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
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
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
Enterprises know what AI can do, but few have the in-house talent to build it. Deloitte’s 2025 State of Generative AI in Enterprise study found
Enterprise AI adoption is accelerating, but strategic clarity is not. According to MIT’s 2026 enterprise study published in Fortune, 95% of generative AI pilots fail
Most supply chain failures don’t happen in the warehouse. They start in the forecast. When demand predictions are off, everything downstream suffers: production misfires, inventory
Enterprises are investing heavily in AI, yet leadership teams keep facing the same questions: Which use cases matter? Is our data ready? What should we
Addepto has earned recognition as a data science and AI consulting firm, turning raw data into working AI-led proof-of-concepts for its clients. Yet, when enterprises
AI adoption is booming, but scaling it remains a steep climb. Research shows that only around 10% of AI projects ever move beyond pilot stages.
AI use continues to expand across industries, bringing faster decisions, smarter operations, and meaningful business gains. Without strong accountability, however, organizations face higher exposure to
Over 75% of companies now use Artificial Intelligence (AI) in at least one business function, transforming how entire industries operate. In logistics, AI powers real-time