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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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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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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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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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KPMG Thought Leadership

kpmg recognized as a horizon 3 market leader in the hfs horizons report agentic services 2026

HFS Research named KPMG a Horizon 3 Market Leader in its HFS Horizons Report: Agentic Services, 2026, placing the firm among the most advanced providers in the agentic AI services market. The designation recognizes KPMG as an "agentic and outcome-driven transformation partner combining AI-first platforms and trusted governance." Horizon 3 classification signifies leadership in emerging, high-complexity capabilities that define the next generation of service delivery. The recognition reflects KPMG's strategy of integrating AI-native platforms with responsible AI governance frameworks to drive enterprise transformation. This positions KPMG competitively as enterprise demand for autonomous, agent-driven business processes accelerates heading into 2026.

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KPMG Thought Leadership

kpmg recognized as a leader in the 2025 2026 idc marketscape for worldwide cybersecurity grc consulting services

IDC MarketScape named KPMG a Leader in the 2025–2026 Worldwide Cybersecurity GRC Consulting Services assessment, recognizing the firm's ability to deliver integrated governance, risk, and compliance solutions at scale. KPMG's positioning reflects its combination of deep regulatory expertise, technology-enabled GRC platforms, and a global delivery model spanning multiple industries and geographies. The firm differentiates through its ability to connect cybersecurity risk management directly to enterprise-wide governance frameworks, translating technical risk into business-relevant insights for board and C-suite audiences. IDC evaluators cited KPMG's investment in AI-driven automation and its alliances with leading technology vendors as key factors supporting clients navigating an increasingly complex regulatory landscape. The recognition positions KPMG among a select group of providers assessed on both current capabilities and future-oriented strategy across the worldwide GRC consulting market.

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KPMG Thought Leadership

kpmg recognized for its clear and differentiated vision and strong innovation roadmap in digital transformation

KPMG has been recognized in Forrester's Q3 2025 report for its clear and differentiated vision and strong innovation roadmap in digital transformation services. The report specifically cites KPMG's innovation capabilities and positive client feedback as key differentiators in the market. KPMG's positioning reflects its investment in building a distinct digital transformation offering that stands apart from competitors. The recognition underscores the firm's commitment to advancing its technology and AI-enabled services for clients globally.

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KPMG Thought LeadershipMay 13

AI Governance Principles for Boards

KPMG, co-developed with the INSEAD Corporate Governance Centre, has released a principles-based framework to guide board-level oversight of artificial intelligence. The framework comprises 5 core principles covering strategic oversight, technology and security, workforce transformation, trustworthy AI, and board accountability. Built on KPMG's Trusted AI approach, it treats trust and transparency as prerequisites for AI scaling rather than obstacles to it. The principles are designed to be sector-agnostic and applicable across jurisdictions and varying levels of AI maturity, allowing boards to adapt them alongside local regulatory requirements. The framework was informed by experienced board members globally and is intended to help directors ask sharper questions and balance opportunity against risk without overstepping into management. A companion webinar hosted by INSEAD is scheduled for 21 May 2026 to translate the principles into practice.

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KPMG Thought LeadershipMay 13

How Big Brothers Big Sisters and AI work together to improve mentor matching

KPMG partnered with Big Brothers Big Sisters of America to deploy an AI-powered mentor-matching system designed to reduce the time children spend waiting for a mentor and improve the quality of pairings. The AI model analyzes data points across volunteer and youth profiles to surface higher-compatibility matches, enabling program staff to make faster, more informed decisions rather than relying solely on manual review. The goal is to increase match rates and longevity, directly driving better outcomes for youth served by the organization's roughly 230 agencies nationwide. This engagement reflects KPMG's broader push to apply AI in the nonprofit sector to scale social impact without proportionally scaling administrative burden. The human-in-the-loop design preserves staff judgment as the final decision point, addressing fairness and accountability concerns inherent in AI-assisted decisions affecting vulnerable populations.

