AI & Automation

Guides on AI development, AI chatbot development, workflow automation, business process automation, and building intelligent tools for founders and teams.
Technician working on server rack illustrating AI powered scalability infrastructure
by Asghar Mirzaie

AI Scalability: A Practical 2026 Guide

You will not find much generative AI work that has made it past the pilot stage. According to Stanford’s 2026 AI Index, 88 per cent of organizations are running some form of AI, but Deloitte’s enterprise survey for the same year tells a different story: only one in three leaders would claim they have actually […]

Operator reviewing a workflow diagram while planning a generative AI startup product
by Saeedreza Abbaspour

Generative AI Startups: A Practical Guide

If you are thinking of putting together a generative AI startup in 2026, there is one figure from MIT’s NANDA initiative you should have at the back of your mind: some 95% of the 300 enterprise deployments they put under the microscope had little to no discernible effect on the P&L. You will not find […]

Plant engineer reviewing tablet beside CNC machine on factory floor using generative AI in manufacturing
by Asghar Mirzaie

Generative AI in Manufacturing: A Practical Guide

MIT’s NANDA initiative found that roughly 95% of enterprise generative AI pilots deliver little to no measurable P&L impact. Most do not fail because the model is weak. They fail because the answer is not tied to the right SOP, the tool sits outside daily work, or no one defined success before the demo. That […]

AI ERP bot interface connected to finance and inventory workflow records
by Asghar Mirzaie

What Is an AI ERP Bot?

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 […]

Building an AI model through data, workflow, and evaluation planning
by Asghar Mirzaie

Building an AI Model: What Matters

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 […]

AI 5G edge setup with cameras, router, and connected device monitoring.
by Asghar Mirzaie

AI 5G: What Product Teams Should Build

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 […]

Team reviewing the pros and cons of AI in marketing workflows
by Masoud Tahsiri

Pros and Cons of AI in Marketing

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, […]

Offshore AI developers reviewing architecture, data access, and production risks
by Saeedreza Abbaspour

Offshore AI Developers: Hiring Guide

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 planning around workflow maps and implementation decisions
by Asghar Mirzaie

Generative AI Business: What Works

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 […]

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