AI promises growth

Transforming AI Awareness into Strategic Action: A CIO’s Guide

AI promises growth, yet many programs struggle to turn goals into results. In manufacturing, AI matters because customers expect shorter lead times and higher quality, plants need automation to unlock capacity, and regulators require stronger traceability. Among AI capabilities, computer vision is production-ready today for inspection, safety, and throughput. The opportunity is real, but when budgets are limited, value must be demonstrated on the line first.

Organizations can invest in a top-tier platform, but workforce adoption depends on enablement, workflow fit, and trust. In a 2024 Gartner survey, 87% of employees needed ongoing training and 60% had not used GenAI for critical work; top adoption blockers included limited GenAI training (30%) and poor-quality GenAI responses (29%).

This post covers why AI matters for enterprise growth in 2025, the real adoption challenges, a clear build-or-buy path, and four strategies to deliver measurable results.

What is an AI strategy?

An AI strategy is the cornerstone of effectively integrating AI into a business. It acts as a roadmap, guiding you on how to leverage AI to achieve specific business goals. Whether it’s extracting deeper insights from data, enhancing operational efficiency, or building better customer experiences, your AI strategy defines the how and why of achieving success with AI.

This plan also encompasses crucial considerations such as:

Tech infrastructure: Ensuring companies have the hardware, software, and resources needed for AI implementation.

Adaptability: Remaining flexible to embrace evolving technologies and industry shifts.

Ethical responsibility: Addressing concerns like bias, transparency, and regulations for responsible AI use.

BY:- Nirosha Gupta;)