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KPMG Thought LeadershipMay 13

KPMG 2026 M&A Deal Market Study

Global M&A activity is positioned for a measured recovery in 2026, with deal volume and value expected to grow modestly after years of rate-driven suppression, according to KPMG's 2026 M&A Deal Market Study. Technology, energy transition, and AI-related assets are the primary sectors attracting acquirer interest, as strategic buyers prioritize capability acquisition over pure scale. Private equity faces continued pressure to deploy an estimated $2.6 trillion in dry powder, accelerating sponsor-to-sponsor transactions and carve-outs as GPs seek liquidity and portfolio exits. Valuation gaps between buyers and sellers remain the single largest deal impediment, though narrowing interest rate differentials are gradually closing that spread. Regulatory scrutiny, particularly in cross-border transactions involving data, defense, and critical infrastructure, adds material execution risk and timeline uncertainty to deals in those categories. Respondents broadly expect deal activity to accelerate in the second half of 2026, contingent on macroeconomic stability and continued easing by major central banks.

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KPMG Thought LeadershipMay 13

The 2026 KPMG Global Third-Party Risk Management Survey

Despite 8 in 10 organizations reporting third-party risk management as a board-level priority, most programs remain underfunded and operationally immature, unable to keep pace with the scale and complexity of modern vendor ecosystems. The survey found that fewer than half of respondents have full visibility into their extended third-party networks, including fourth and fifth parties, leaving critical exposure gaps. Cyber and data privacy risk tops the list of third-party concerns, yet only a minority of organizations conduct continuous monitoring, relying instead on point-in-time assessments that fail to capture real-time risk changes. AI adoption is accelerating the problem, with third parties increasingly deploying AI tools that organizations have limited ability to audit or govern. Regulatory pressure is intensifying globally, with frameworks such as DORA in Europe driving firms to formalize oversight structures, though compliance efforts remain inconsistent across geographies and industries. The report concludes that organizations must shift from reactive, checklist-driven approaches to integrated, technology-enabled TPRM programs with clear ownership, adequate investment, and continuous risk intelligence.

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KPMG Thought LeadershipMay 13

The modern CFO

The modern CFO role has fundamentally expanded beyond financial stewardship into strategic enterprise leadership, with finance chiefs now expected to drive growth, manage enterprise-wide risk, and guide technology transformation simultaneously. CFOs face mounting pressure across four core dimensions: delivering on traditional financial oversight, enabling data-driven decision-making, leading digital and AI adoption, and serving as a key partner to the CEO and board on long-term strategy. Talent retention and workforce transformation within the finance function represent a critical operational challenge, as automation reshapes which capabilities the function needs. CFOs who successfully navigate this expanded mandate invest in modernizing finance infrastructure while developing their teams' analytical and strategic competencies. The role increasingly demands fluency in technology, sustainability reporting, and stakeholder communication well beyond conventional accounting and treasury expertise. Organizations whose CFOs operate at this broader strategic level demonstrate stronger alignment between capital allocation decisions and enterprise value creation.

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KPMG Thought LeadershipMay 13

Winners Don’t Wait: AI-First Transformation in Volatile Times | KPMG Velocity

KPMG's central argument is that volatility is not a reason to pause transformation but an accelerant for it — organizations that move decisively on AI-first strategies now will widen their competitive gap while hesitant peers stall. The research positions AI not as a discrete technology initiative but as a full operating model redesign, requiring leaders to rewire strategy, talent, and processes simultaneously rather than sequentially. Companies achieving the strongest returns are treating AI transformation as an enterprise-wide commitment, not a series of isolated pilots, and are moving from experimentation to scaled deployment at speed. The report emphasizes that uncertainty itself — tariffs, geopolitical disruption, economic volatility — historically rewards bold movers who use transformation to structurally reduce costs and build resilience rather than waiting for conditions to stabilize. Execution discipline, clear ownership, and governance frameworks are identified as the differentiating factors between organizations capturing AI value and those generating activity without results.

