AI is making professional services faster to deliver, but it is also weakening the connection between time spent and value created. Baker McKenzie’s move away from hourly billing offers agencies, technology providers, and other service businesses an early view of what may follow.
For decades, professional services firms have relied on a straightforward commercial model: track the hours required to complete the work and bill the client accordingly. Artificial intelligence is making that approach more difficult to defend.
Baker McKenzie is moving away from hourly billing as its default, according to The Wall Street Journal. The global law firm expects to use more value-based pricing and alternative fee arrangements as AI reduces the time required for work such as contract drafting, document review, and due diligence.
Hourly billing will not disappear. Some assignments remain difficult to scope, and the firm expects to use hourly rates when another model does not fit. The larger change is that time will no longer automatically serve as the primary measure of value.
When Efficiency Reduces Revenue
The traditional model creates a conflict as AI becomes more capable. A firm may invest in technology, proprietary workflows, training, security, and quality controls, only to complete an assignment in fewer billable hours.
The client receives the result sooner, but the provider may generate less revenue for producing it. Under that model, greater efficiency can reduce the provider’s compensation even when the work becomes more valuable to the client.
That problem is not limited to law. Agencies, consultancies, accounting firms, marketing service providers, and technology implementation partners face the same tension. AI can accelerate research, campaign development, creative production, reporting, customer communication, and routine account work.
Clients are likely to expect some of those efficiencies to lower their costs. Providers still need to recover the investment required to build and govern the systems producing those savings.
From Hours Worked to Outcomes Delivered
Value-based pricing offers one answer, but it requires a different relationship between provider and client. Instead of paying for the time required to perform a task, the client pays for an agreed deliverable, business result, or defined level of service.
For an agency, that could mean pricing around qualified leads, locations activated, campaigns delivered, customer-acquisition improvements, or measurable increases in visibility. A SaaS provider might combine platform fees with implementation, optimization, or performance components rather than billing every service hour separately.
That shift makes measurement more important. A provider cannot price around value without establishing what value means, which data will be used, and which factors remain outside its control.
Local and multi-location marketing makes the issue more complicated. Campaign performance may vary by market because of local competition, franchisee execution, store operations, weather, inventory, or differences in customer demand. Agencies cannot reasonably guarantee an outcome when they control only part of the customer journey.
The likely result is not one universal pricing model. Providers may combine platform subscriptions, fixed project fees, retainers, service-level commitments, and performance incentives depending on the assignment.
AI Adoption Is Becoming a Company-Wide Effort
Baker McKenzie’s strategy extends beyond billing. The firm is reportedly incorporating AI competency into interviews and performance reviews, reflecting the expectation that employees should know how to use the technology responsibly.
Other law firms are moving in a similar direction. Latham & Watkins established a $1 million award pool for associates who develop AI tools, workflows, training, or knowledge resources that create value for clients or the firm. A&O Shearman is asking its practices to dedicate part of their time to building specialized AI systems.
These programs suggest that AI capability is becoming part of the product clients purchase, not simply an internal cost-saving tool. The differentiator may be less about access to a particular model and more about the provider’s data, workflows, industry knowledge, governance, and ability to apply AI consistently.
The Pricing Model Must Catch Up
Baker McKenzie is addressing a question that will reach well beyond the legal sector. If AI reduces the labor required to deliver professional services, providers must decide whether they are selling time, technology, expertise, outcomes, or some combination of the four.
Hourly billing remains familiar and easy to understand, but it increasingly misaligns the interests of clients and professional services providers. Value-based pricing can correct that problem, although it also demands clearer scoping, stronger measurement, and greater transparency about what the provider controls.
The immediate task is not from companies to abandon hourly billing. It is to identify where AI has already weakened the relationship between effort and value, and determine whether the pricing model still reflects what the client is actually buying.
