22 Deploying Artificial Intelligence ^Top A Framework for Gauging Adoption Readiness for AI F irst mover advantages for incumbent firms are well-known, and so are their disadvantages and second-mover advantages, thus confirming incumbent inertia (reluctance to change).52 But crossing the chasm and getting the mainstream market to adopt AI solutions will require adequate planning even before investing in the technology.53 Since challenges such as security and scale discussed earlier can be magnified with large-scale operations in an incumbent’s world, how can it evaluate whether, when, and how to adopt AI? Here is a framework to indicatively gauge the firm’s readiness for adoption while evaluating an AI use case. Fundamentally, evaluating capabilities, both organizational and technologi- cal, will reveal the readiness of the organization to consider adopting AI in its business. A firm has to evaluate whether its capabilities allow it to build an AI solution or implement a solution built by someone else, or use some combination of the two to deliver a robust competitive response.54 Although the figure shows quadrants here, organizational readiness and technological readiness have to be gauged on a spectrum of low to high. 52 Rajesh K. Chandy and Gerard J. Tellis, “The Incumbent’s Curse? Incumbency, Size, and Radical Product Innovation,” Journal of Marketing 64, no. 3 (July 2000): 1-17, http://www.jstor.org/stable/3203484. Marvin B. Lieberman and David B. Montgomery, “First-mover (dis)advantages: Retrospective and link with the re- source-based view,” Strategic Management Journal 19, (1998): 1111-1125, http://marvinlieberman.com/wp-content/ uploads/2016/08/fma2-smh1998.pdf. 53 Geoffrey A. Moore, Crossing the Chasm (New York, NY: Harper Business, 1991). 54 Christine Oliver, “Sustainable Competitive Advantage: Combining Institutional and Resource-Based Views,” Strategic Management Journal 18, no. 9 (1997): 697-713, https://www.jstor.org/stable/3088134.