The model as a diagnostic tool
In addition to mapping out the typical trajectory for AI implementation, the maturity model can also be used as a diagnostic tool to identify where an organization can leapfrog ahead to new capabilities without passing through all intermediary points (e.g., implementing a generative AI solution without first acquiring a foundation in predictive/analytic AI). It is important to recognize that leapfrogging cannot occur at the whole-organization level.
Startups, of course, are unburdened by legacy constraints and so can build from scratch around AI capabilities. But organizations with more than a few years of history are inevitably burdened with constraints – infrastructure, culture, systems, staff skillsets – that make it impossible to skip past whole stages on the maturity curve without potentially disastrous outcomes. Successful leapfrogging instead targets specific opportunities, deploying advanced AI solutions in comparatively localized, but impactful, contexts. For instance, a company with no high-level experience of analytic/predictive AI might seek to implement a generative AI knowledge management tool in one of its units.
In this context, the maturity model becomes a tool for identifying leapfrogging opportunities and for mapping constraints. The diagnostic process works backward from a survey of possible desired outcomes.
First, identify AI solutions that will deliver the greatest business value.Second, for each solution, map the constraints that block its successful implementation. Draw a critical path from the current state to the target state, identifying either clear passage or minimal, surmountable barriers. Third, where barriers exist, determine the feasibility of unblocking the path to the solution rapidly and cost-effectively.
This granular approach reveals why leapfrogging is possible in some domains but not others. China pursued a maturity-driven path to carrier warfare capabilities because its target end state required building sets of tightly interwoven capabilities that could not be obtained independently (e.g., carrier construction, design, and maintenance all overlap and contribute to each other, and in each case, China needed to advance through at least three generations of technology, from small diesel-powered ships with a few dozen planes to nuclear-powered vessels with nearly 100 aircraft). In this case, there was no viable path direct from an initial lack of carrier knowledge to constructing and operating some of the most complex machines ever built. By contrast, the path dependencies required to move from China’s existing missile capabilities to novel antiship ballistic missiles were achievable, if not simple. This was a paradigm-shifting advance built on existing technological foundations with a comparatively small number of technical barriers to be overcome.