3 Levels of AI Adoption for Professional Services
Professional services such as accounting, law, architecture, engineering, design, management consulting and custom software development are expected to experience more disruption from AI than many other areas of the economy. While generalists should be worried, specialists and those who have developed their own esthetic could create significant, sustainable value by leveraging artificial intelligence.
There are three levels of AI adoption that professional service firms can consider. The first is off-the-shelf general business processes solutions available, or soon to be available, through existing vendors. The second level of AI tools includes sector-specific tools to support core value-creating activities. Lastly, firms can develop custom in-house AI models that codify or productize existing expertise or esthetics.
Soon most of the software vendors that we use will have AI components fully baked into their products, or available as add-ons. Microsoft and Google are expected to bring their AI copilot tools for Docs and 365 out of testing and to market this November(ish). Other popular vendors like QuickBooks are making big commitments to incorporate AI into their core offerings. These new tools and features from existing providers, along with some new-to-market solutions, promise to further streamline traditional business activities like proposal writing, invoicing, hiring, and sales. One of the big AI promises is that it will free us up from mundane tasks allowing us to focus on the parts of our jobs that we enjoy, or at least creates the most value. If true, this is where most of us will see changes in our day-to-day work-life.
Professional services like architecture and app development are already big users of sector-specific AI tools. These tools seem almost magical at times, whether it’s a coding co-pilot suggesting code, or a rendering tool allowing architects to make changes to a design and have all the building components adjust accordingly in real time. There’s a wave of more narrow AI tools coming on stream that are built to serve each specific professional service sector. For professional services like law, which presently has limited software tools to do the heavy lifting, plenty of AI-enabled tools are being developed. As these AI tools evolve, they will take over more of the value-creating activities and are the primary threat to generalists.
Firms with a clearly defined specialization or esthetic have an opportunity to productize their core differentiators using an in-house trained AI model. These models can be trained on historical outputs like completed projects, and meta materials like e-mail. Often with some additional explicit training by staff, AI will be able to duplicate the specialized value-creating outputs. Examples of professional services that could build in-house models include law firms focused on cross-border IP sales, engineering firms specializing in building bridges, or architecture firms with expertise in designing biohazard labs. A clearly defined esthetic is also an opportunity to build an in-house model, although large generative AI models are proving wildly good at copying styles. Most professional service firms are generalist by nature, but many develop niche specialties and expertise that can be leveraged using AI.
In the next few years, sector-specific AI tools targeting professional services will get much better, and more prolific. Across most sectors, firms probably won’t die off en masse. People still want to work with people, and the sales/buying process for high-ticket items is usually complex. We’ll still need architects and engineers to sign off on designs for liability reasons, among others. However, as AI takes over most tasks in the value-creation process, firms will need fewer employees to get the same outcomes. Because human labour is the primary producer of value in professional services, economics dictate that some level of price deflation should be expected across most professional services. Professional services are under significant threat from artificial intelligence. Firms that can adopt AI tools while maintaining the level of service that their clients expect should survive if not thrive.
