AI decision-makers, at 91%. The executives being asked to sign off on AI solutions are the ones feeling the trust problem most acutely.

Airtable is a rapidly scaling technology company with almost 1,000 employees, and its pre-Workday environment involved multiple point solutions that required ongoing manual reconciliations and data integrity checks, consuming time and making it harder to maintain confidence in people and financial data across the business.

Uncertainty Delays Decisions

When teams don’t trust the data beneath a recommendation, caution becomes the rational response. Some 61% of midsize employees put off decisions to avoid risk, eight points above large-enterprise peers.

The impact goes beyond hesitation. When systems struggle to keep up, decision quality and decision speed suffer most — each flagged by around 40% of midsize employees — followed by cross-team coordination. Among upper-midsize organizations — those with at least 1,500 employees — the gap with large enterprise peers is widest in financial forecasting (30% vs. 26% for large enterprise).

BetterUp , a workforce coaching company with nearly 3,000 employees, knew this dynamic well. As the company scaled rapidly across 10 countries, critical data was scattered across siloed tools and disconnected systems, making it difficult to get a clear picture of the global workforce. "If you don't have clean data, clean systems, clean processes, you can't do culture," says Jolen Anderson, chief people and community officer.

Employees at midsize organizations have often faced a choice between simple tools they'll outgrow and costly enterprise systems designed for much larger companies. As a result, many improvised a middle path of patched-together tools and integrations that met immediate needs but added complexity and stretched lean teams even more. Workday GO closes that gap.

Made For Midsize Organizations: Workday GO is not a scaled-down enterprise product with capabilities and costs that midsize organizations don't need; it’s the same powerful Workday solution, packaged and priced for organizations with lean teams and 500-3,500 employees.

One Platform, Fewer Integrations: HR, payroll and finance run in one place, replacing the point solutions most midsize organizations manage separately. There are fewer integrations for lean IT teams to maintain, and easier connectivity to the other systems reduces maintenance demands.

When Airtable moved off multiple siloed applications onto a unified platform, it removed the reconciliation burden and data integrity overhead, lowered system maintenance costs and reengineered workflows with new automations. “We know that Workday will scale with our business, and it gives us that competitive edge,” says Marycarl Feldman, head of HR and financial systems.

“We know that Workday will scale with our business, and it gives us that competitive edge.” Marycarl Feldman, Head Of HR & Financial Systems, Airtable

A Single Source Of Truth: With these critical systems all on one platform, accurate reporting replaces the spreadsheet chases and time-consuming reconciliation that fragmented systems produce.

After acquisition-driven growth left Elders managing 15 disparate systems, the company consolidated those into a single version of the truth with Workday, cutting time-to-hire by 50% and reducing leave leakage by 40%.

With a unified data source in place, BetterUp has scaled its operational foundation across 10 countries and is now building out Workday AI Assistant and Agent of Record integrations, targeting a 50% reduction in manual HR transactions.

Agentic AI Built Into Core Workflows: Purpose-built AI agents covering self-service, payroll and deployment are embedded directly in core workflows, automating routine, time-consuming tasks. This establishes trusted, governed AI with guardrails that respect existing access permissions — rather than the lawless agents that result when AI is bolted on as a separate layer.

Rapid Setup And Results: Rather than a sprawling, years-long implementation, Workday GO uses a predefined setup process built on best practices from thousands of launches and AI deployment tooling to deliver targeted-scope, high-quality and timely activations.

Midsize organizations trust AI more than their large-enterprise peers and are already seeing its benefits. What's been missing is a foundation capable of converting that readiness into results. Fix that, and midsize organizations stop playing catch-up. They become what the data already suggests they are: the most AI-ready cohort in the enterprise world, and the next leader of AI-led productivity — once the infrastructure matches the ambition.