Realizing the Value of AI

ReadFun Yet InformativeIndustry InsightsStats & Trends

Jul 13

Even my 22-month-old daughter understands the frustration of trying to grasp something valuable, only to see it slip away at the last moment. Recently, I watched her struggle with a drinking fountain. Eagerly, she pushed the button to release the water, but as she moved to drink, she let go, watching the water disappear before she could enjoy it. Eventually, she resorted to a short-sighted solution, scooping water from the basin with her hand.

This scene perfectly explains how many companies approach artificial intelligence (AI). Eager to tap into the vast potential AI promises, they push forward with investment and enthusiasm. Yet, as they try to capture its value, they find themselves unprepared for the sustained effort required to truly benefit, often settling for superficial, less effective solutions.

According to Gartner, 49% of companies claim their top struggle to implement AI techniques is estimating and demonstrating AI value.

Here's why companies are struggling with AI:

Lack of strategy: Many organizations jump into AI without a clear strategy or understanding of how it fits into their broader business objectives. Like pressing the button without knowing how to drink the water, they activate AI initiatives without a plan for capturing the value. Before diving in, ensure there's a clear understanding of what you want to achieve with AI and how it aligns with your business goals. This strategy should encompass not just technology adoption, but also how AI will enhance customer experiences, streamline operations, and drive innovation.
Talent and skills gap: Just as my daughter couldn't quite coordinate the timing between pressing the button and drinking, companies often find they lack the necessary skills and talent to implement and leverage AI effectively. Building or upskilling your team to be proficient in AI is crucial. This includes not only data scientists and AI specialists but also project managers and business analysts who understand how to apply AI in a business context.
Short-term thinking: Faced with the immediate challenge, it's tempting to choose quick fixes over developing a sustainable approach. This is akin to settling for scooping up the remnants of water, rather than learning how to drink directly from the stream. Rather than looking for quick wins, focus on how AI can be integrated into your operations for long-term value. This means investing in the right infrastructure, ensuring data quality, and fostering a culture of continuous learning and adaptation.