JustUpdateOnline.com – The era of merely testing artificial intelligence is coming to an end as companies begin to weave the technology into the very fabric of their daily operations. Rather than being a flashy add-on, AI is evolving into a foundational element that drives background processes and strategic decision-making.
According to Kelvin Cheema, the Global Chief Information Officer and Managing Director of Global Transformation & Change at Acuity Analytics, the corporate world is shifting its perspective. He suggests that for AI to provide genuine value, it must transition from a niche experiment to a systematic function that alters how work is executed and how leadership arrives at conclusions.
Moving Beyond Isolated Experiments
For many years, enterprises have treated AI as a "bolt-on" feature or a series of isolated pilots. However, Cheema argues that the real power of the technology is realized when it becomes "invisible infrastructure." In this model, AI is no longer confined to a laboratory setting but is instead deeply embedded in essential functions such as risk assessment, financial reporting, and procurement.
When AI models are integrated into daily planning and governance, the business begins to function like "enterprise as code." This means that company processes and decision-making structures become more adaptive, testable, and automated.
Identifying the Roadblocks to Success
Despite the hype, many AI initiatives fail to reach their full potential. Cheema points out that these failures are rarely due to technical limitations. Instead, they are often the result of organizational issues. Many firms attempt to find specific "use cases" for AI without first streamlining their overall workflows.
Common pitfalls include:
- Siloed Operations: Running AI projects within isolated departments without a unified strategy.
- Lack of Ownership: Failing to establish clear business accountability for AI outcomes.
- Fragmented Data: Attempting to layer advanced AI over disjointed data systems, which leads to inaccurate results and stagnant growth.
Cheema estimates that currently, fewer than five percent of global organizations are truly "future-ready," meaning they have successfully scaled AI to produce measurable business benefits.
The Power of Integration
To overcome these hurdles, a platform-centric strategy is recommended over one-off projects. Cheema emphasizes that "integration beats raw intelligence." For AI to be effective, it requires a solid, governed data foundation.
At Acuity Analytics, for instance, the strategy involved consolidating various systems into a unified cloud-based ecosystem. By integrating functions like performance management and human capital management into a single data warehouse, the company created a backbone where AI is a fundamental capability rather than a secondary feature.
Redefining Success and the Path Ahead
Measuring the success of AI shouldn’t just be about how many employees use a tool or how much money is saved initially. Instead, leaders should look at improvements in the quality of decisions, the speed of obtaining insights, and the accuracy of forecasts. Furthermore, ensuring that AI is explainable and auditable is vital for long-term maturity.
Looking toward the next few years, the competitive gap between industry leaders and laggards will likely be defined by their operating models. The focus is shifting away from who possesses the most sophisticated algorithm and toward how effectively humans and machines can collaborate within a well-governed framework. For the modern enterprise, the goal is no longer just "doing AI," but rather operating as an AI-driven organization.