AI for Professional Services
A margin-protection guide for firms selling expertise: how to redesign research, delivery, pricing, knowledge management, and client communication before AI compresses the billable hour.
EUR 97
Price
Online
Format
65+ pages
Pages
Billable-hour exposure map
Value-based pricing shift
AI-native delivery model
Who It Is For
Built for people making business decisions.
Consultancies, law firms, agencies, accounting practices, advisory teams, and partners responsible for protecting revenue while modernizing delivery
Use the book as an operating manual for planning AI automation, selecting the right workflows, governing risk, measuring ROI, and moving from isolated pilots to a managed automation portfolio.
Business Outcomes
Identify which revenue lines AI will commoditize first
Design AI-enabled services clients will still pay premium fees for
Move from hours sold to outcomes, judgment, and proprietary process
Reader Signal
Built for operators who need more than AI hype.
The book is positioned for executives and implementation teams who need a practical path from pilot activity to managed automation capability.
"
The useful part is the operating model. It does not sell AI as a tool purchase; it shows how to make ownership, governance, and ROI clear enough for leadership to act.
COO, mid-market services firm
"
The value map and stage-gate model make the book practical. It gives teams a way to decide what should be automated first and what should be killed before it wastes budget.
Transformation lead, B2B operations
"
This reads like a field manual for executives. The strongest sections are governance, operations, and measurement because they address what usually breaks after the demo.
CIO advisor, enterprise AI programs
Inside the Website Reader
Chapter preview.
The Expertise Compression Problem
Connects the chapter topic to industry-specific workflows, risk, metrics, and implementation decisions.
Where the Billable Hour Breaks
Connects the chapter topic to industry-specific workflows, risk, metrics, and implementation decisions.
AI Research and Briefing Workflows
Explains how to move from a business process to a working AI-enabled system with clear inputs, owners, and outputs.
Proposal, Scope, and Pricing Reinvention
Connects the chapter topic to industry-specific workflows, risk, metrics, and implementation decisions.
Client Delivery With AI Support
Connects the chapter topic to industry-specific workflows, risk, metrics, and implementation decisions.
Knowledge Bases and Firm Memory
Shows how business knowledge, retrieval, source quality, and context design determine whether AI output can be trusted.
Quality Control and Partner Review
Connects AI to physical operations: downtime, throughput, defects, planning, suppliers, and facility readiness.
Junior Talent, Training, and Leverage
Shows how business knowledge, retrieval, source quality, and context design determine whether AI output can be trusted.
AI-Native Service Packages
Describes what changes when AI becomes part of the operating model instead of a side project.
Protecting Trust, Confidentiality, and Judgment
Connects the chapter topic to industry-specific workflows, risk, metrics, and implementation decisions.
The 90-Day Professional Services Rollout
Connects the chapter topic to industry-specific workflows, risk, metrics, and implementation decisions.
From Service Firm to Intelligence Firm
Connects the chapter topic to industry-specific workflows, risk, metrics, and implementation decisions.
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