All AI News

KPMG Thought Leadership

capital advisory

KPMG's Infrastructure, Capital Projects and Climate Advisory practice positions the firm as an end-to-end advisor for asset-intensive organizations navigating the full capital project lifecycle, from strategy and financing through delivery and operations. The central thesis is that responsible renewal of America's physical infrastructure drives economic growth, improves quality of life, and advances sustainability goals. KPMG serves four primary sectors—energy and utilities, transportation, digital infrastructure, and social/commercial real estate—covering assets ranging from power grids and renewables to data centers, ports, and affordable housing. The practice differentiates on AI-enabled delivery, having ranked first for quality AI advice and implementation among US consulting firms per the 2024 Source Global Research study. Services span six integrated offerings including major projects advisory, project procurement and financing, infrastructure funding, and site selection, all backed by a global professional network with deep subsector expertise.

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KPMG Thought Leadership

Customer and Operations

KPMG's Customer and Operations practice positions itself as an integrated consulting capability connecting customer experience strategy with operational execution across the full enterprise value chain. The practice focuses on helping organizations close the gap between customer-facing growth ambitions and back-office operational performance, treating the two as inseparable levers of competitive advantage. Service offerings span customer experience transformation, contact center modernization, supply chain optimization, and intelligent automation, with AI and data analytics embedded across each domain. The practice targets industries where operational complexity directly erodes customer satisfaction and margin, including financial services, healthcare, retail, and industrial manufacturing. KPMG frames its differentiation around combining technology implementation skills with industry-specific process knowledge, reducing time-to-value on transformation programs. The underlying argument is that firms treating customer strategy and operational redesign as separate workstreams leave measurable value unrealized.

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KPMG Thought Leadership

Global Business Services and Outsourcing Advisory

KPMG's Global Business Services (GBS) and Outsourcing Advisory practice positions GBS as a strategic lever for enterprise transformation, moving beyond cost reduction toward value creation, agility, and digital capability. The practice advises organizations on designing, building, and optimizing GBS models—including shared services, outsourcing, and hybrid structures—to drive operational efficiency across finance, HR, IT, and supply chain functions. KPMG integrates AI, automation, and analytics into GBS operating models to accelerate performance and reduce manual process dependency. The firm offers end-to-end support spanning strategy through execution, including location selection, governance design, vendor management, and continuous improvement. For outsourcing decisions, KPMG provides sourcing strategy, contract optimization, and transition management to help clients extract maximum value from third-party relationships. The underlying premise is that well-structured GBS organizations, enabled by technology, serve as platforms for sustained business resilience and competitive differentiation.

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KPMG Thought Leadership

Harness the power of data to modernize operations

Organizations that treat data, analytics, and AI as strategic assets rather than back-office functions gain measurable competitive advantage in cost, speed, and decision quality. KPMG positions its Data & Analytics practice around end-to-end modernization: helping clients move from fragmented data infrastructure to integrated, AI-ready platforms that support real-time operational insight. The approach spans data strategy, cloud migration, advanced analytics, and AI implementation, with emphasis on embedding trusted data governance throughout. KPMG argues that most enterprises underperform because they lack the architecture and talent to convert raw data into business value at scale, not because they lack data itself. The firm's advisory model combines technology alliances, proprietary accelerators, and sector-specific expertise to compress time-to-value for transformation programs. The central message is that data modernization is a prerequisite for AI adoption that delivers returns, not a parallel workstream.

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KPMG Thought Leadership

Human Capital Advisory

KPMG's Human Capital Advisory practice positions workforce strategy as a core driver of business performance, arguing that organizations must align their people, culture, and operating models to compete effectively amid accelerating disruption from AI, automation, and shifting labor dynamics. The practice offers integrated services spanning workforce transformation, HR function redesign, talent strategy, change management, and total rewards optimization. KPMG emphasizes that technology adoption alone is insufficient without corresponding investment in workforce readiness and organizational design. The firm targets C-suite leaders seeking to translate business strategy into measurable human capital outcomes, connecting HR decisions directly to enterprise value. Engagements are structured around four primary levers: workforce planning, talent acquisition and retention, leadership and culture, and HR technology enablement.

