AI & Automation

A Bundesbank BOP-F survey of more than 7,000 firms found generative AI use rising from 26% in 2024 to an expected 56% in 2026. In manufacturing, though, the share of working time involving GenAI remains low: 7.5% in 2024, expected to reach 8.9% by 2026. That gap explains the real state of generative AI in […]

AI in ERP is projected to reach USD 46.5 billion by 2033, but the useful question is smaller: what can an AI ERP bot safely do inside a real finance, procurement, inventory, or operations workflow? For CIOs, ERP leaders, operations teams, and product teams building AI-assisted workflows, the answer is not “let the bot run […]

Most teams do not need to build a new AI model from scratch. They need to build a reliable AI system around the right model, the right data, and the right workflow. That distinction matters because the cost, risk, and timeline change completely depending on what “building an AI model” means in your case. This […]

The AI in 5G networks market is estimated at $3.66 billion in 2025 and $14.88 billion by 2030, according to The Business Research Company and ResearchAndMarkets. That growth is real, but it hides a harder truth for product teams: AI 5G is not a magic layer that makes every connected product instant, autonomous, or easier […]

95% of B2B marketers now use AI-powered applications, according to the Content Marketing Institute. That makes the pros and cons of AI in marketing less of a future debate and more of an operating decision for marketing leaders, growth teams, publishers, ecommerce teams, and agencies. AI can help teams produce more, test faster, personalize better, […]

Deloitte’s 2024 outsourcing survey found that more than 70% of organizations now outsource critical technology functions. AI is part of that shift, but offshore AI developers are not a simple way to buy cheaper code. They can help product, engineering, and operations teams move faster, especially when the work is well scoped. They can also […]

Generative AI business adoption is real, but the results are uneven. Many teams have tried ChatGPT, copilots, content tools, or internal assistants. Far fewer have turned those experiments into production systems that save money, improve decisions, or change how work gets done. This article is for leaders, operators, consultants, and product teams deciding where generative […]

Most generative AI for manufacturing pilots do not fail because the model is too weak. They fail because the answer is not tied to the right SOP, the tool sits outside daily work, or nobody defined what success should look like before the demo. For plant leaders, engineering teams, IT/OT groups, and operations executives, the […]

AI TRiSM matters most after an AI system starts touching real customers, sensitive data, internal workflows, or business decisions. The demo may work. The model may answer well in testing. The risk begins when people use it in ways your team did not predict. AI TRiSM stands for AI Trust, Risk, and Security Management. Gartner […]