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The Billable Hour is Dead; Long Live the Billable Hour — Kevin Madura + Mo Bhasin, Alix Partners
Takeaway
Professional services are being reshaped by AI compressing ingest work and enabling 100%-of-corpus analysis — but enterprise productivity needs domain partnership, not just deployment.
Summary
- Alix Partners built an internal GenAI platform — 20 engineers, 50 deployments, hundreds of users; consulting model shifting from junior-leverage to senior-leverage via AI replicating senior knowledge.
- Cites METR benchmark showing rapid takeoff in LLM-completable task length and Dwarkesh's 'AI-first firm' concept (50 CEO copies).
- Use case 1: structured-output classification (e.g. mapping companies to NAICS codes) replaces classic NLP pipelines (stemming, stop words, SVM/naive Bayes); tool calls fetch missing context.
- Engagements have three phases (ingest/normalize → analysis/hypothesis → recommendations); AI compresses phase 1 from 50%→10-20% of effort and lets you analyze 100% of contracts instead of top-20% prioritization.
- Spending paradox: 89% of CEOs say they'll deploy agentic AI but NBER/BCG/S&P show ~no productivity uplift — distinguishes employee productivity from enterprise productivity, requires deep business-partner relationships.
enterpriseconsultingstructured-outputs
Original description
If software was eating the world before, knowledge work will soon be devoured by AI. In corporate America there are thousands of hours spent on rote tasks every day by employees, consultants, and lawyers alike. But is AI really capable of replacing work in the real world yet? Productivity estimates from GenAI range from 1.5% (NBER) to 96% (☝ us! ️). In this talk we'll share war stories of where the answer is yes (and no) and how we reduced human time spent on tasks from days to minutes in high-impact situations. The path from promise to actual product, used in real world settings, from our experience, is still unmapped. Learn what we built, how we built it - with code - and how we got stakeholder buy-in to deploy it. About Kevin Madura Kevin leads technical advisory engagements and investigations in situations involving complex software, applied AI, and digital assets. As testifying expert and "translator" of technical material, he regularly interfaces with executive leadership, legal counsel, regulators, and engineers, balancing deep technical expertise with strategic clarity to drive outcomes. About Mo Bhasin Mo Bhasin is Director of AI Products at AlixPartners, where he leads development of the firm's internal genAI platform. He helped scale the platform to 50+ deployments, and grew the AI team from 2 to 20 in under a year. Over the last 15 years, he's built products as a data scientist at Google, Nest, and most recently as a startup founder at Outoftheblue.ai. He holds an engineering degree from the University of California Berkeley, and an MBA from University of Chicago Booth School of Business. Recorded at the AI Engineer World's Fair in San Francisco. Stay up to date on our upcoming events and content by joining our newsletter here: https://www.ai.engineer/newsletter Timestamps 00:00 Introduction to Alix Partners and the AI Shift 01:05 How AI is Reshaping Knowledge Work 02:19 The Future of Professional Services Models with AI 03:36 AI's Impact on the Three Phases of Engagements 05:07 Scaling Data Analysis Beyond Human Limitations 06:36 The Paradox of AI Investment and Productivity 07:22 Use Case 1: Categorization with Structured Outputs 10:34 Use Case 2: Retrieval-Augmented Generation (RAG) 12:46 Use Case 3: Structured Data Extraction from Unstructured Data 15:54 Key Requirements for Scaling GenAI Initiatives 16:48 Final Thoughts: The Future of LLMs in the Enterprise