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KPMG Thought LeadershipMay 12

From Automation to AI: Tech leaders are focused on ROI | KPMG

US technology leaders are shifting AI investment strategies from broad experimentation toward measurable business outcomes, with ROI now the dominant lens for evaluating technology spending. The KPMG 2026 US Technology Survey finds that organizations are moving beyond initial automation initiatives to more targeted AI deployments directly tied to productivity gains, cost reduction, and revenue generation. Cybersecurity, cloud infrastructure, and AI remain the top three funding priorities, but budget justification has become more rigorous as boards and CFOs demand clearer proof of value. Talent gaps and data readiness continue to rank as the primary barriers to scaling AI, with many organizations still struggling to connect AI pilots to enterprise-wide impact. Governance and risk management frameworks are increasingly viewed as prerequisites rather than afterthoughts, reflecting growing regulatory scrutiny and internal accountability pressures. Technology leaders who can demonstrate concrete financial returns are securing larger budgets, while those unable to quantify impact are seeing investment stall.

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KPMG Thought LeadershipApril 17

security framework

KPMG's AI Security Framework Design service addresses the growing need to secure artificial intelligence systems as organizations accelerate AI adoption across enterprise operations. The framework provides a structured approach to identifying, assessing, and mitigating security risks specific to AI and machine learning environments, including model integrity, data poisoning, and adversarial threats. KPMG integrates this AI-specific security architecture with existing cybersecurity governance programs, enabling organizations to manage AI risk within their broader enterprise security posture. The service targets boards and C-suite leaders who need defensible governance structures to meet emerging regulatory expectations around AI accountability and security. Organizations that adopt a purpose-built AI security framework early are better positioned to scale AI initiatives without introducing uncontrolled risk into critical systems.

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KPMG Thought LeadershipMarch 10

KPMG CFO life sciences roundtable first edition

Life sciences CFOs face a dual mandate: driving growth through innovation and M&A while simultaneously cutting costs to fund R&D pipelines under intensifying margin pressure. The Inflation Reduction Act's drug pricing provisions represent the most disruptive near-term regulatory challenge, forcing CFOs to reassess portfolio strategy and capital allocation earlier in the product lifecycle than previously required. Talent costs and retention remain a top operational concern, with finance functions competing for specialized skills in data analytics and digital transformation. CFOs are accelerating investment in finance automation and AI-enabled forecasting tools to reduce the cost-to-serve of the finance function while improving decision support speed. Supply chain resilience has been elevated to a board-level financial risk, requiring CFOs to weigh the cost of redundancy against vulnerability to disruption. The overarching tension for life sciences CFOs is balancing short-term investor pressure for profitability with the long-cycle capital commitments that define the industry's value creation model.

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KPMG Thought Leadership2025

6 Key Questions Finance Leaders Are Asking About Data and Analytics | KPMG

Finance leaders are converging on 6 critical questions as they work to extract business value from data and analytics investments, with the central challenge being how to move from reporting what happened to driving decisions about what to do next. The questions span data governance and trust, the right operating model for analytics, talent and capability gaps, technology architecture choices, AI integration into finance processes, and how to measure the return on data investments. Data quality and trust remain the foundational barrier, as analytics initiatives stall when business stakeholders don't believe the numbers, making governance a prerequisite rather than an afterthought. Finance functions are being pressed to shift from centralized data ownership to federated or hybrid models that balance control with speed, requiring deliberate choices about where analytics capability sits organizationally. AI and generative AI are accelerating the timeline for finance transformation but also raising new questions about model risk, auditability, and workforce redesign that CFOs must address before scaling. Leaders who treat data and analytics as a strategic asset tied to specific business outcomes, rather than a technology program, are closing the gap between investment and measurable impact faster than peers who lack that business-case discipline.

