Bookings Defined - Contracts that have been agreed to that will be performed at a later date. A rise in bookings generally signals strong forward looking demand and rising revenue expectations. A decline in bookings indicates weak forward looking demand and decreased revenue expectations.
Accenture's recent earnings release shocked the consulting industry. The company's profits and revenues were up. However, investors focused on slower bookings, softer demand signals, and reduced growth expectations. New bookings declined to $19.3 billion in the quarter. In the prior quarter, Accenture reported record bookings of $22.1 billion. Accenture attributed the 3B decrease in bookings to a variety of factors. However, the most important one for our audience is that consultants need to move from traditional consulting models that provided reports full of recommendations to productized consulting models that leverage AI to produce consistent and predictable outcomes tied to enterprise value.
Consulting firms have generally operated under a standard economic model for decades. Consultants sell expertise and expertise is delivered through people. Revenue growth requires hiring more professionals, increasing utilization, raising hourly rates, or acquiring additional firms. This model was profitable as long as the work was coming in. However it also contains structural limitations based on time that becomes obvious as artificial intelligence improves.
The first limitation is scalability. Traditional consulting firms require more labor to generate more revenue. Firms with efficient processes are still heavily dependent upon human delivery. As demand increases, firms must recruit, train, manage, and retain larger teams. Growth is limited by the firms ability to attract talent and there is less talent available.
The second limitation is consistency. Client experiences can vary significantly because delivery depends upon the talents of the consultant providing the services with inconsistent methodologies. The larger the organization becomes, the more difficult it becomes to maintain consistency.
The third limitation is speed. Traditional consulting projects require extensive discovery, analysis, meetings, interviews, data gathering, report creation, and presentation cycles. Clients wait weeks or months before receiving recommendations with no expectation that the consultant will aid the client with the execution of the recommendations. While thoroughness remains important, business leaders want insights at technological speed rather than human speed.
The fourth limitation is economics. Most consulting firms still monetize effort and clients purchase hours, projects, retainers, or teams. AI is now capable of performing about 80% of the analysis, research, reporting, and workflow execution for a client project. Buyers know this and they are expecting to share in the cost savings.
This is where AI productized service models become significant. A productized service model converts knowledge into systems. Customization is limited because firms use repeatable frameworks, standardized methodologies, AI-assisted workflows, decision engines, and structured implementation processes. Technology performs much of the analysis, monitoring, reporting, and execution support. Humans should provide the review of the client deliverable. This does not mean Partners and Managers should stop reviewing the work.
Productization is a stronger business model.
Instead of scaling by adding more headcount, firms can scale via systems that allow their team to handle more clients and engagements. Delivering recommendations and reviewing progress quarterly via humans is giving way to systems that monitor conditions continuously so that decisions can be made in real time. The manual production of reports after extensive manual effort can now be done in minutes.
Most importantly, clients want productized service models. They are less interested in purchasing hours and more interested in purchasing outcomes. They want faster answers. They want greater consistency.
They want measurable results. They want continuous guidance rather than periodic consulting projects. They want systems that help them implement recommendations rather than reports that sit on a shelf. This does not mean consulting is disappearing. It means consulting is changing.
The winners of the next decade will combine human expertise, AI-powered analysis, and productized delivery models into a new form of advisory business. The advisor remains essential. The difference is that technology increasingly becomes the delivery engine.
Accenture's bookings will probably be the bell weather of consulting demand going forward. My expectation is that there will be a steady decline in revenues using traditional consulting models and that we will see this reflected in further reduced bookings at the end of next quarter.
Firms that continue selling labor alone will see their revenues significantly decline year over year because they cannot provide enough value to overcome competitors that are utilizing AI enabled productized systems.