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KPMG Thought Leadership

KPMG Managed Services

KPMG Managed Services positions the firm as a long-term operational partner that takes on the execution of complex business functions—not merely advising on them. The offering combines KPMG's domain expertise, proprietary technology, and third-party platforms to run processes across finance, risk, compliance, tax, and other functions on an ongoing basis. The model is designed to deliver cost reduction, scalability, and access to specialized talent that organizations struggle to maintain internally. KPMG differentiates the offering by embedding its regulatory and industry knowledge directly into service delivery, rather than providing a purely technology-driven outsourcing solution. The target market includes organizations facing talent shortages, rising compliance complexity, and pressure to convert fixed operational costs to variable structures.

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KPMG Thought Leadership

Supply Chain Operations Consulting: Build a Resilient, AI-Enabled Supply Chain

KPMG positions AI-enabled supply chain transformation as the critical response to escalating disruption from geopolitical volatility, climate events, and demand uncertainty. The firm's supply chain operations practice integrates AI, advanced analytics, and digital technologies across planning, procurement, manufacturing, logistics, and fulfillment to build both efficiency and resilience simultaneously. KPMG argues that organizations can no longer treat these as competing priorities, and that connected, data-driven supply chains deliver measurable cost reduction alongside improved agility. The practice spans end-to-end capability building, from network design and inventory optimization to supplier risk management and control tower visibility. KPMG combines industry-specific expertise with technology alliance partnerships to accelerate implementation and drive outcomes at scale.

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A&M Insights

A&M Crypto Advisory

Alvarez & Marsal's Crypto Advisory practice offers end-to-end institutional digital-asset services spanning stablecoin adoption, tokenization of real-world assets, custody infrastructure, compliance, tax, accounting, and on-chain investigations. The practice targets traditional corporates, financial institutions, and crypto-native businesses seeking to operate digital-asset programs with institutional-grade controls and reporting. Key offerings include corporate treasury vehicle (DATCO) setup for Bitcoin, Ethereum, and Solana reserves; IPO readiness for crypto-native firms; M&A due diligence; and custom on-chain dashboards that translate blockchain data into board- and regulator-ready analytics. A&M also advises governments, central banks, and regulators on stablecoin frameworks, custody licensing, and DeFi oversight.

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A&M Insights

How To "Share" Responsibility in Setting Up Your Own Shared Services Center

Organizations scaling back- and middle-office operations face a structural choice between outsourcing and building a captive shared services center (SSC). A captive SSC concentrates accountability questions around leadership alignment and internal client relationships, making governance design a critical early decision. Success depends on clearly defining ownership, rules of engagement, and how the SSC interacts with business units — particularly in large organizations where headcount impact is significant. The article outlines frameworks for establishing accountability structures that prevent the common failure modes of captive SSC buildouts.

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KPMG Thought Leadership

business transformation

88% of companies are simultaneously managing multiple transformation programs, yet most struggle to convert data and change initiatives into measurable business value. KPMG's central argument is that AI and GenAI close this gap by detecting patterns, predicting outcomes, and generating actionable insights at speed and scale — making disruption a competitive advantage rather than a threat. The firm positions transformation not as incremental change but as a fundamental shift in how organizations operate, structured around five elements: Evolve, Grow, Operate, Innovate, and Trust. KPMG deploys a modular entry-point model under its Velocity framework, allowing organizations to scale AI-enabled solutions across functions and geographies with minimal disruption. The firm was ranked number one for overall consulting quality in the US by Source in 2025 and recognized as a worldwide leader in enterprise governance, risk, and compliance by IDC MarketScape, underscoring its claim to execution credibility across the full transformation lifecycle.

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KPMG Thought Leadership

Infrastructure, Capital Projects and Climate Advisory

KPMG's Infrastructure, Capital Projects and Climate Advisory practice positions the firm as an end-to-end advisor for owners, investors, and developers navigating large-scale capital deployment across infrastructure and energy transition assets. The practice integrates project development, financing structuring, delivery oversight, and climate risk advisory into a unified service model, reflecting the convergence of traditional infrastructure investment with decarbonization mandates. KPMG emphasizes that capital projects face mounting complexity from supply chain volatility, regulatory shifts, and ESG requirements, demanding integrated advisory support across the full asset lifecycle. The firm targets sectors including transportation, energy, water, digital infrastructure, and social assets, leveraging federal funding mechanisms such as the Infrastructure Investment and Jobs Act and Inflation Reduction Act to accelerate client investment. KPMG's value proposition centers on reducing cost overruns, schedule slippage, and stranded asset risk by embedding financial, technical, and sustainability expertise at each project stage.

