Real stories. Real results.

Developing algorithm process model for comprehensive AI governance

A ministry needed an integrated governance approach for the responsible development, acquisition, and deployment of algorithms and AI systems. It required ethical, legal, and technical frameworks to manage frontline risk in times of significant technological change. We developed the Algorithm Process Model (APM), a comprehensive framework covering the entire algorithm lifecycle from initiation to decommissioning, including assessment frameworks, templates, and guidance for ten distinct phases spanning idea generation through implementation and monitoring. The structured model was tested across five diverse algorithmic applications—from decision support to predictive maintenance—and includes EU AI Act implementation advice, ethical principles based on international guidelines, and procurement policy recommendations. It provided the organisation with a robust, integrated approach to responsible algorithm governance across all operational domains.

Co-creating a future-ready AI vision and roadmap

A national land registry agency sought to develop a comprehensive AI vision aligned with its public mission and core values to guide effective and responsible AI implementation across its operations. We supported the organisation through contextual analysis, co-creation workshops, and stakeholder interviews to identify strategic opportunities, risks, and organisational priorities. We developed an AI vision that identified opportunities within the organisation, aligned AI initiatives with the business and organisational strategy and goals, and established a roadmap of actions needed to enhance the organisation's AI maturity level. The resulting strategy positioned the agency for AI-driven transformation while maintaining its commitment to public values and provided clear guidance for broader AI maturity development across governance, organisational structure, and AI literacy initiatives.

Develop strategic AI roadmap for a non-profit helpline  

A national youth helpline sought strategic guidance to navigate digital transformation and identify opportunities for Responsible AI adoption while maintaining its human-centric mission and ethical standards. Acting as strategic advisors to the executive team, we facilitated in-depth discussions on AI implementation and future direction, focusing on organisational needs and opportunities with strong emphasis on human impact and ethical considerations. We developed tailored AI use cases and translated them into a strategic roadmap aligned with the helpline's operational and long-term goals and broader business and organisational strategy. This roadmap now serves as a foundation for Responsible AI integration, enabling the organisation to harness AI's potential while safeguarding its human-centric mission.

Scaling data & AI transformation across global insurance operations  

A global insurance company faced uneven maturity across data & AI capabilities, insufficient alignment between local units and central leadership, and a variety of operating models that prevented them from unlocking value from their data at scale. We supported their data & AI strategy development across nine business units and the central organisation, assessing current capabilities, designing future-state blueprints, and delivering a comprehensive roadmap with clear milestones. The transformation delivered a harmonised operating model, prioritised AI use cases, and a scalable structure including a dedicated data & AI hub, laying the foundation for agentic AI implementation and stronger cross-functional collaboration across the global organisation.

Intelligent document processing with AI for enhanced efficiency

Function: Legal Risk & Compliance | Business: Financial sector

A financial entity needed to evaluate its potential exposure following a landmark judicial ruling that affected the treatment of certain interest claims under bankruptcy law. The client was responsible for assessing thousands of debt instruments. It was critical to identify which notes might be subject to due interest claims. However, analysing thousands of contracts manually to determine the relevance and potential impact of these claims posed a major efficiency and accuracy challenge.

PwC supported this effort by deploying the AI-powered document analysis platform Harvey to extract and organise key metadata from over 4,000 contracts. This included key attributes such as issue dates, maturity, governing law, and programme classifications. The platform enabled the team to create a comprehensive, searchable database, while highlighting gaps needing targeted manual review. Using this structured data, the team rapidly classified securities, aligned them with relevant regulatory frameworks, and assessed claim relevance based on statutory limitation periods.

Our solution delivered a precise, high-quality analysis that identified financial notes potentially exposed to interest claims. This significantly reduced manual workload, improved analysis accuracy, and empowered the client and their investors with actionable insights to proactively manage their legal and financial risk exposure.

Accelerating operational efficiency with agentic AI architecture  

An international financial institution sought to improve operational efficiency by increasing straight-through-processing rates across key business processes. With a mature data environment already in place, the organisation was well-positioned to scale AI adoption. We designed an agentic solution architecture that enables rapid development and integration of AI agents into existing systems, facilitates sharing of AI capabilities and agents across business units, and ensures control over reliability and deployment costs. The result was a standardised architecture that reuses core data and AI components already active within the client’s ecosystem, while leveraging cutting-edge agentic technologies. The engagement also delivered a clear roadmap for platform development to accelerate implementation.

