4 posts
95% of AI projects never escape pilot purgatory. A C-level decision guide built on BCG's 10-20-70 rule, McKinsey State of AI 2025 data, a three-layer ROI measurement model (Utilization → Productivity → Business Outcome), a use-case prioritization matrix, and two anonymized Turkish enterprise cases.
A comprehensive Turkish-enterprise-focused guide to calculating AI investment ROI in TRY with tax incentives included. Covers ROI formulas (simple ROI, NPV, payback, IRR), 4 value dimensions, hidden cost lines, 6 concrete use-case calculations, TÜBİTAK/KOSGEB incentives, SMB vs enterprise differences, and a 5-step ROI framework — for CFOs and decision-makers.
A 7-stage maturity model that structures the enterprise AI adoption journey in Turkey: definitions for each stage, scoring criteria across four dimensions (strategy, data, talent, governance), a 21-question self-assessment, and stage-transition patterns. A production-focused reference framework aligned with KVKK + EU AI Act + ISO 42001.
The most critical factor in AI agent project success is often not model choice, but use-case selection. Many organizations apply agent technology to the wrong problems simply because it is popular, leading to high expectations, low impact, architectural complexity, and poor ROI. In reality, agentic systems do not create value everywhere. In some settings they can transform operations, while in others classic workflow automation, rule engines, or standard software integrations are the better solution. This guide explains how to select realistic enterprise use cases for AI agents by examining decision complexity, tool needs, human approval, operational risk, data access, measurable business impact, and organizational readiness.