An Independent Assessment of How AI Could Change Your Business
Most professional services firms are already experimenting with AI. The harder question is what it will actually do to the economics of the business.
Clients are becoming more capable. Productivity can improve without automatically improving profit. Pricing may change. Technology and control costs can appear elsewhere. Quality, regulation and professional accountability still matter. Different clients, industries and markets will move at very different speeds.
For firms operating in international networks, investment is rarely uniform. Some member firms invest heavily in technology, data and shared capabilities while others invest much less. Capability may exist somewhere in the network without being equally accessible or economically useful everywhere.
The AI Economics Review addresses one practical leadership question:
How could AI change the economics of our different businesses, and what should we do about it?
The objective is not to predict exactly what AI will be capable of in five years. It is to understand what is already changing, where the firm’s economics appear more or less exposed, and which decisions make sense despite the uncertainty.
What the Review Examines
The Review focuses on four questions.
What is changing around us?
I examine relevant clients, competitors, firms in markets that appear further ahead, regulation, emerging business models and, where relevant, developments across the wider international network.
What could this mean for our economics?
I assess the implications for demand, pricing, productivity, capacity, cost, quality, talent and new revenue opportunities.
Which parts of the business could change first?
I distinguish between what is technically possible and how quickly client behaviour is likely to change. Client size, internal capability, industry, geography, trust, regulation and switching costs all matter.
What should leadership do now?
The answer may be to invest, protect, redesign, build capability, migrate clients towards a different proposition, monitor developments or deliberately wait.
The Economic Portfolio Map
AI will not affect every part of the firm in the same way.
I therefore assess economically different combinations of Client × Service × Team, rather than treating an entire service line as one business.
The central output is an Economic Portfolio Map:
| Future attractiveness: Lower | Future attractiveness: Higher | |
|---|---|---|
| Current attractiveness: Higher | Protect, harvest or migrate | Invest and grow |
| Current attractiveness: Lower | Reduce investment or exit | Redesign, build or acquire before growing |
For each relevant portfolio, I consider its current economics, how AI could change its future attractiveness, the likely timing of that change and whether the firm has a credible right to win.
For firms inside international networks, I also consider where the required capability sits. A member firm may have access to strong network-level technology but limited influence over investment priorities, funding or deployment. Another may need to build locally because shared capability is not sufficiently accessible. What the network owns matters less than what the firm can actually use.
The purpose is not to produce a mechanical score. It is to support better allocation decisions.
The Review identifies where different economics may require a different response. It does not attempt to design the resulting operating model, governance or incentives.
What You Receive
A concise leadership assessment covering:
- the most relevant external developments
- the Economic Portfolio Map
- implications for demand, pricing, delivery, quality, talent and capability
- relevant network opportunities and constraints
- directional recommendations
- the assumptions and uncertainties leadership should monitor
The Review concludes with a Board, Executive Committee or leadership discussion. The outside-in assessment gives leadership something concrete to react to; the discussion tests that view against the internal reality and determines what the findings mean for the firm.
Outside-In by Design
You do not need to prepare a large data pack before I can start.
I use public information to build the best possible outside-in view of the firm’s likely client mix, service mix, geographic footprint, market position, delivery model, relevant competitors and, where applicable, wider network context.
That includes looking at where other member firms or the network itself appear to be investing, which capabilities are shared and where materially different approaches are emerging across countries.
These are hypotheses to be tested, not claims that the firm’s economics can be reconstructed perfectly from public information.
If greater precision is useful, you can provide internal information upfront, such as revenue by service or client group, pricing, profitability, workforce information, current technology initiatives, network capabilities or strategy material.
Start with what is publicly knowable. Add internal information where it materially improves the analysis.
How the Review Works
A typical Review takes around three to four weeks.
Agree the question → build the outside-in view → identify the relevant economic portfolios → assess how the economics could change → map the portfolios → discuss the implications
The Review can cover the whole firm at a high level or focus more deeply on a service line, client segment or strategically important part of the business.
When the Review Is Useful
The Review is most useful when leadership needs to make decisions about AI investment, service portfolios, pricing, talent or shared capabilities, but does not yet have a sufficiently integrated view of the economic consequences.
That may involve changing client behaviour, new pricing or capacity assumptions, uncertainty around talent, significant technology investment, different futures across parts of the firm, or network capabilities whose local value is unclear.
It is not a technology selection exercise or an AI roadmap. Those are different questions.
Why My Perspective Is Different
I focus specifically on the economics and institutional design of professional services.
Through my Industry Insights and Case Studies, I study how client demand, pricing, delivery, talent, quality, technology investment, ownership and institutional structures are changing across the industry, including how international networks allocate and share capabilities.
I combine that research with more than twenty years of operating model and transformation experience, including CIO responsibility in a Big Four environment.
The value is not predicting which technology will win. It is understanding how changing technology affects the economics and institutional structure of professional services, and what that means for leadership decisions.
Research Behind the Review
The Review builds on a wider body of research into how technology, economics and institutional structures are changing across professional services.
- When Expertise Becomes Metered Infrastructure: How AI Is Changing the Economics of Professional Services
- The AI Cost Stack
- The AI Capability Layer: Who Will Own the Infrastructure Behind AI-Enabled Professional Services?
- Manufacturing Judgment: How Professional Services Build Their Most Valuable Asset
- Trust Capital: Why Professional Services Manufacture Judgment but Accumulate Trust
- The Two-Speed Firm: Why Professional Services Firms Are Quietly Splitting Into Multiple Economic Systems Under One Brand
Explore the full Industry Insights library
Discuss an AI Economics Review
If your leadership team is trying to understand how AI could change the economics of your business, I would be interested to understand the context.
The first conversation is simply to determine the question, the appropriate scope and whether an independent Review would add value.
Email: henrico.dolfing@roughtrailventures.com
Mobile: +41 79 326 4763
LinkedIn: Henrico Dolfing