Software is eating the world as Netscape's and famous Silicon Valley venture capitalist Marc Andreessen stated in the Wall Street Journal in 2011. As per the recent Gartner software demand and market share report in April 2023, this fact remains. In other words, demand is outstripping supply. Therefore software is expensive, especially software that enables disruptive competition or runs major value-chain functions. More often than not, this involves large ERP (Enterprise Resource Planning) software packages. The industry has over 40 years of less than stellar results from attempting this form of large-scale reuse and perceived accelerator. Look no further than the numerous attempts to replace legacy Cobol/CICS applications with the likes of SAP, IBM Sterling, Oracle XXM, SAP/Hana, SaS, Charles River, etc.. It is clear that the current strategy for improving supply-side economics has failed.
At the center of the long list of train-wreck programs, often mission critical and highly visible when they fail is the COTS acquisition paradigm. "Commercial-Off-The-Shelf" software engineering has a long and notorious past. Not without ample investment in research from the likes of the Software Engineering Institute at Carnegie Mellon University, approaches like the "Evolutionary Process for Integrating COTS - EPIC" were attempted at massive scale and complexity. Similarly, government, the largest practitioner of COTS-based Software Engineering invented "GOTS - Government Off-The-Shelf" which attempted to mitigate the rigidity of the paradigm.
To achieve the promise of large-order reuse in a repeatable and effective manner requires a new paradigm. Introducing AI-OTS - Artificial Intelligence Off-The-Shelf Software engineering. While AI-OTS looks similar to the COTS evolutionary integration strategies of the past, the high degree of generative capabilities and automation yield a far more efficient and effective approach to improve supply-side dynamics. Rather than try to force-fit a rigid set of blueprints and associated realization on a business, the flexibility of being able to automatically generate a custom-fitted set of Use Cases for an enterprise is now available with the advent of Generative AI. Such a fit-for-purpose strategy reflects the reality of the complexity and dynamism of the current competitive landscape. The myth of "can't we just go out and adopt a package" was never a viable strategy even if it sounded very enticing.
AI - OTS Software Engineering enables two macro trends to take hold in the industry. The first is agnosticism, or as McKinsey calls it "Vendor Switching". Incumbent vendors within enterprises will face increased competition with generic versions of problem-space software which yield lower total-cost-of-ownership (TCO) coupled with lower switching costs. The second is re-patriation, with such cheaper generic versions of software enabling enterprises to bring their software investments back in-house, effectively shifting the scale from buy to build.
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