Most AI strategies are elaborate 50-slide performances designed to impress investors and boards, while the boring operational work that creates actual business value gets completely ignored. The uncomfortable reality is this: genuine success happens in operations, not in innovation theater.
Most AI tools will not exist in three years. The economics are brutal: point solutions become platform features overnight, and startups burn cash twice as fast as traditional SaaS. Here is how to spot which ones survive and avoid betting your operations on doomed solutions.
Companies waste millions choosing build or buy based on cost spreadsheets and technical capabilities. The real decision is whether your middle managers understand AI well enough to actually use whatever you build or buy. Without that understanding, both choices fail at the same rate.
Everyone is jumping between ChatGPT, Claude, Gemini, and Perplexity looking for the perfect answer, but the constant switching is killing productivity more than any single assistant ever could
When 85% of AI projects fail, the problem is not the technology. Most companies evaluate features when they should be evaluating support, infrastructure readiness, and team preparation.
Traditional maturity frameworks push companies through expensive levels that rarely predict success. After watching dozens of implementations, here is the contextual approach that actually matters.
Executives approve AI initiatives when you frame them as business leverage multipliers with clear ROI timelines and risk controls - not technology experiments
The scrappy approaches that make AI pilots successful become liabilities at enterprise scale. Here is how to build AI capabilities that work for 50 people, not just 5.
Traditional AI readiness assessments measure data quality and infrastructure while missing what actually predicts failure: workflow fragmentation. Your teams toggle between 47 different tools, switching contexts 1,200 times daily. That is where most AI projects die, not in the data architecture.