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KPMG Thought Leadership2025

AI-Enabled Financial Close as a Service | KPMG

KPMG's AI-Enabled Financial Close as a Service offering reframes the traditional month-end close as a managed, AI-augmented process rather than an internal finance function, targeting the persistent inefficiencies that plague most organizations' close cycles. Finance teams typically spend the majority of close time on manual, low-value tasks such as reconciliations, journal entries, and intercompany eliminations — areas where AI and automation can eliminate significant labor and error rates. KPMG's model combines its accounting and process expertise with AI-powered technology platforms to deliver close activities as an ongoing managed service, shifting fixed finance costs toward a variable, outcome-based structure. The approach targets measurable outcomes including faster close timelines, reduced cost per close, and improved data accuracy, while freeing internal finance talent to focus on analysis and decision support. Human oversight and controls are embedded throughout to satisfy audit and regulatory requirements, positioning AI as an accelerant rather than a replacement for professional judgment.

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KPMG Thought Leadership2025

AI-Powered Finance as a Service KPMG

KPMG's Finance as a Service (FaaS) model positions AI as the core driver for transforming finance functions from transactional processors into strategic business partners. The model combines AI-enabled automation, cloud platforms, and outcome-based managed services to allow organizations to consume finance capabilities on demand rather than building and maintaining them internally. KPMG projects that AI-powered FaaS can reduce finance operating costs by 40–60% while simultaneously improving speed, accuracy, and analytical depth across core processes including close, reporting, FP&A, and compliance. The approach shifts finance talent away from manual execution toward higher-value interpretation and decision support, with AI agents handling routine tasks end-to-end. Adoption is structured around three maturity stages—standardize, automate, and augment—enabling organizations to scale at a pace aligned with their technology readiness and risk tolerance. KPMG frames this not as incremental improvement but as a fundamental redesign of how finance operates, with competitive advantage accruing to organizations that move earliest and most decisively.

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KPMG Thought Leadership2025

Finance AI Solutions: Transform Your Finance Operations | KPMG

KPMG positions AI-enabled Finance as a Service as the path for finance functions to move beyond transactional processing toward strategic decision support. The offering combines AI, automation, and cloud-based platforms to reduce manual effort across core finance processes including record-to-report, order-to-cash, and procure-to-pay. By embedding AI agents and intelligent automation into these workflows, organizations can compress close cycles, improve forecast accuracy, and redeploy finance talent toward higher-value analysis. KPMG frames this not as incremental technology adoption but as a structural redesign of the finance operating model, integrating tools with process and talent transformation. The firm presents itself as providing both the technology implementation capability and the functional finance expertise required to scale AI solutions with controls and governance intact.

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KPMG Thought Leadership2025

Future of Financial Planning: Smarter EPM with AI | KPMG

AI-embedded Enterprise Performance Management (EPM) is moving financial planning from periodic, backward-looking reporting to continuous, forward-looking decision intelligence. KPMG argues that integrating generative and predictive AI into EPM platforms enables finance functions to automate routine planning tasks, compress forecasting cycles, and shift FP&A talent toward higher-value strategic analysis. The piece identifies three core capability shifts: AI-driven scenario modeling that processes more variables at greater speed, natural language interfaces that democratize access to financial data across business units, and autonomous anomaly detection that improves forecast accuracy and control. KPMG cautions that realizing these gains requires organizations to first address data quality, governance, and model explainability — without which AI outputs lack the reliability needed for executive decision-making. The firm positions itself as an implementation partner capable of bridging EPM platform capabilities with enterprise AI strategy, change management, and finance operating model redesign.

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KPMG Thought Leadership2025

Future of the Financial Close | KPMG

The article's content beyond navigation elements was not provided, so I cannot summarize the substance of KPMG's findings on the future of the financial close. The title "The Future of the Financial Close: Smarter, Faster, Trusted" signals a focus on modernizing period-end reporting through automation and AI, but no data, arguments, or recommendations from the body of the piece were included in the text supplied. To deliver an accurate 4-6 sentence executive summary, please provide the full article body. I will not fabricate findings or statistics that were not present in the source material.