Intelligent document processing with AI for enhanced efficiency

Function: Financial Risk & Compliance | Business: Public sector

A government-backed financial institution aimed to improve the efficiency and accuracy of its document-heavy operations. The challenge was to streamline the review of thousands of customer financial documents processed daily, while ensuring compliance with data privacy regulations.

PwC supported this transformation by implementing AI-powered document analysis tools built on open-source large language models. These tools were designed to automate key tasks such as identifying and redacting personally identifiable information (PII) to enhance data protection, generating concise summaries of lengthy documents to enable faster and more targeted reviews, and detecting language patterns likely to be relevant for financial assessments to help teams focus on critical content.

By embedding these AI capabilities into daily operations, the institution significantly reduced manual effort, improved processing speed, and enhanced the quality of document reviews. The result was a scalable, future-ready solution that empowered employees to focus on high-value tasks while maintaining rigorous compliance standards.

Developing algorithm process model for comprehensive AI governance

A ministry needed an integrated governance approach for the responsible development, acquisition, and deployment of algorithms and AI systems. It required ethical, legal, and technical frameworks to manage frontline risk in times of significant technological change. We developed the Algorithm Process Model (APM), a comprehensive framework covering the entire algorithm lifecycle from initiation to decommissioning, including assessment frameworks, templates, and guidance for ten distinct phases spanning idea generation through implementation and monitoring. The structured model was tested across five diverse algorithmic applications—from decision support to predictive maintenance—and includes EU AI Act implementation advice, ethical principles based on international guidelines, and procurement policy recommendations. It provided the organisation with a robust, integrated approach to responsible algorithm governance across all operational domains.

Accelerating AI risk governance for digital transformation

A large financial institution wished to accelerate the pace of its AI implementation by strengthening its in-house AI risk expertise. We provided hands-on subject matter expertise to the second-line risk management team to clear backlogs, establish lasting governance practices in relation to (generative) AI use cases, and co-develop an AI risk control framework aligned with ISO/IEC 42001. We advised on AI policy updates and upskilled the internal risk team, delivering faster approvals, stronger controls, and a repeatable assessment process for responsible AI implementation.

Building comprehensive AI risk framework for EU AI Act compliance  

A technology-driven financial institution was looking to systematically manage AI risks and prepare for compliance with the newly introduced EU AI Act across their AI-powered operations. Our cross-line-of-service team helped navigate EU AI Act requirements by analysing several scalable AI use cases in customer service and internal operations, while assessing regulatory and governance needs. We established an organisation-wide AI inventory, delivered AI literacy sessions, and developed a comprehensive AI risk management blueprint with defined roles, responsibilities, and AI principles. This resulted in a tailored framework that enhanced risk management capabilities, streamlined processes, improved operational efficiency, and guided the organisation toward full compliance readiness.

Mapping Responsible AI readiness for a ministry  

A ministry aimed to promote the responsible use of data, AI, and algorithms in anticipation of future legal obligations, including the EU AI Act. We conducted a needs assessment across ten operational agencies to understand current practices and future requirements. The approach included document analysis, informative sessions on upcoming legislation, discussions on Responsible AI, and a joint validation workshop. The outcome was a detailed report that comprehensively mapped the ministry's needs in policy, communication, and training, enabling informed decision-making for Responsible AI implementation across all operational agencies.

AI-Accelerated IT Controls Gap Assessment for J-SOx Compliance

Function: IT Risk & Compliance | Business: Automotive

An international mobility manufacturer wanted to review how their current IT control framework compared to J-SOx best practices and the standard controls for their S/4HANA system. Their objective was to make sure their controls met regulatory requirements and system standards, an important but time-consuming task when done manually.

PwC helped speed up this process by utilising the AI Agent Platform. Based on the client's documentation and the best practice guidance, an initial review of potential gaps was performed. Throughout the process, PwC experts reviewed the AI’s findings, iteratively providing the human input and feedback to improve the results and ensure accuracy.

This combination of AI support and expert insight allowed to quickly and thoroughly identify areas where the client’s controls could be strengthened. As a result, the client received a clear and detailed assessment highlighting where improvements were needed to meet J-SOx and S/4HANA standards. The outcome was a faster, more efficient way to understand control gaps and plan fixes, helping the client build a stronger, compliant control environment with greater confidence and less manual effort.

Accelerating policy alignment with AI-powered gap analysis

Function: Legal Risk & Compliance | Business: Financial sector

A prominent global financial services firm encountered significant hurdles in managing regulatory changes. Their entire capacity for change was absorbed by compliance tasks, limiting their ability to focus on business growth, product innovation, and enhancing customer experiences.

