Module 1.1 established how AI arrived at its current capability and why the transformer architecture made the current generation of tools possible. Module 1.2 developed what large language models actually are as systems and how they fit within the broader four-layer stack of AI technology. Both modules worked at the level of general technology. This module works at the level of professional practice. The question it answers is where these systems actually show up in the work of the domains this programme covers, what they do well in each domain, and what their limits are when the work gets specific.
The question matters because general statements about AI's capabilities are less useful to a practitioner than specific statements about AI's capabilities for the particular work that practitioner does. A consultant wants to know what AI changes about the work of consulting. A lawyer wants to know what AI changes about legal practice. A real estate professional wants to know what AI changes about valuation, marketing, or transaction coordination. The answer varies across domains because the underlying work varies. The technology is the same in all cases. The applications are substantially different.
This module covers six main professional domains (consulting, legal, insurance, finance, commercial real estate, and residential real estate) and two auxiliary domains (marketing and business operations). Each domain gets a treatment covering what the professional work fundamentally involves, where AI currently adds substantive value, how the AI is being used at the mechanism level, and where the applications fall short. The treatment is written at a level of generality that should remain accurate as specific products come and go, because the underlying capabilities of the technology have stabilised even as the specific tools continue to evolve. A practitioner who understands the general pattern for their domain can evaluate any specific tool against that pattern and form accurate expectations about what the tool can do.
The module closes with a treatment of human-AI collaboration as a general framework, because the patterns that emerge across the eight domain surveys have common features that are easier to see when they have been surveyed than when they are treated abstractly. A three-level framework (assisted work, augmented work, and autonomous systems) captures the range of ways AI and humans currently work together in professional practice, and the closing section develops this framework with examples drawn from the surveys that precede it.
One note before the surveys begin. The applications discussed in each domain section are those where AI currently adds substantive value in ways that are established enough to be described with confidence. The field moves quickly, and new applications continue to emerge. The intent is to provide a working map of current use that will remain useful as the field develops, rather than a comprehensive catalogue of every possible AI application. Where specific product names appear, they serve as examples of a general category of tool rather than endorsements or claims about specific adoption.