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Abstract: Economic consulting is knowledge-intensive, document-intensive and labor-intensive - almost perfectly designed for AI-enabled transformation. Yet industry-wide adoption has been measured and uneven. This article identifies unique structural barriers in the industry that may explain why the industry has not moved more aggressively and which may determine the pace and form of adoption. Understanding these barriers clarifies why a distinctive, controlled, and infrastructure-first implementation model is required.
I. Introduction
AI is widely acknowledged as a disruptive technology. Disruptive technologies can generate significant value for the adopting firm or can severely damage a business model that cannot adapt its operations, pricing, and workflows to the new reality. The effects of AI advances depend to a large extent on the suitability of AI to the workflows of the company or industry.
The consulting industry is considered a prime target for the application of AI. The industry is knowledge-intensive, document-intensive, and labor-intensive — almost perfectly designed for AI-enabled transformation.1 So much so that PwC's US leadership has signaled that partners resisting AI “have no place at the firm."2 In this paper, we focus our attention on the economic consulting industry, comprised of firms engaged in high-stakes litigation and regulatory matters consulting. Just like the broader consulting industry, economic consulting is considered an AI target due to its reliance on highly qualified and expensive labor to conduct customized, highly academic, and document-intensive analyses.
The market has not been kind to many publicly-traded economic consulting, and strategy consulting, firms. As of the time of writing, the equity shares of companies like Accenture, Huron Consulting, Charles River Associates, and others, have experienced year-to-date declines ranging from 27% to 36%, while the broader market has risen by over 8%. Many of these declines have occurred despite rising revenues and stable profits. News and analyst commentaries have repeatedly listed potential AI disruption as one of the important factors affecting investor expectations. Publications have highlighted the “efficiency trap” of increased AI productivity leading to a reduction in consulting billable hours. They also focus on the broader “potential [for AI] to automate significant portions of research, data analysis, report generation, and other analytical tasks.”3
While this paper is not about market valuations, the market and analysts seem to be discounting significantly more downside than upside potential for economic consulting firms. An important contributing factor in this regard is that economic consulting has not yet shown an industry-wide shift from labor-intensive bespoke consulting to scalable AI-enabled delivery, nor a clear AI-driven decoupling of revenue growth from headcount growth.
We think that expectations based on AI enthusiasm and benchmarks from other industries are inapplicable to economic consulting. This paper contends that the economic consulting industry faces unique structural, institutional, and economic forces that will likely result in a much slower and gradual adoption of AI.
Before turning to those forces, it is worth establishing the baseline. Economic consulting firms have publicly confirmed that AI is relevant to their core work and that they are moving forward in their adoption of it. Charles River Associates (“CRA”) describes artificial intelligence as having a “tremendous impact reshaping traditional industries” and states that its multidisciplinary experts are increasingly applying AI, machine learning, and advanced analytics techniques across litigation, investigations, intellectual property, labor and employment, regulatory compliance, and strategic advisory matters. CRA further notes that consultants leverage AI tools to summarize large datasets, identify meaningful information within lengthy materials, automate portions of investigations, and enhance analytical workflows.4 Similarly, Analysis Group’s data science experts “draw on tools from AI, machine learning, natural language processing (NLP), causal inference, statistical simulation, and data visualization,” and that by “integrating emerging technologies such as generative AI (GenAI),” the firm seeks to “drive efficiency, clarity, and strategic value” for clients.5 Cornerstone Research states that its teams “utilize AI and ML to drive automation of increasingly complex tasks and unlock new approaches for analysis,” including the use of supervised and unsupervised learning techniques in litigation and investigations.6 FTI Consulting has publicly launched “IQ.AI,” a suite of AI-driven solutions designed for legal and regulatory matters, including disputes, investigations, antitrust review, and data-breach response. The company states that IQ.AI combines generative AI technologies, proprietary workflows, and expert consulting capabilities to automate complex tasks, improve document review, summarize investigations, and support large-scale regulatory and litigation matters.7
So, the question is not whether AI will transform economic consulting. The question is why this process will likely happen much more gradually than many outside of the industry expect. Answering that question requires examining the distinctive features of both the AI technology and the economic consulting industry, and, most importantly, the interaction between them that determines the pace and form of adoption.
Endnotes
1. See, for example, Varanasi, Lakshmi. “Inside the AI Boom That's Transforming How Consultants Work at McKinsey, BCG, and Deloitte.” Business Insider, April 2025. https://www.businessinsider.com/consulting-ai-mckinsey-bcg-deloitte-pwc-kpmg-chatbots-ai-tools-2025-4.
2. “The Future of Consulting in the AI Age: Technology Is Ready, Organisations Are Not.” Consultancy.uk, April 13, 2026. https://www.consultancy.uk/news/43733/the-future-of-consulting-in-the-ai-age-technology-is-ready-organisations-are-not.
3. Trefis Team. “CRA International (CRAI).” Trefis, June 2026. https://www.trefis.com/data/companies/CRAI#businessDescription, Finsee AI. “FTI Consulting (FCN) Q1 2026 Earnings Review: Top-Line Boom Masks Underlying Margin Compression.” Finsee AI, 2026. https://finsee.ai/earnings/fcn/2026/q1/en/, Finterra. “The AI Infrastructure Pivot: Why Accenture (ACN) Just Jumped 8% and What It Means for the Future of Consulting.” Financial Content, February 2026. https://markets.financialcontent.com/stocks/article/finterra-2026-2-27-the-ai-infrastructure-pivot-why-accenture-acn-just-jumped-8-and-what-it-means-for-the-future-of-consulting#google_vignette
4. Charles River Associates. “Artificial Intelligence (AI).” Charles River Associates. https://www.crai.com/industries/technology/artificial-intelligence-ai/. See also Charles River Associates. “Advanced Analytics & Big Data.” Charles River Associates. https://www.crai.com/services/analytics/.
5. Analysis Group. “Data Science, AI & Statistical Modeling.” Analysis Group. https://www.analysisgroup.com/practices/data-science-ai-statistical-modeling/.
6. Cornerstone Research. “Artificial Intelligence and Machine Learning.” Cornerstone Research. https://www.cornerstone.com/data-science-center/expertise/ai-ml/.
7. FTI Consulting. “FTI Consulting’s Technology Segment Launches IQ.AI for Legal and Compliance.” FTI Consulting, October 8, 2024. https://www.fticonsulting.com/about/newsroom/press-releases/fti-consultings-technology-segment-launches-iqai-for-legal-and-compliance.
