The EY 2026 Tax and Finance Operations Survey of 1,600 CFOs and senior leaders across 30 jurisdictions finds that AI ambition has dramatically outrun data infrastructure [1]. With 64% citing insufficient AI-ready data as their top barrier [1] and agentic AI expectations surging from 21% to 77% in a single year [1], the gap between aspiration and execution is widening fast. Channel ecosystem partners specializing in AI consulting, data management, and agentic solutions are positioned to capture this demand, backed by a channel market on track to reach $41.8B by 2029 [2].
What is Covered in this Article
- Data readiness as the primary AI barrier in tax and finance [1][1]
- Structural causes: data silos, poor quality, and strategy gaps [1][1]
- Agentic AI maturity gap: expectations vs. reality [1][1]
- Channel partner opportunity in AI consulting and data management [3][3]
- Co-sourcing outcomes validating the ecosystem value proposition [1]
The News: EY released its 2026 Tax and Finance Operations Survey [1], drawing on responses from 1,600 CFOs and senior finance and tax leaders across 30 jurisdictions and 22 industries [1]. The study finds that 64% of respondents cite insufficient AI-ready data as the single biggest barrier to advancing AI initiatives [1], while only 16% consider their tax function highly effective at accessing, organizing, using, and reusing data [1]. Agentic AI expectations have surged, with 77% now expecting AI agents to benefit the tax function, up from 21% a year ago [1], yet 71% remain at a completely nascent or exploratory maturity stage [1]. The survey findings make clear that ambition alone will not be enough and that leaders must address foundational data, governance, and talent capabilities to generate returns on AI investments.
EY Survey: Data Gaps Are Stalling Enterprise AI in Tax and Finance
Analyst Take: EY's survey delivers a clear verdict: the bottleneck in enterprise AI is not enthusiasm, it is data infrastructure. With only 16% of tax functions rated highly effective at managing data [1] and 43% unable to execute a sustainable data, AI, and technology strategy [1], the structural deficit is deep enough to create a durable, large-scale services opportunity for channel ecosystem partners.
Structural Data Dysfunction Is the Root Cause
The EY findings point to systemic dysfunction rather than isolated gaps. Among organizations that rate their data practices as ineffective, 61% cite data silos and 52% report poor data quality as key obstacles [1]. These are not configuration problems; they reflect legacy operating models that were never designed for AI-scale data flows. Futurum's Data Intelligence Platforms Signal Report corroborates this pattern at the enterprise level, finding that 93% of enterprises acknowledge difficulty establishing the governance necessary for production AI deployments [4]. The convergence of EY's sector-specific findings with Futurum's broader enterprise data confirms this is not a tax-function anomaly. It is a cross-functional infrastructure crisis that requires deliberate remediation before AI can deliver measurable value.
Agentic AI Expectations Have Surged Past Execution Readiness
The sharpest signal in EY's survey is the agentic AI expectation gap. Respondents expecting AI agents to benefit the tax function jumped from 21% to 77% in a single year [1], yet 71% remain at a completely nascent or exploratory maturity stage [1]. That 56-point expectation swing against near-zero maturity progress defines the near-term implementation gap. Futurum research adds structural texture to this gap: nearly a quarter of organizations (24.6%) now cite the inability of agents to write back to systems of record as a top infrastructure bottleneck [4]. Passive legacy architectures are blocking the bidirectional data flows that agentic AI requires. With 83% of survey respondents prioritizing an agentic workforce [1] and 81% emphasizing AI-skilled hiring [1], demand for implementation support will accelerate sharply into 2027.
Channel Partners Are Primed to Close the Gap
Futurum's 2H 2026 Decision Maker Survey shows channel partners have positioned themselves precisely where EY's enterprise clients need help. AI consulting is the top growth-driving service at 86.7% [3], and AI software including copilots is the top growth-driving technology category at 78.3% [3]. Data management services register at 56% as a high-conviction growth area [3], directly addressing the silos and quality failures EY identifies. Critically, 66.8% of channel partners have already developed their own AI solutions using LLMs [3], and more than half are running AI agents internally [5]. That operational experience translates into credible advisory capacity for enterprise clients work through the same agentic transition. The broader channel market supports the scale of this opportunity, with a base-case trajectory reaching $41.8B by 2029 at a 36% CAGR [2].
Co-Sourcing Results Validate the Ecosystem Value Proposition
EY's own co-sourcing data makes the channel case concrete. Among organizations already using co-sourcing, 86% report a greater ability to focus on higher-value activities, 78% report improved tax risk management, and 77% report greater success work through legislative and regulatory change [1]. These outcomes map directly to the pressures EY's respondents face: 79% are adapting operations in response to geopolitical developments [1] and nearly two-thirds are not fully prepared for real-time tax demands [1]. The channel is already bifurcating around AI execution capability, and vendors that segment partners by growth posture and fund execution over enablement will capture the enterprise relationships that matter [3]. EY's co-sourcing results position it as both a bellwether for what works and a potential orchestrator of the broader AI-ready data transformation ecosystem.
What to Watch
- Data remediation spend: whether CFOs allocate dedicated budget for AI-ready data infrastructure in Q1 2027 planning cycles [1][1]
- Agentic maturity progression: how quickly the 71% at nascent or exploratory stages advance to production deployments over the next two quarters [1]
- Channel partner segmentation: which partners earn preferred status by demonstrating production-grade agentic AI delivery for finance and tax clients [3]
- Co-sourcing expansion: whether organizations without co-sourcing arrangements adopt them in response to real-time tax compliance pressure heading into 2027 [1][1]
- Write-back architecture adoption: how fast vendors resolve the agent-to-system-of-record bottleneck that currently blocks agentic AI at scale [4]
Sources
1. AI ambition outpaces data readiness in tax and finance …, EY, November 2026
2. 2H 2025 Hyperscaler Marketplace Market Sizing & Five-Year Forecast, Futurum Research, December 2025
3. 2H 2026 Ecosystems, Channels & Marketplaces Global Enterprise Decision Maker Survey Report, Futurum Research, August 2026
4. Futurum Signal Report | Data Intelligence Platforms – August 3, 2026, Futurum Research, August 2026
5. 1H 2026 Ecosystems, Channels & Marketplaces Global Enterprise Decision Maker Survey Report, Futurum Research, March 2026
Disclosure: Futurum is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
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This content is written by a commercial general-purpose language model (LLM) along with the Futurum Intelligence Platform, and has not been curated or reviewed by editors. Due to the inherent limitations in using AI tools, please consider the probability of error. The accuracy, completeness, or timeliness of this content cannot be guaranteed. It is generated on the date indicated at the top of the page, based on the content available, and it may be automatically updated as new content becomes available. The content does not consider any other information or perform any independent analysis.