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KPMG Thought Leadership2025

How Finance Leaders Unlock the Power of Data | KPMG

Finance leaders who treat data as a strategic asset rather than a reporting byproduct are gaining measurable competitive advantage, and those who fail to make this shift risk being left behind as AI-driven decision-making becomes the standard. The article identifies a persistent gap between data availability and data utility, with many CFOs still spending the majority of their time on data gathering rather than analysis and strategic counsel. High-performing finance organizations share three common traits: a unified data architecture that eliminates silos, clearly defined data governance ownership, and finance talent that combines analytical fluency with business acumen. Investment in cloud-based platforms and automation is accelerating close cycles and freeing capacity, with leading organizations reducing manual data processing by 30 to 50 percent. KPMG argues that the CFO must take an active role in enterprise data strategy, not just consume outputs from IT, positioning finance as the connective tissue between operational data and enterprise value creation. Organizations that align data infrastructure investment with finance transformation initiatives are realizing faster ROI and stronger forecasting accuracy than those treating the two as separate workstreams.

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KPMG Thought Leadership2025

Integrating Finance as a Service into GBS for Higher Value | KPMG

Global Business Services organizations that remain focused on cost reduction and transactional efficiency are leaving significant value on the table. KPMG's central argument is that integrating Finance as a Service (FaaS) into GBS transforms finance from a back-office function into a strategic value driver by combining advanced technology, data analytics, and flexible service delivery. This model shifts GBS finance capabilities beyond standardization toward predictive insights, real-time reporting, and decision support that directly enables business growth. FaaS within GBS leverages AI, automation, and cloud platforms to reduce manual processing costs while simultaneously elevating output quality and speed. Organizations that make this transition can expect measurable improvements across cycle times, cost-per-transaction metrics, and the ratio of finance staff focused on analysis versus transaction processing. The path forward requires deliberate redesign of operating models, talent strategies, and governance structures rather than incremental layering of technology onto existing GBS frameworks.

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KPMG Thought Leadership2025

The Future of Finance with AI

AI is poised to fundamentally reshape the finance function, shifting it from a backward-looking reporting role to a forward-looking, intelligence-driven operation. KPMG argues that finance leaders who treat AI as a strategic capability rather than a back-office efficiency tool will gain measurable competitive advantage. Automation of routine tasks such as reconciliations, forecasting, and close processes can free finance professionals to focus on higher-value analysis and decision support. The transformation requires deliberate investment in data quality, governance frameworks, and workforce reskilling, as technology alone will not deliver results without organizational readiness. CFOs are urged to act now by piloting AI use cases, building scalable data infrastructure, and embedding AI literacy across finance teams. Organizations that delay risk ceding ground to peers who are already converting AI investment into faster, more accurate financial insight.

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KPMG Thought Leadership2025

The Future of the CFO

The CFO role is undergoing a fundamental structural shift, expanding well beyond financial stewardship into enterprise-wide strategic leadership across technology, talent, and transformation. Modern CFOs are expected to operate across five distinct dimensions simultaneously: financial guardian, strategic advisor, technology champion, talent leader, and external stakeholder communicator. AI and automation are compressing the time finance teams spend on transactional work, freeing CFOs to allocate more bandwidth to forward-looking analysis and decision support for the CEO and board. The expanding mandate creates a capability gap, as fewer than half of finance organizations report having the digital skills required to execute on this broader agenda. KPMG positions the path forward as deliberate investment in finance talent development, operating model redesign, and technology adoption — with CFOs who delay on any of these three fronts risking strategic irrelevance. The CFOs most likely to succeed are those who treat the finance function itself as a business to be continuously transformed, not merely a control function to be managed.