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PwC Insights

Responsible AI in Finance

PwC identifies three priority actions for finance leaders deploying AI: establishing data integrity, validating AI outputs through human-led review, and embedding governance into financial reporting controls. The piece targets CFOs, CAOs, and controllers at public companies, where AI use in forecasting, impairment assessments, and revenue recognition directly implicates ICFR frameworks and auditor engagement. One-third of CEOs report GenAI has already increased revenue and profitability, creating pressure to scale adoption while managing compliance risk. Practical guidance centers on data lineage systems, tailored review protocols calibrated to use-case risk, and iterative refinement of AI models—illustrated through an ASC 606 revenue recognition case where AI initially misclassified performance obligations before human oversight corrected the error.

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OpenAI News (firm Scan)

ChatGPT for Your Most Ambitious Work

OpenAI has launched ChatGPT Work, an agentic capability powered by GPT-5.6 that executes multi-step enterprise workflows across connected apps including Slack, Microsoft Teams, Google Drive, SharePoint, CRMs, and Microsoft 365. The product moves beyond Q&A to producing finished outputs—spreadsheets, slides, documents, and interactive web apps—and can run autonomously for hours via Scheduled Tasks even when users are offline. Internal OpenAI data shows finance teams reduced month-end close and forecasting from days to hours, while sales teams compressed proof-of-concept development from weeks to 24 hours. ChatGPT Work is available today on Pro, Enterprise, and Edu plans, with Plus and Business rollout within days; enterprise admins retain governance controls over data access, tool connections, agent permissions, and audit visibility via the Compliance API.

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BCG Publications

Sustainability Reporting in Europe: From Compliance to Strategy

BCG analysis of FY2024–FY2025 CSRD disclosures finds most European companies have adopted a compliance-driven reporting posture, producing lengthy disclosures disconnected from strategic priorities, with recurring annual costs for large organizations exceeding €1 million. The forthcoming ESRS Set 2 standards, applicable from FY2026, reduce mandatory data points by approximately 60–70% and shift the regulatory emphasis from completeness to decision usefulness, creating a structural reset opportunity. BCG argues companies should use FY2026 to transition from compliance-driven to strategy-led sustainability reporting by realigning materiality assessments with business strategy, redesigning end-to-end reporting processes, and deploying AI and governance capabilities at scale. Despite widespread vendor claims, actual AI deployment in sustainability reporting remains limited due to misaligned use cases, fragmented data landscapes, and inadequate organizational readiness—gaps that must be addressed to realize efficiency gains.

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KPMG Thought Leadership

maximize value through transactions

KPMG positions its M&A advisory practice around a deal architect model designed to reduce value leakage and accelerate value creation from pre-deal through post-deal phases. Dealmakers face mounting complexity from tariff uncertainties, political volatility, and increasingly strategic deal objectives such as AI capability acquisition and operating model transformation. KPMG's response is a tech-enabled, AI-driven approach that delivers faster insights across the full deal cycle, including strategy, due diligence, integration, and separation. A single point of accountability synthesizes functional and industry expertise to keep teams aligned on the investment thesis throughout. The firm was recognized by Forbes as one of America's Best Management Consulting Firms in 2025, reinforcing its standing as a credible M&A partner across sectors including financial services, healthcare, technology, and industrial manufacturing.

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KPMG Thought LeadershipJuly 1

KPMG reframes enterprise AI value as an architecture problem, not a model problem: a 10-layer full-stack (nine layers plus a Trust, Ops & Control wrapper) with a central Work Layer where agents turn intent into governed action — skip a layer and you gain a liability, not leverage.

**The thesis:** swapping one LLM for another or bolting an assistant onto an app raises usage and token spend while value stays elusive — models and interfaces are fragments of a larger whole. When work becomes computational, *architecture* becomes the operating system of the business. **The stack (9 layers + a wrapper):** Applications · Agents · Assistants · Context · Models · Refinery · Data · Compute · Energy — all inside a **Trust, Ops & Control** boundary. **Context + Agents** form the central **Work Layer**, where intent is translated into governed action by agents operating with shared context. **Why it matters:** value compounds only when every layer works as a system; skip one and you gain a liability. Token economics is a design constraint (not an operational afterthought), governance is the boundary (not a bolt-on), and energy is an architectural input (not a facilities issue). Start from a measurable outcome and trace it through the stack to find weak layers before committing budget. Cites the KPMG Q1 2026 AI Pulse Survey — 73% automating cross-function workflows, 53% routing critical information between teams.

