By continuing to focus primarily on productivity and efficiency gains, companies are missing out on AI’s full transformative potential, according to a recent report.
The bottom line: Using AI primarily for task-level automation and related efficiency gains limits its true potential for business transformation. Instead, companies should take an AI-centric approach to all workflows enterprise-wide.
Focus on productivity over ROI: 41% of the companies surveyed measure productivity improvements, while 41% measure efficiency. And conversely, only 32% tie AI outcomes to profits or revenue.
- Internal productivity gains remain marginal, not material: a company may save several thousand employee hours by using AI, but increased computing costs may offset or outweigh such savings. By focusing on task automation, companies are simply adding AI tool and computing costs without removing significant work from the system, leading to "trapped work."
- Only between 5% and 15% of organizations currently have an effective AI strategy that goes beyond efficiency gains.
Experts recommend taking an AI-centric approach to all workflows, and redesign processes to remove unnecessary and repetitive human work as much as possible. This still allows people to stay involved where judgement and oversight are needed.
The report suggests leaders focus on four key areas:
- Define clear business outcomes and success metrics for AI initiatives.
- Identify specific AI use cases tied to those business outcomes.
- Establish a structure to plan, test, and deploy AI applications.
- Scale AI applications with cloud computing, frontier models (i.e., Anthropic’s Claude, Google’s Gemini, Open AI’s ChatGPT, Meta’s Llama, xAI's Grok) and work with embedded agents.
