AI Adoption in Enterprises: Why Sustainable Transformation Is a Slow Burn, Not a Moonshot

AI adoption in enterprises is often misrepresented. Headlines celebrate exponential breakthroughs and flashy pilots, yet most organisations experience something different: a slow, steady burn.

McKinsey research shows nearly 80% of companies have deployed generative AI, but few report material earnings impact. The reality is more incremental. AI scales not through moonshots but through methodical investments in data, training, and small-scale pilots that quietly expand.

One manufacturing client illustrates this perfectly. Starting with machine vision for quality control on a single line, the company proved ROI before expanding to ten sites. Over 12 months, throughput improved, scrap fell, and the board approved a digital twin initiative—not because of hype, but because of measurable operational results.

For executives, the lesson is clear: sustainable AI transformation is a marathon, not a moonshot. Companies that invest steadily in governance, talent, and operational metrics will be ready to scale advanced models when the hype fades—leaving behind competitors chasing headlines.