Industry
High Tech
High Tech Solutions to Drive Business Transformation through Technology
Highlights
- Audit and consulting firms are undergoing a fundamental transformation, driven by evolving client expectations, regulatory changes, and the rapid adoption of advanced technologies like Generative and Agentic AI.
- GenAI and Agentic AI are reshaping the audit and consulting value chains—enabling automation, deeper insights, and new ways of delivering value across business development, execution, and client relationship management.
- The future of professional services lies in moving from siloed, service-specific solutions to an integrated, AI-native operating system that orchestrates expertise, technology, and data to deliver superior outcomes for clients.
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Evolving Expectations
In 2025, audit and consulting firms stand at the threshold of a transformative era, shaped by evolving client expectations, regulatory shifts, and economic pressures.
Audit and consulting professionals are navigating a period marked by fast-evolving demands from both clients and regulators. For auditors, the landscape is being reshaped by intensified focus on transparency, increased regulatory oversight—especially in the light of recent accounting scandals and quality concerns—and the imperative to adapt to new digital risks and technologies. Audit teams are not only ensuring compliance but are also expected to deliver strategic insights that directly impact organizational resilience and risk management.
Consultants, meanwhile, are seeing a surge in expectations for hyper-specialized expertise and the integration of advanced technologies such as AI and analytics into client solutions. As companies seek measurable value and agility in today’s unpredictable economic environment, consulting firms need to shift away from generalist advice to delivering actionable roadmaps that bridge technology, compliance, and operational needs. Sustained growth is now increasingly tied to their ability to drive innovation while driving real, operational change for clients.
There’s also the dual challenge of ongoing talent shortages in critical domains and the need for continuous investment in upskilling and technology. Economic volatility has underscored the importance of cost optimization, resilience, and long-term trust for clients and stakeholders alike.
In this environment, firms that successfully blend specialized human expertise with technology-driven insights are positioning themselves as strategic partners to their clients.
AI as a force of change
Building on these sector dynamics, the increasing complexity and volume of client expectations, regulatory mandates, and operational challenges underscore the critical role of advanced technologies.
Among these, GenAI and Agentic AI represent transformative forces with the potential to streamline workflows, enhance decision-making, and unlock new levels of insight across both audit and consulting domains.
GenAI transforms how professionals interact with information and generate insights while Agentic AI introduces a paradigm shift toward autonomous, collaborative systems capable of executing complex, multi-step processes with minimal human intervention. Together they form a cohesive and capable technological foundation.
Rewiring the Audit and Consulting Value Chain
From automating routine processes to enabling more nuanced risk assessments and strategic foresight, these technologies offer a chance to address the shared challenges auditors and consultants face.
Audit value chain.
During the business development phase, opportunity harvesting involves real-time analysis of publicly available data to identify audit prospects, such as reviewing financial statements to assess the current auditor’s tenure and uncover any noted issues. This approach broadens the pool of potential clients for audit partners. Proposal development leverages automation to draft audit proposals, streamlining the process and minimizing non-billable time for audit partners.
For engagement execution phase, initial setup includes automated drafting of audit letters, intelligent data ingestion and mapping, skill-based team assembly, and delivery of tailored knowledge insights. These measures reduce non-billable time for engagement managers, audit partners, and clients. Scope and strategy activities feature AI-driven risk assessments, audit document generation, intelligent audit plan creation, and document comparison, which enhance audit quality and resource allocation. Execution activities cover automated evidence ingestion, time tracking, AI/ML anomaly detection, and real-time engagement insights to expand audit data coverage and support audit teams. Conclusion and reporting activities utilize content and sentiment analysis of management letters, AI-generated drafts of audit observations, and audit reports to further decrease non-billable time.
In the relationship continuance phase, up-selling and cross-selling leverage client data analysis and benchmarking to identify improvement opportunities and monitor regulatory changes, enabling proactive service delivery and generating additional revenue streams for audit, tax, and advisory partners.
Consulting value chain
Marketing phase focuses on building brand awareness, attracting potential clients, and demonstrating expertise. Priorities include creating marketing collateral, establishing thought leadership, and targeting key markets. Generative AI and agentic AI use cases such as AI-driven market analysis and predictive lead scoring support these efforts, with partners and marketing managers leading the activities.