To tackle this, we at PwC introduced the Policy Gap Analyzer to fast-track regulatory change processes. The core idea is that compliant policies lay the groundwork for aligning organisational standards and business processes with regulations. We tested the tool by evaluating compliance with the General Data Protection Regulation (GDPR). It compared regulatory requirements with the company's Personal Data policy, demonstrating its ability to speed up compliance efforts.

The Policy Gap Analyzer boosted efficiency by automating the identification of policy gaps. It facilitated the alignment of policies with current regulations and reduced manual effort, freeing up valuable compliance resources. Ultimately, the organisation achieved quicker compliance, responded more swiftly to regulatory changes, and reduced risk exposure. This shift allowed them to redirect their change capacity from regulatory responses to business-centric activities.

Driving efficiency and engagement with Microsoft 365 Copilot

A rapidly expanding technical service provider needed to leverage AI and Microsoft 365 Copilot to enhance operational scalability while reducing costs. We conducted a six-week program with employees from four key functions, combining hands-on training with strategic use case development. We also provided practical implementation guidance and identified opportunities for AI agent applications. The program delivered significant results: participants saved an average of seventy minutes per week while reporting improved job satisfaction. We co-developed 25 high-value use cases and identified nine AI agent-based solutions for additional business value. The company received a structured phased rollout strategy with targeted recommendations for scaling AI capabilities across the entire organisation.

Implementing (Gen)AI at leading healthcare knowledge institute  

A leading healthcare information provider faced challenges with manual, inconsistent processes for capturing and exchanging critical data across their network, creating bottlenecks that slowed information flow when speed and accuracy were essential. We implemented ChatGPT Enterprise and built a custom AI lab, launching three pilot AI assistants that were iteratively improved and scaled to over thirty solutions through hands-on training, hackathons, and governance frameworks. The program achieved 75 per cent staff adoption within six months and delivered six core use cases that transformed daily operations, positioning generative AI as a strategic enabler for faster, more consistent healthcare information standardisation and exchange across their entire ecosystem.

Transforming document intelligence with AI-powered digital expert

A major bank faced challenges navigating thousands of project documents across work instructions, audits, regulatory compliance, and process execution, creating inefficiencies in knowledge management. To address this, we developed the Digital Project SME, a GenAI-powered Power BI dashboard that serves as an intelligent subject matter expert. Leveraging Llama models and Power BI, the solution allows users to get answers to questions across organisational documentation and access GenAI-generated summaries and insights through a user-friendly interface. The solution enables fast and accurate document retrieval and delivers significant time and cost savings while transforming document management into a smart, efficient experience.

Empowering financial decision-making with AI-powered assistant

A leading consumer goods company faced significant market challenges and process bottlenecks that hindered their ability to leverage available data effectively for financial planning and reporting across the organisation. We developed an AI-powered assistant using AzureAI and PowerBI that enables users across finance and non-finance functions to interact with financial data through natural language, streamlining processes foro financial planning and analysis, and removing data accessibility barriers. Delivered in two phases, use case identification and MVP implementation, the solution improved data accessibility, enhanced reporting accuracy, and strengthened decision-making capabilities across the business.

Developing AI custodian assistant for global operational efficiency

A major international organisation's standardisation office needed to accelerate maintenance of several thousands of standardized documents, as manual processes were labour-intensive and slowed collaboration among its thousands of registered users. We developed an AI-powered assistant using Azure OpenAI and Logic Apps that automates repetitive documentation tasks, enhances compliance and data governance, and intelligently adds relevant references to streamline workflows. The solution revolutionised collaboration and accessibility for the organisation's global community, enabling more agile operations and empowering users with effortless navigation, maintenance, and collaboration on critical standardisation documents.

Reimagining the claims handling process for a leading property and casualty insurer  

Business: Insurers  

A leading property & casualty insurer operated a highly manual claims process resulting in significant inefficiencies throughout the process and low NPS scores amongst colleagues and clients. We helped the insurer redefine the future state of their claims organisation identifying the claims workforce of the future. Subsequently, we detailed the key shifts infusing agentic AI to redefine high volume process steps and launched pilots to drive real results. The result: reduced turnaround time, lower average handling time, reduced costs per claim, and decreased inbound query calls.