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KPMG Thought Leadership2025

The future of the close with AI

AI is poised to fundamentally transform the financial close process by automating routine tasks, reducing cycle times, and shifting finance professionals toward higher-value analytical work. KPMG argues that organizations applying AI to the close can move from a reactive, backward-looking reporting function to a continuous, forward-looking insights engine. Key use cases include automated journal entry preparation and review, anomaly detection in account reconciliations, and AI-assisted variance analysis and commentary generation. The technology targets a close process where manual effort still dominates, with many finance teams spending 60–70% of close time on low-judgment data gathering and formatting tasks. Realizing these gains requires foundational investments in data quality, standardized processes, and clear human oversight protocols before AI can operate reliably at scale. KPMG positions the transformation as phased, beginning with task-level automation and progressing toward an autonomous close supported by agentic AI systems.

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KPMG Thought LeadershipApril 9

kpmg google cloud alliance expansion agentspace adoption

KPMG has expanded its AI alliance with Google Cloud to accelerate enterprise adoption of Google's Agentspace platform, delivering modular and scalable AI agent solutions to clients across legal services, banking, and other industries. The collaboration moves beyond a standard vendor relationship, positioning KPMG as an implementation and transformation partner that combines Google Cloud's AI infrastructure with the firm's industry-specific expertise. Target use cases focus on automating and augmenting complex business operations where agentic AI—systems capable of reasoning and taking multi-step actions—can drive measurable efficiency gains. The partnership is designed to scale across sectors, with legal and financial services serving as initial deployment verticals given their high volumes of document-intensive, decision-driven workflows. KPMG's investment in this alliance reflects a broader strategic bet that agentic AI, not generative AI alone, will define the next wave of enterprise transformation.

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KPMG Thought LeadershipJanuary 21

ai quarterly pulse survey

KPMG's AI Quarterly Pulse Survey finds enterprises are moving decisively from AI experimentation into large-scale production, with 2026 marked as the inflection point for this transition. The survey tracks sentiment and investment patterns across agentic AI, generative AI, AI scaling, and workforce integration. Organizations are prioritizing trusted AI frameworks as deployment velocity increases and governance demands intensify. The shift reflects growing executive confidence in AI's measurable business value, moving the conversation from proof-of-concept ROI to operational performance at scale.

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KPMG Thought Leadership

4 ways AI can empower Finance

AI is poised to fundamentally reshape the Finance function by shifting it from transaction processing toward strategic value creation. KPMG identifies 4 core application areas: automating routine financial operations, enhancing forecasting and scenario planning through predictive analytics, strengthening risk management and compliance monitoring, and enabling Finance teams to deliver deeper business insights faster. These capabilities collectively reduce manual effort, compress reporting cycles, and improve decision quality across the enterprise. Realizing this value requires Finance leaders to address data quality, talent upskilling, and governance frameworks before scaling AI deployment. Organizations that move deliberately on these foundations stand to convert Finance from a cost center into a forward-looking strategic partner to the business.

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KPMG Thought Leadership

From digital to intelligent close

Finance organizations must evolve from digitally enabled close processes to AI-driven intelligent close operations to remain competitive and meet rising demands for faster, more accurate financial reporting. The intelligent close moves beyond automation of discrete tasks to embed AI and machine learning across the entire record-to-report cycle, enabling continuous accounting, real-time anomaly detection, and predictive analytics rather than periodic batch processing. This shift reduces close cycle times, lowers error rates, and frees finance talent from transactional work to focus on analysis and decision support. Achieving this requires organizations to address three interdependent layers: data quality and integration, process standardization, and AI-enabled technology platforms. KPMG positions the transition as a strategic imperative, not an incremental upgrade, requiring deliberate investment in governance, talent upskilling, and technology architecture to unlock the full value of an intelligent close.

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KPMG Thought Leadership

Global Business Services: The future is AI—and it’s here.