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A&M Insights

Private Equity Services

Alvarez & Marsal's Private Equity Services practice covers the full investment lifecycle—pre-acquisition due diligence, post-acquisition value creation, and exit preparation—integrating operational, financial, tax, IT, and commercial capabilities. The firm combines Big Four-quality accounting and tax expertise with hands-on operational consulting, serving PE firms across sectors including healthcare, financial services, energy, and software/technology. Post-acquisition offerings include CFO services, cost optimization, merger integration, carve-out support, IPO readiness, and interim management. A&M has also launched a dedicated Generative AI group within its PE practice, developing AI-enabled tools and solutions specifically for private equity firms.

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KPMG Thought Leadership

Achieve transformation and make the difference

KPMG's business transformation practice positions the firm as an end-to-end partner for organizations seeking to redesign operations, technology, and strategy simultaneously rather than sequentially. The core argument is that sustainable transformation requires integrating people, process, and technology changes together, as piecemeal approaches consistently underdeliver on value. KPMG draws on cross-industry experience and proprietary frameworks to help clients move from strategy through execution, reducing the gap between transformation intent and realized outcomes. The practice spans functional areas including finance, supply chain, customer experience, and enterprise technology, with AI and digital enablement embedded across all workstreams. KPMG emphasizes that transformation must be tied to measurable business outcomes, not activity milestones, to generate competitive advantage that endures beyond the initial program.

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KPMG Thought Leadership

Global Business Services and Outsourcing Advisory | KPMG

KPMG's Global Business Services (GBS) and Outsourcing Advisory practice helps organizations design, transform, and optimize shared services and outsourcing models to reduce costs, improve performance, and scale operations. The practice covers the full lifecycle, from strategy and business case development through vendor selection, contracting, transition management, and ongoing governance. KPMG advises across key functional towers including finance, HR, IT, procurement, and supply chain, applying both captive and third-party delivery models. The approach integrates automation, AI, and digital enablers to modernize service delivery and extract greater value beyond traditional labor arbitrage. Clients benefit from KPMG's combination of operational, commercial, and technology expertise to navigate increasingly complex sourcing decisions and multi-vendor environments.

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KPMG Thought Leadership

Procurement Advisory Services | AI-Enabled Procurement & CLM | KPMG

KPMG's procurement advisory practice positions AI-enabled transformation as the primary lever for converting procurement from a cost center into a strategic value driver. The firm offers end-to-end services spanning strategy, sourcing, contract lifecycle management, and technology implementation, with AI embedded across each phase to automate manual processes and surface actionable insights. KPMG combines its advisory capability with alliances across major procurement platforms to accelerate deployment and reduce implementation risk. The practice targets measurable outcomes including cost reduction, supplier risk mitigation, and improved contract compliance. Organizations that treat procurement as a strategic function rather than a transactional one are presented as better positioned to manage supply chain disruption and capture sustainable savings.

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KPMG Thought Leadership

Supply Chain Operations Consulting & AI-Enabled Supply Chain | KPMG

KPMG positions AI-enabled supply chain transformation as the critical lever for building resilience against persistent disruptions including geopolitical shifts, tariff volatility, and demand uncertainty. The firm's supply chain consulting practice spans strategy through execution, covering network design, procurement, inventory optimization, logistics, and S&OP/IBP. KPMG integrates proprietary and third-party AI tools to drive measurable outcomes, targeting improvements in forecast accuracy, inventory reduction, and cost-to-serve. The practice serves clients across industries with sector-specific solutions, combining functional expertise with technology implementation capabilities across platforms such as SAP, Oracle, and Blue Yonder. KPMG frames supply chain not merely as an operational function but as a source of competitive advantage requiring continuous investment in data, analytics, and organizational capability.

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BCG PublicationsJune 16

From Hindsight to Foresight: The CEO Mandate for an AI-First Chief Financial Officer

BCG argues that CEOs must redefine the CFO role around AI-first operating principles, shifting the function from backward-looking reporting to forward-looking, predictive decision support. The thesis is that finance organizations still structured around historical data and manual processes are leaving material value on the table, while AI-enabled CFOs can compress planning cycles, automate routine accounting tasks, and redirect talent toward strategic capital allocation and scenario modeling. The piece outlines a mandate for CFOs to lead AI adoption across FP&A, treasury, and financial close—not merely adopt tools incrementally—and positions this transformation as a CEO-level governance priority, not a finance-IT initiative. BCG contends that companies whose CFOs operate with AI-native workflows will achieve faster, more accurate forecasting and stronger return on AI investment than peers who treat finance automation as a back-office efficiency play.