Building accurate financial models for volatile energy market

Function: Finance

One of the leading energy companies in the Netherlands needed to adjust their financial reporting models for commodities (Gas and Power) to handle the highly volatile energy market, as traditional gross margin calculations were no longer providing accurate output in unstable market conditions. We developed a sophisticated financial model that provides highly detailed and accurate actual insights by integrating usage-, pricing- and sourcing data through a state-of-the-art data platform across the B2C domain. As this effort led to reconciliation of information across the business unit, various other initiatives were spinning off to improve data maturity. Through multiple MVP phases, the model now has a proven (>1 year) track record of highly accurate volume and revenue reporting of Gas and Power. Next to the much needed improved reliability of external reporting, this enables the company to more actively drive performance through improved management reporting (customer value and insights across the full value chain) compared to legacy systems.

Delivering smarter IT health and policy compliance through automated dashboards

Business: Pension | Function: IT

A leading pension provider faced challenges with inconsistent quarterly IT health reporting across seven value streams, relying heavily on manual processes that impeded effective decision-making. In response, we developed the Digital Health Cockpit, an automated dashboard that replaces manual reporting with a unified view of the digital landscape. Additionally, a policy monitor has been designed to track real-time compliance with IT, data, and AI policies. This integrated solution is set to provide instant insights, support improved governance decisions, and centralise all health monitoring in one place, transforming how the organisation manages IT oversight and policy compliance.

Empowering financial decision-making with AI-powered assistant

Function: Finance  

A leading consumer goods company faced significant market challenges and process bottlenecks that hindered their ability to leverage available data effectively for financial planning and reporting across the organisation. We developed an AI-powered assistant using AzureAI and PowerBI that enables users across finance and non-finance functions to interact with financial data through natural language, streamlining processes foro financial planning and analysis, and removing data accessibility barriers. Delivered in two phases, use case identification and MVP implementation, the solution improved data accessibility, enhanced reporting accuracy, and strengthened decision-making capabilities across the business.

Risk & compliance – Control optimisation and automation through AI Agents Platform

Function: Financial Risk & Compliance | Business: Energy Infrastructure

A Transmission System Operator (TSO) aimed to transform and enhance its internal control system. The goal was to develop a fully documented set of best-in-class finance processes, supported by a robust internal control framework aligned with industry standards. PwC supported this transformation by leveraging its AI Agent Platform (AIAP), a proprietary tool designed to accelerate risk and compliance work through advanced prompt engineering and automation. The platform analysed client documentation, such as control descriptions and process flows, and benchmarked it against PwC’s extensive best practice libraries.

AIAP enabled the team to rapidly identify control gaps, improvement opportunities, and areas for automation. For example, it was used to assess control maturity by validating completeness and quality, prepare risk assessments by comparing existing frameworks to international standards, and enhance the Risk and Control Matrix (RCM) by identifying automation opportunities tailored to the client’s ERP environment. The result was a future-ready control framework delivered with greater speed, precision, and strategic value, empowering the client to focus on high-impact risk management decisions.

Optimising service operations with intelligent route planning

Business: Asset-heavy industry

An equipment manufacturer partnered with us to transform their maintenance operations and evolve into a service-driven organisation. By automating service route planning, they aimed to improve efficiency, reduce operational costs, and strengthen customer relationships. We developed a tailored algorithm that translated their business rules into a smart optimization engine, delivered through an intuitive interface with advanced planning capabilities. The Azure-hosted solution streamlined all service visits, prioritised critical breakdowns, and intelligently combined preventive and corrective tasks. Within weeks, the client was able to enhance engineer productivity, deliver faster response times, and reduced travel and planning efforts. This transformation not only improved service quality but also helped the client build long-term customer loyalty through timely and efficient maintenance.

Accelerating AI adoption at a large grocery retailer

The FP&A team at a leading retail company was seeking support to accelerate their AI journey. We guided them by identifying and prioritising use cases and introducing Microsoft Copilot to demonstrate immediate value. Through targeted workshops and interviews, we helped the team distinguish between use cases ready for implementation and those better suited to future, extended AI solutions. Our upskilling sessions equipped an initial group of professionals to integrate Copilot into their workflows. As a result, time was repurposed from non-value-adding to value-adding activities, alongside increased understanding of AI tooling and greater enthusiasm to expand the AI toolbox.

Redesigning a data platform for a financial institution

An international financial institution was operating with fragmented data platforms across its country organisations, making it difficult for agents to access and use data consistently. Legacy environments further complicated data extraction and governance, creating inefficiencies and risks. We designed a standardised architecture for a unified data platform and built custom migration tooling to unlock legacy systems. Our team developed a full migration plan, including costing, and conducted deep dives into data governance and data extraction tooling. To validate the approach, we piloted the migration in one country, testing both the tools and the process end-to-end. The pilot validated the new data platform. Migration to other countries kicked off.