In a Reddit conversation, a user talked about how their attempts to automate workflow resulted in more complex, broken processes. They asked a question, ‘At
The majority of the enterprises already collect vast amounts of operational data, yet still struggle to answer three significant questions: Why does work slow down?
Global supply chains are facing constant disruption, from volatile freight rates to unpredictable demand and fragmented visibility. In fact, according to Gartner, despite modern ERP
A failed AI automation implementation rarely fails loudly. It fails quietly through stalled pilots, brittle workflows, and systems that technically work but never change how
Enterprise AI adoption is rising rapidly, but success rates aren’t. A study by S&P Global finds that 42% of companies scrap their AI initiatives, and
A Reddit chat on automation failures had people discussing how enterprises automate everything and anything, while leaving the bottlenecks untouched. Automation has moved from an
88% of enterprises reported using AI in at least one business function, but no more than 10% report scaling it, finds McKinsey’s The State of
Enterprises are investing heavily in artificial intelligence, but most struggle not with the models themselves, but with embedding AI into real systems and workflows where
AI has fully captured the enterprise arena, but so have the risks that come with scaling it. Adoption is accelerating across every major industry. The
Last-mile delivery has quietly become the most expensive and least controllable part of modern logistics, representing up to half of total delivery costs. Traditional last-mile
Loan approvals that once stretched across weeks are now completed within hours. Customer support teams handle significantly higher case volumes without expanding headcount. During major
Forrester’s 2026 technology and security predictions say that ‘AI will face a reckoning next year.’ Today, fewer than 1/3rd of the decision-makers can tie the