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IBM ThinkJune 12

LLMs corrupt the documents they work on. Does agentic AI make it worse?

Microsoft research found that LLMs progressively degrade document content the more they interact with it—a phenomenon the study calls 'document corruption.' The research quantified how repeated LLM passes introduce factual drift, omissions, and hallucinated additions, with degradation compounding across iterations. Agentic AI architectures, which route documents through multiple sequential LLM calls across orchestrated workflows, amplify this risk by multiplying the number of model-document interactions. The findings carry direct implications for enterprise deployments using AI agents for document-intensive processes such as financial reporting, contract management, and compliance workflows, where content fidelity is non-negotiable.

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A&M InsightsJune 8

Global Valuation Services

Alvarez & Marsal's Global Valuation Services practice offers independent valuation, financial modeling, and advisory across private credit, structured securities, M&A transactions, disputes, and regulatory compliance. The practice covers asset-backed finance, equity compensation valuation, divorce financial analysis, and government funding strategy, positioning A&M as a broad-spectrum valuation partner. Recent thought leadership spans German and European bank equity valuations—where rate cuts and compressed cost of capital are pushing price-to-book multiples to record levels—and a Spanish energy M&A market that saw a 30% decline in deal volume in 2025 due to grid constraints and price cannibalization in solar. A CFO-focused checklist highlights that over 70% of ERP initiatives miss original goals, urging private equity finance leaders to scrutinize vendors on integration, security, and total cost beyond the demo.

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BCG PublicationsJune 8

Future of Finance 2026: Time to Shift Gears?

BCG's 2026 Future of Finance report finds that finance functions have reached an inflection point where incremental efficiency gains are no longer sufficient—CFOs must now reorient the function toward value creation and strategic decision support. Despite years of digital investment, most finance organizations remain anchored to transactional work, with AI adoption delivering isolated productivity wins rather than structural transformation. The report argues that leading finance functions are shifting from cost-center to insight engine, deploying AI agents across planning, forecasting, and reporting to compress cycle times and redeploy headcount toward higher-value analysis. BCG identifies three priority shifts: accelerating agentic AI deployment in core finance processes, redesigning the operating model around outcomes rather than tasks, and elevating the CFO's role as a strategic partner to the business. Organizations that delay this transition risk a widening capability gap as early movers compound productivity and analytical advantages.

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BCG PublicationsJune 4

Vibe Coding Is Coming to Finance. CFOs Need Guardrails

BCG argues that 'vibe coding'—AI-assisted, natural-language-driven software development—is reaching finance functions, enabling non-technical finance staff to build scripts, models, and automations without formal engineering oversight. While this democratizes development and can accelerate FP&A, reporting, and analysis workflows, it introduces material risks: ungoverned code touching financial data, controls gaps, and potential SOX compliance exposure. BCG contends CFOs must act now to establish guardrails covering code review, data access permissions, audit trails, and acceptable-use policies before ad-hoc AI-generated tools proliferate across the finance organization. The piece frames this as a governance and operating-model challenge requiring coordination across finance, IT, and audit leadership.

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PwC InsightsJune 4

Dynamic controls testing with AI

PwC's dynamic controls testing framework applies AI to transform internal controls from periodic, sample-based reviews into continuous, comprehensive testing processes. Rather than testing a fraction of transactions on a scheduled cycle, AI-enabled dynamic controls testing analyzes full populations of transactions in near real-time, surfacing exceptions and control failures as they occur. This shift materially reduces the lag between a control breakdown and its detection, lowering financial misstatement risk and strengthening SOX compliance posture. The approach also enables internal audit and accounting teams to redirect manual testing effort toward higher-judgment activities, improving operating leverage across the controls function.

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EY Insights

EU Taxonomy Barometer 2025: Key Insights and Next Steps

EY's EU Taxonomy Barometer 2025 examines how evolving EU Taxonomy regulations are reshaping sustainability reporting obligations for large companies operating in or exposed to European markets. The framework classifies economic activities by environmental sustainability criteria, requiring companies to disclose the proportion of revenue, capital expenditure, and operating expenditure aligned with EU-defined thresholds. Compliance demands significant data infrastructure investment and cross-functional coordination across finance, accounting, and reporting teams. As the regulatory perimeter expands and assurance requirements tighten, companies face mounting pressure to operationalize taxonomy alignment at scale and demonstrate audit-ready disclosures.