AI is fundamentally reshaping Global Business Services (GBS), moving the function beyond traditional cost arbitrage toward a strategic driver of enterprise value. Organizations that integrate AI into GBS operating models are achieving measurable gains in process automation, decision intelligence, and workforce productivity that exceed what prior generations of shared services delivered. The window for competitive differentiation is narrowing, as early adopters are pulling ahead while laggards risk structural cost and capability disadvantages that will be difficult to close. Successful transformation requires more than technology deployment — it demands redesigned processes, new talent models, and governance frameworks that embed AI accountability from the outset. GBS leaders are being called to move from pilots to scaled adoption, treating AI not as an enhancement to existing workflows but as a foundational reset of how services are delivered. Organizations that act now with intentional strategy and executive commitment will define the next performance benchmark for GBS.

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KPMG Thought Leadership

Fifth Annual CAO Survey: Fast-tracking the future

KPMG's Fifth Annual CAO Survey finds that chief accounting officers are accelerating the pace of finance function transformation, driven primarily by automation, AI adoption, and mounting regulatory complexity. The majority of CAOs report increasing pressure to deliver real-time data and insights to the C-suite while simultaneously managing a growing volume of compliance and reporting obligations. Talent remains a critical constraint, with CAOs citing difficulty attracting and retaining professionals who combine technical accounting expertise with data and technology fluency. Investment in cloud-based ERP systems and advanced analytics tools is rising as organizations seek to reduce manual close processes and improve forecast accuracy. CAOs are also expanding their strategic remit beyond traditional controllership, taking on broader roles in enterprise risk, ESG reporting, and digital finance initiatives. The survey signals that organizations lagging on technology investment and workforce upskilling face measurable risk of falling behind peers on both efficiency and decision-support capability.

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KPMG Thought Leadership

Supercharge your Finance workforce with GenAI

GenAI presents a significant productivity opportunity for finance functions, with the potential to automate or augment a substantial share of routine analytical, reporting, and forecasting tasks. Finance organizations that deploy GenAI strategically can redirect workforce capacity from transactional processing toward higher-value decision support and business partnering. KPMG identifies use cases across the finance value chain, including variance analysis, management reporting, audit preparation, and scenario modeling, where GenAI can compress cycle times and reduce manual effort. Successful implementation requires deliberate investment in data quality, governance frameworks, and workforce upskilling, as technology alone does not deliver value without the right operating model. CFOs are advised to prioritize a phased adoption roadmap that balances speed to value against risk controls, particularly around data integrity and model reliability. Organizations that move early and build GenAI fluency into their finance talent base are positioned to gain a durable competitive advantage.

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KPMG Thought Leadership

Will generative AI mean the death of service delivery centers?

Generative AI will not eliminate service delivery centers but will fundamentally transform their purpose and composition. The labor arbitrage model that justified offshoring — moving high-volume, repetitive transactional work to lower-cost locations — is directly threatened as AI automates the same routine tasks those centers were built to perform. Rather than shutting down, organizations that adapt will reposition their centers around higher-value work: AI model governance, exception handling, process design, and judgment-intensive activities that require human oversight. The workforce profile will shift materially, demanding fewer transactional processors and more technologists, analysts, and specialists capable of managing AI-augmented operations. Centers that fail to evolve their talent mix and operating model risk becoming obsolete, while those that reinvent themselves as hubs for AI-enabled service delivery can capture new productivity and capability advantages. The strategic imperative is not whether to maintain these centers, but how quickly leaders redesign them before the cost-and-efficiency rationale that built them disappears.

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KPMG Thought LeadershipJuly 12

kpmg microsoft agreement 2023

KPMG and Microsoft announced a landmark multi-year cloud and AI agreement in July 2023, committing to embed artificial intelligence across KPMG's Audit, Tax, and Advisory practices. The alliance centers on Microsoft's Azure OpenAI Service, Microsoft 365 Copilot, and related cloud infrastructure to transform how KPMG delivers professional services. KPMG committed to investing $2 billion over 5 years in AI and cloud capabilities, with Microsoft's technology forming the core platform for that buildout. The deal targets both internal workforce productivity and the development of new AI-powered client solutions at scale. This positions KPMG as one of the largest professional services deployments of Microsoft's generative AI stack, with the intent to differentiate across all three service lines against Big 4 competitors.

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