Additional information
by M. Sheets (Author)
Corporate software rarely fails in dramatic ways. Most of the time it works just well enough to ship the quarter while quietly draining momentum day after day. Permissions do not match how people actually work. Dashboards begin to replace judgment. Approval chains multiply. Tools meant to simplify work slowly become another layer of work. Teams adapt with rituals, workarounds, and shadow processes that keep things moving while quietly charging an invisible tax on attention.
Now AI is entering that same environment.
The promise is enormous. AI can summarize work, automate tasks, and surface insights that once took entire teams. But inside large organizations it often collides with the same structures that slowed the last generation of software. Governance, procurement, security reviews, identity systems, and tool sprawl shape how AI is adopted just as much as the models themselves. Without careful design, AI risks becoming another layer on top of already complex systems rather than the force that simplifies them.
The Year of Corporate Software takes a clear, human look at that tension. It explores the everyday friction created by enterprise tooling and what happens when AI enters those systems. This is not a vendor pitch and it is not a teardown of technology. It is a grounded examination of how good intentions turn into bureaucracy, how incentives shape behavior, and how "standardization" can quietly shift into control. Along the way it looks at the real mechanics of how organizations buy, deploy, govern, and live inside software: ticketing systems, identity and access management, procurement workflows, collaboration platforms, internal apps, data pipelines, and the metrics that claim to measure progress.
For leaders now introducing AI into the enterprise, those mechanics matter more than the models themselves. The book connects everyday frustrations to deeper causes such as misaligned incentives, risk avoidance, unclear ownership, and the false comfort of process replacing trust. It explains why tool sprawl continues even when everyone complains about it, why temporary integrations become permanent systems, and why local optimizations can create organization wide drag. It also explores how AI can either amplify these problems or help solve them depending on how it is introduced.
Most importantly, it offers practical ways forward. How to introduce AI without creating new bureaucracy. How to design guardrails that protect data without suffocating experimentation. How to simplify workflows so automation actually removes work instead of shifting it. And how to rebuild a culture where software and AI support the people doing the work rather than quietly controlling it.
If you have ever wondered whether the friction you feel inside corporate software is just you, or whether the system itself has become unnecessarily complex, The Year of Corporate Software will feel familiar. And if you are responsible for bringing AI into that system, it offers a clearer way to understand the challenge and a practical path toward making the next generation of enterprise software actually work better than the last.