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OpenAI News (firm Scan)

Building Self-Improving Tax Agents With Codex

OpenAI and Thrive Holdings co-developed Tax AI for Crete's network of 30+ accounting firms, processing 7,000 tax returns this season with a self-improving architecture powered by OpenAI's Codex. The system automates preparation of 1040 and 1041 returns, saving practitioners roughly one-third of their time, increasing throughput by approximately 50%, and achieving up to 97% draft accuracy. The core innovation is a three-part improvement loop: structured capture of practitioner corrections, production traces that map failures from source documents to filed output, and a Codex-driven eval pipeline that autonomously investigates root causes, proposes fixes, and validates changes against targeted and regression evals. At launch, only 25% of returns reached 75% correct field completion; within six weeks that figure rose to 86%, with continued gains as the system expanded into more complex filings such as K-1s, rental schedules, and multi-source reconciliations.

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Anthropic News (firm Scan)

Introducing Claude for Small Business

Anthropic launched Claude for Small Business, a product targeting the 44% of U.S. GDP and nearly half the private-sector workforce represented by small businesses. The offering integrates with QuickBooks, PayPal, HubSpot, Canva, DocuSign, Google Workspace, and Microsoft 365 via toggle installation inside Claude Cowork, delivering 15 pre-built agentic workflows and 15 task-level skills across finance, operations, sales, marketing, HR, and customer service. Key workflows include payroll planning, month-end close, cash-flow dashboards, invoice chasing, and campaign execution—all requiring user approval before any action is taken. The launch includes a free AI Fluency for Small Business course in partnership with PayPal and a 10-city hands-on workshop tour beginning May 14 in Chicago.

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Anthropic News (firm Scan)

Agents for Financial Services

Anthropic has released ten ready-to-run agent templates targeting high-volume financial services workflows, including pitchbook construction, KYC screening, general ledger reconciliation, month-end close, and statement auditing. The templates deploy as plugins in Claude Cowork or Claude Code, or as autonomous Claude Managed Agents with audit logs, credentialed data access, and long-running session support. Claude now integrates directly with Microsoft Excel, PowerPoint, Word, and Outlook via add-ins, with context persisting across applications so work initiated in a financial model can flow into a presentation without manual re-entry. Eight new data connectors—including Dun & Bradstreet, SS&C Intralinks, Verisk, and a Moody's MCP app covering 600 million entities—expand the governed data ecosystem, and Claude Opus 4.7 leads Vals AI's Finance Agent benchmark at 64.37%.

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Anthropic News (firm Scan)

PwC Expanded Partnership

Anthropic and PwC have expanded their strategic alliance, with PwC deploying Claude across its global workforce of hundreds of thousands of professionals to build agentic technology, execute deals, and reinvent enterprise functions for clients. PwC is launching a dedicated Office of the CFO business group—its first standalone unit anchored in Anthropic technology—targeting regulated industries where accuracy and auditability are critical, including banking, insurance, and healthcare. The partnership includes a joint Center of Excellence and certification of 30,000 U.S. professionals on Claude, with Claude Code and Claude Cowork rolling out firm-wide. Production deployments are already delivering measurable results: insurance underwriting cycles cut from 10 weeks to 10 days, cybersecurity incident response reduced from hours to minutes, and overall delivery time improvements of up to 70% across live client engagements. Anthropic's $100 million Claude Partner Network investment underpins this collaboration, which it describes as the deepest commitment within that program.

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EY Insights

How focusing on cash can support a value-added finance transformation

EY argues that embedding a 'cash culture' into finance transformation programs generates measurable value beyond cost reduction by making working capital and liquidity optimization central to the finance operating model. The piece positions cash visibility—spanning receivables, payables, and inventory—as a strategic lever that finance leaders can use to fund transformation investments and demonstrate near-term ROI. Finance transformation efforts that lack a cash focus risk delivering process improvements without tangible balance sheet impact, limiting the business case for continued investment. EY recommends aligning KPIs, incentives, and data infrastructure around cash metrics to sustain behavioral and structural change across the enterprise.

