This article explores the impact generative AI will have on businesses. While most sources argue generative AI will significantly boost productivity, some suggest it might merely lead to longer and more frequent coffee breaks.

Adding a UK-Sized Economy Every Year
Bloomberg recently estimated that generative AI will contribute between $128 billion in 2024 and $219 billion in 2025 to global revenue, reaching $340 billion by 2026. These numbers highlight the explosive growth businesses can expect from integrating AI technologies. This revenue impact is just one aspect; time savings and efficiencies are also crucial. McKinsey estimated that total productivity gains could exceed $3 trillion annually, roughly the size of the UK's gross domestic product.
Global Topline Revenue Contribution by Generative AI

Source: Bloomberg, CFO Briefing, July 28th 2024. Note: 2024 to 2032 estimates.
Fragmented and Multifaceted
According to Bloomberg, Chief Financial Officers are increasingly adopting generative AI to automate routine tasks, improve financial forecasts, and enhance decision-making processes. Despite clear benefits, quantifying generative AI's exact contribution to a company's productivity remains complex. Companies like Cisco and Adobe are exploring methods to present AI-related revenue in their financial statements. However, attributing specific revenue gains directly to AI initiatives is challenging due to the multifaceted and often fragmented nature of their impact on business operations.
More Coffee and Increased Productivity
So, which is it? Will we just have more frequent coffee breaks, or will generative AI massively increase productivity? The main challenge lies in the measurement. Generative AI, like all AI, is a horizontal technology that can be applied to every function, system, and process in an organization. Emails can be written faster and more persuasively, and production quantities can be optimized to meet demand more accurately and reduce waste. While benefits from faster email writing are harder to measure, reductions in stockouts and over-production are usually more clear.
For some use cases, measuring the positive impact of generative AI is straightforward. In marketing and finance, for instance, many routine reports are generated. Measuring who creates a report and how long it takes is relatively easy.
Seven Steps to Measure Productivity Gains
Here are seven steps to measure the productivity gains of introducing generative AI to improve a business process:
Identify Specific Use Cases: Pinpoint areas within your business where generative AI can be applied. Common use cases include automating routine tasks, enhancing decision-making, optimizing production processes, and improving customer interactions.
Define Key Performance Indicators (KPIs): Establish clear KPIs to measure productivity improvements, such as time saved on tasks, reduction in errors, and increase in output quality. Also, set a financial objective, as projects with explicit financial objectives tend to perform better.
Conduct a Baseline Assessment: Measure the current performance of the identified processes without generative AI intervention. Document the time, resources, and costs associated with these processes to create a benchmark.
Pilot Testing: Start with a small-scale pilot project to assess the initial impact of generative AI on the selected processes. Collect data on the improvements observed during this phase.
Analyze Results: Compare the data collected from the pilot with the baseline assessment. Identify specific areas where productivity has increased and quantify the gains.
Iterate and Optimize: Use the insights gained from the pilot to refine the AI solutions and their implementation. Continuously seek feedback from employees and make adjustments to optimize performance.
Scale Up: Based on the success of the pilot projects and the data collected, expand the AI implementation to other areas of the business. Apply the lessons learned to ensure consistent productivity gains across the organization.
Conclusion
The value of generative AI in a business environment is becoming increasingly evident. From driving financial growth to enhancing operational efficiency, gen AI offers numerous benefits. However, the challenge of quantifying its exact contribution and the cautious stance of some CFOs highlight the need for a strategic approach to adoption of the technology. Businesses that embrace AI and integrate it effectively into their operations are likely to gain a competitive edge in the market. It is crucial for companies to explore the potential and pilot generative AI projects, positioning themselves for future success.
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