How can generative AI transform productivity?

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The personal computer (PC) was invented in the 1980’s. However, it was not until the late 1990’s, when unit costs had dropped and PCs started being connected to the internet, that this breakthrough started having a noticeable impact on productivity figures.

As explored in this series, we believe that generative AI, like the PC, is a breakthrough technology that will transform the world. But, while most new inventions take years to gain mass adoption and have a significant impact, generative AI is already so powerful that it will start impacting employee productivity almost immediately.

Employee productivity is the average value of goods and services produced per hour of work.1 To put it another way, it’s a measure of how efficiently and effectively workers perform their tasks and achieve their goals. Employee productivity is crucial for enterprise workplace solutions (EWS) providers because it enables them to reduce costs, whilst at the same time increasing the quality of their service and improving customer satisfaction. This can translate into significant long-term competitive advantage, especially in a period of high inflation and economic stagflation.


Employee productivity is typically boosted through technological innovation. Whereas manufacturing has been made significantly more efficient by automation, it has been difficult to make the same gains for certain types of knowledge work, especially office-based roles that rely on tasks that require communication, creativity and problem solving. This in turn has limited productivity growth in these areas. There is only so much output individual workers can achieve, without getting burnt out or facing motivation issues. Companies have also traditionally found it hard to recruit skilled workers and scale-up, further impacting productivity.

This is why generative AI is so disruptive. It can effectively complete office tasks, previously thought impossible to automate, such as writing emails, formatting business presentations, understanding customer inquiries, suggesting meetings, matching with services/products available and preparing a response to customer email.

This can help increase the productivity of many knowledge workers by giving them extra capacity and reducing the time spent on non-core tasks.


A recent analysis by McKinsey claims that generative AI could increase employee productivity by up to 0.6% per year until 2040, as well as adding $2.6 trillion to $4.4 trillion in economic value to the global economy. We look at some key areas it will impact below:

Automating non-core tasks

Generative AI models, like GPT-4, are excellent tools for creating business content across a wide range of channels and formats. Using them can save knowledge workers significant time and resources, as they no longer need to create all of their content manually. It is estimated that the average employee spends eight hours and 42 minutes drafting emails each week, time that could be re-invested elsewhere.3 Indeed, a study from MIT has shown that ChatGPT could increase worker productivity by 40% for some written tasks, such as sending internal emails or writing cover letters for grant applications.

Productivity gains can be further amplified by integrating generative AI into wider processes. For example, using it to record and transcribe a meeting, summarize the key points and then automatically email the participants. Or to generate a summary of a presentation or keynote and have it automatically printed and distributed to the attendees.

man in an online meeting

Research and data analysis

Another area where generative AI can boost productivity is research and data analysis. Instead of typing a query into an online search engine, workers can ask an AI-powered chatbot instead. Due to its ability to ‘understand’ the query, make accurate inferences and learn over time, the results from the chatbot can be more relevant and informative while less time consuming than a manual search. Companies can use the technology to help employees access internal company information much quicker, especially if they have domain-specific models that can understand the context of the search as well. The McKinsey Global Institute, estimates that knowledge workers spend about a fifth of their time searching or gathering information.

SPS partners with several AI-enabled Intelligent Search companies across the legal, financial services, and insurance, as well as working directly with AI models to empower our intelligent records and business admin support teams.

Organizational tasks

Generative AI can also support planning and task management. For example, it can analyze an individual’s schedule, priorities and goals and then create personalized to-do lists, with tasks prioritized based on dependencies such as importance, available resources and time. This function can be expanded so that it organizes the tasks for an entire team, supporting a project manager. It can enhance collaboration by assigning tasks based on the availability of team members and their skill sets, as well as generating progress reports and sending reminders to ensure deadlines are met. It can also analyze outcomes against set parameters and provide feedback on how to improve quality and performance in the future, such as suggesting areas of further study or training. By improving collaboration, cutting delays and optimizing resources, generative AI can help companies be more productive, across a range of projects.

For more information on how generative AI is transforming knowledge work don’t miss our next blog post, which looks at data management and analysis.

working from the mobile phone and laptop


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