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EY Insights

How can the financial controller transform to shape the future with confidence?

The 2024 Global EY DNA of the Financial Controller Report, based on a survey of more than 1,200 financial controllers and senior finance leaders, finds that 86% of controllers expect their role to change significantly over the next five years, with 39% anticipating a shift from value protection and optimization toward value creation. AI adoption is already high among surveyed controllers, with 89% having adopted AI tools and 65% using generative AI on a frequent basis. The report identifies three transformation levers: converting compliance-grade financial data into strategic insights, building enterprise AI confidence by evaluating reliability and transparency of AI outputs, and integrating sustainability reporting with business performance. EY frames the controller's evolving mandate as the 'Age of And'—simultaneously maintaining traditional reporting and compliance responsibilities while acquiring forward-looking skills in data, AI, and sustainability to serve as a strategic copilot to the CFO.

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EY Insights

How corporate disclosure committees are adapting in a time of change

Corporate disclosure committees are under pressure to evolve as companies face an expanding and rapidly shifting disclosure landscape—spanning new SEC rules, ESG reporting requirements, cybersecurity incident disclosures, and AI-related risks. EY argues that many existing committee structures, charters, and processes were designed for a narrower set of obligations and now require deliberate reassessment to remain effective. Key recommended adaptations include broadening committee membership beyond finance and legal to include functional experts (e.g., cybersecurity, sustainability, HR), refreshing charters to reflect current regulatory scope, and improving information-gathering processes to surface material topics earlier in the reporting cycle. The piece frames disclosure committee modernization as a governance imperative, not an administrative update, given the legal and reputational consequences of disclosure failures in a heightened enforcement environment.

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EY Insights

How tax and finance can drive talent transformation | EY - US

Tax and finance functions face a critical talent gap as automation and AI eliminate routine compliance work, requiring leaders to fundamentally rethink workforce composition and skill requirements. Organizations must build a structured transformation roadmap that maps current roles against future-state operating models, identifying which positions will be eliminated, redefined, or newly created. The shift demands investment in three core capability areas: data and technology proficiency, strategic business partnering, and higher-order judgment skills that machines cannot replicate. Upskilling existing staff through targeted learning programs is more cost-effective than wholesale hiring, but requires honest skills gap assessments tied to specific business outcomes. Leaders who treat talent transformation as a one-time project rather than a continuous operating discipline will fall behind, as the pace of technology change outstrips traditional workforce planning cycles. Success depends on CFOs and tax leaders taking direct ownership of the agenda rather than delegating it entirely to HR.

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EY Insights

tax risk and controversy survey

The 2025 EY Tax Risk and Controversy survey of 1,934 senior tax executives finds tax controversy is rising in both volume and resolution time, yet AI adoption is accelerating rapidly on both sides of disputes. 87% of respondents believe GenAI will make tax audits and dispute resolution more efficient and accurate, and nearly 70% have already built or are integrating at least one GenAI tool focused on tax controversy management. Satisfaction tracks directly with adoption: 91% of those using AI report satisfaction with their controversy management, 9 points above the overall respondent base, and those integrating GenAI are nearly 50% more likely to report being "very satisfied" compared to non-adopters. Tax authorities are moving in parallel, with 29 of 38 OECD members deploying AI as of 2024, primarily for fraud and evasion detection, and individual jurisdictions using GenAI for real-time compliance and audit targeting. Digital services taxes have emerged as a leading future controversy concern alongside the daily volatility introduced by trade tariffs. Technology alone is insufficient—strong tax governance, skilled teams, and clear use-case strategy remain essential to convert AI capability into effective controversy management.

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EY Insights

tfo survey

The 2025 EY Tax and Finance Operations Survey of global tax and finance leaders finds that continuous, embedded transformation — not episodic change — is the defining capability separating high-performing functions from the rest. 81% of organizations plan moderate to significant business changes in the next two years, more than double the prior year's rate, driven primarily by geopolitical pressure, tariffs, and supply chain restructuring. 86% rank data, AI, and technology as a top priority, with leaders projecting AI will improve effectiveness by 30% and free up 23% of budget for reallocation to strategic work — yet most acknowledge their data foundations remain inadequate to realize that potential. Pillar Two global minimum tax compliance is the single most acute regulatory burden, cited by 81% as the top legislative change affecting their business, with 85% expecting their overall tax liability to increase as a result and only 21% describing themselves as very prepared to comply. Tax transparency obligations are also accelerating, with the share of companies voluntarily disclosing total taxes paid more than doubling to 80% from 37% two years ago. The survey's central prescription is that tax and finance functions must reframe transformation as a permanent operating discipline, building agile structures and AI-ready talent that allow them to act as real-time strategic advisors rather than reactive compliance processors.