Business development phase emphasizes identifying and qualifying leads, nurturing client relationships, and winning new projects. Key priorities are lead generation, client prospecting, proposal creation, and sales strategy. Generative and agentic AI use cases, including one-click proposals and reconnecting with dormant clients, are essential, involving partners and consultants.
Engagement execution phase is dedicated to delivering quality consulting services, meeting client needs, and achieving project goals. The focus is on project scoping, resource allocation, project management, and client communication. Intelligent project management and predictive resource allocation, powered by generative and agentic AI, are key use cases, with engagement managers and consultants as primary personas.
Post engagement service phase ensures ongoing client satisfaction, gathers feedback, and strengthens long-term relationships. Priorities include analysing client feedback, managing relationships, identifying upselling opportunities, and generating referrals. Generative and agentic AI use cases like sentiment analysis, automated report generation, and data synthesis are typically managed by engagement managers.
Knowledge/value creation phase involves capturing insights, documenting best practices, and promoting continuous learning. Priorities include knowledge management, recording lessons learned, developing intellectual capital, and supporting training programs. Generative and agentic AI use cases, such as cognitive knowledge management, auto-case generation post-engagement, and leveraging knowledge for innovative consulting services, are managed by knowledge management specialists.
From stitching solutions to orchestrating outcomes.
While audit and consulting use cases differ in their specific applications and areas of emphasis, they share common capabilities that can benefit the entire each other. To enhance efficiency and scalability, we need to transition from isolated, service line-specific solutions to a unified, AI-native operating system—an integrated, adaptive architecture designed to deliver seamless and scalable results in an AI-driven environment.
The operating system consists of the following key components: -
Domain and business ontology: Establishes a shared semantic framework that standardizes concepts, rules, and relationships across the organization—ensuring consistent understanding and collaboration between human experts and AI agents.
Agent marketplace: Comprises a diverse set of AI agents categorized by scope and reusability:
- Capability agents: Generalized agents providing reusable functions across value chains, such as contract term extraction or data normalization.
- Domain agents: Specialized agents focused on specific audit or consulting domains, for instance, risk analysis or financial modelling.
- Niche agents: Tailored, often client- or industry-specific agents with focused functionality and limited reusability but high relevance, designed for particular customer needs or regulatory environments.
GenAI model repository: Central repository of open source, commercial, and proprietary Large Language Models and Small Language Models to execute specific tasks and use cases.
Model context protocol servers: Secure gateway that standardises how AI agents access and interact with external systems, tools, and real time data. E.g. real time query of client’s financial records, market and competitive analysis.
Agentic workflows: Use case-specific orchestrations that combine multiple AI capabilities to deliver complete business outcomes—from end-to-end audit procedures to comprehensive strategic analyses
The operating system envelops the core enterprise IT and operational technology (audit platforms, consulting platforms, analytics tools, knowledge platform et al) used by auditors and consultants. It powers the experience gateway – auditor and consultant workbench, dashboards, and customer portals – to enable a new way of interacting and delivering outcomes in the AI age.
Succeeding in the AI Age
The convergence of GenAI and Agentic AI presents unprecedented opportunities for audit and consulting firms to transform their service delivery models, enhance client value, and secure sustainable competitive advantages.
Realizing this potential requires moving beyond fragmented technology solutions towards a comprehensive AI-native operating system that orchestrates diverse capabilities within unified, scalable architectures.
Firms that successfully implement these systems will be positioned to:
- Deliver superior audit quality through continuous monitoring and advanced analytics.
- Provide strategic consulting insights based on real-time data synthesis and scenario modelling.
- Scale professional expertise through intelligent automation and knowledge management.
- Adapt rapidly to changing client needs, regulatory requirements, and market conditions.
The path forward demands significant investment in technology infrastructure, talent development, and organizational transformation. However, the firms that make these investments thoughtfully and systematically will establish commanding positions in the evolving professional services landscape.
The question is not whether AI will transform audit and consulting, but which firms will lead this transformation, and which will be forced to follow. The AI-native operating system architecture presented in this whitepaper provides a roadmap for firms committed to leadership in the AI-driven future of professional services.
We envision a future where we can help auditors and consultants operate at the ‘top-of-their-license’. To do that, there is a need to pivot and rethink the way firms work.