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Deloitte InsightsMay 12

3 actions top executives and board leaders can take to help safeguard data credibility

Deloitte argues that data credibility has become a board-level strategic risk, not merely a technical concern, as AI systems amplify the downstream consequences of poor data quality. The piece outlines 3 concrete actions top executives and board directors can take to strengthen data governance frameworks: establishing clear data ownership and accountability structures, embedding data quality controls into core business processes, and building oversight mechanisms that make data provenance and lineage visible to decision-makers. As AI and automation rely increasingly on enterprise data as a primary input, organizations with weak governance face compounding risk across financial reporting, regulatory compliance, and strategic planning. The authors position data credibility as a prerequisite for trustworthy AI outputs, making governance investment directly tied to ROI on broader digital transformation programs.

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PwC InsightsMarch 30

AI predictions for tax leaders: PwC

PwC's piece for tax leaders identifies 4 action-ready AI predictions aimed at guiding tax function transformation. The article positions AI adoption in tax as moving from experimentation to operational deployment, with tax leaders expected to lead—not just react to—enterprise AI agendas. Key themes include agentic AI handling compliance and data-intensive workflows, the need for tax-specific data governance, and upskilling tax teams to work alongside AI tools. PwC frames tax leaders as strategic owners of AI decisions within the tax function, requiring deliberate investment in technology, talent, and process redesign.

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PwC InsightsMarch 18

AI for global transparency reporting | PwC

PwC's piece argues that AI is becoming central to meeting the rising demands of global transparency reporting, as regulatory requirements across jurisdictions increasingly require structured, auditable, and timely disclosure of non-financial and operational data. AI tools can accelerate data aggregation, consistency checks, and narrative generation across complex multinational reporting frameworks, reducing manual effort and error risk. The piece positions AI-enabled transparency reporting as both a compliance imperative and a trust-building mechanism with regulators, investors, and other stakeholders. Organizations that embed AI into their reporting infrastructure now will be better positioned to adapt as disclosure standards continue to expand and converge globally.

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PwC InsightsMarch 11

Invoice automation for finance operations: PwC

PwC outlines an AI-enabled invoice automation framework targeting accounts payable operations within finance functions. The approach leverages AI agents to extract, validate, and route invoice data, reducing manual processing time and exception handling overhead. Key benefits cited include improved straight-through processing rates, faster cycle times, and stronger internal controls over disbursements. The piece positions invoice automation as an entry point for broader AI-driven finance transformation, with implications for working capital management and AP team redeployment.

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EY InsightsMay 31

Three critical areas of change faced by CAOs and Controllers

CAOs and Controllers face three critical areas of change reshaping the accounting and controllership function: the accelerating adoption of AI and automation in financial reporting and close processes, evolving regulatory and accounting standard requirements demanding greater agility in policy and disclosure, and a structural shift in the talent model as routine tasks are automated and the function is expected to deliver higher-value strategic insight. EY positions these pressures as simultaneous, not sequential, requiring CAOs to modernize operating models while maintaining control integrity and audit readiness. The article emphasizes that technology transformation within the controllership must be paired with governance frameworks to manage data quality, AI-generated outputs, and internal control design. Organizations that treat these changes as isolated initiatives rather than an integrated transformation risk falling behind on both compliance and strategic finance capability.

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PwC InsightsMay 29

Generative AI

This PwC hub aggregates 30+ generative and agentic AI thought leadership pieces published between mid-2024 and mid-2025, spanning enterprise AI strategy, responsible AI governance, workforce redesign, and function-specific agent deployment. Key themes include agentic AI applications across finance, procurement, IT, HR, and marketing; a dedicated series on responsible AI covering data governance, privacy, regulatory readiness, internal audit, and model testing; and workforce restructuring away from traditional hierarchical models toward AI-augmented operating models. PwC's 2026 AI Business Predictions and a midyear 2025 update frame focused, outcome-oriented AI strategies over broad model proliferation. Finance-specific content explicitly addresses how AI agents reshape the CFO operating model and whether top-performing finance functions have reached terminal value.

3 minRead