How AI increase the productivity of your team?

According to recent research, the use of AI can increase team productivity by up to 40%. Does this sound too good to be true? Well, it’s a reality. Modern AI systems like GPT-4 can assist employees in various tasks, spanning from fostering creativity and analyzing data to generating text. Do you want to find out how much AI can boost productivity and what benefits it can bring to your team? Read on to find out more.

How much does using AI increase the productivity of your team? - table of contents

How does AI assist professionals?

Is there any evidence that using AI during work increases productivity? Indeed! The largest study confirming this hypothesis was conducted by a group of scientists from American business schools, including Harvard Business School and MIT Sloan School of Management. Researchers examined the work of 758 consultants, representing about 7% of all consultants employed at the Boston Consulting Group.

Their task was to develop concepts for new products, taking into account aspects such as:

creativity,
analytical thinking, or
persuasive skills.

As part of an experiment testing whether AI increases productivity, they compared their performance without AI support and with the use of GPT-4, the language model on which the latest version of ChatGPT Plus is based. The study aimed to examine how incorporating AI into daily work would alter the typical workflow of consultants.

Source: DALL·E 3, prompt: Marta M. Kania (https://www.linkedin.com/in/martamatyldakania/)

Does AI increase work productivity?

The results at BCG were surprisingly clear. All consultants with AI support improved the quality of their work. In fact, its quality increased up to 40%. But how was the study conducted?

In the experiment, participants were randomly divided into three groups:

a control group — its members didn’t use AI at work,
a group with access to GPT-4 – however, without prior instruction on how best to use artificial intelligence,
a group with access to GPT-4 and instructional materials.

The study was divided into three phases:

First, the consultants filled out a survey regarding their demographic data and predispositions.
Then, they proceeded to the main part, where they performed tasks related to developing product concepts. These tasks closely resembled their daily work, involving realistic case studies, such as creating shoes for narrow target groups and athletes. The tasks required creativity, analytical thinking, as well as writing persuasive texts.
The third phase involved interviews summarizing the consultants’ experiences with working with AI.

As it turned out, consultants using GPT-4 were 12.5% more productive and 25% faster. The greatest benefits were observed among less-skilled professionals who received additional training on effective ways to use GPT. In this group, researchers noted a remarkable 43% increase in productivity!

Ways of collaborating with artificial intelligence

Did all employees interact with AI in the same way? It appeared not. So the researchers decided to identify two most common ways in which AI increases productivity. They called them “Cyborg” and “Centaur” personas.

Cyborg

The Cyborg model represents a collaborative approach where humans and AI work closely together to achieve tasks. Examples of Cyborg collaboration include:

a programmer starts coding, and AI complements and refines the code, just like when using Github Copilot,
a consultant begins drawing conclusions from analysis, and AI contributes additional data and visualizations, leveraging tools like ChatGPT Plus,
a copywriter starts crafting an advertising text from a concept, and AI suggests ideas and ready-made segments. The copywriter then refines the concept,
an engineer sketches a project, and AI produces a visualization based on it.

In the Cyborg model, the key is the seamless integration of human and machine efforts to achieve optimal results—this is how AI significantly boosts productivity.

Source: HuggingFace (https://huggingface.co/spaces/hysts/ControlNet-v1-1)

Centaur

The Centaur model involves task delegation, where some tasks are performed by humans, and others are delegated to AI based on an individual assessment of each entity’s strengths and weaknesses. Examples of Centaur strategies include:

AI diagnosing, and the doctor tailoring possible therapies,
a consultant identifying a business problem, and AI generating analyses and recommendations,
a lawyer drafting a legal complaint, and AI verifying the correctness and completeness of the document,
a copywriter creating a text outline, and AI making stylistic and grammatical corrections.

The key is strategically dividing tasks and leveraging the strengths of both humans and machines. However, the Centaur approach presents a challenge: how to distinguish tasks better suited for AI, enhancing productivity, from those better handled by humans?

Fragmented boundaries of technology

Researchers have labeled the challenge of defining the “competence” of artificial intelligence as the “fragmented boundaries of technology.” This term pertains to the diverse and fluctuating capabilities of artificial intelligence.

The capabilities of AI are advancing rapidly, often in unexpected ways. That’s why tasks that may appear similarly challenging for humans can fall on different sides of this “boundary” – some may be easily solvable with the help of AI, while others remain beyond the current reach of its capabilities.

For example, as the study showed, GPT easily:

generated creative ideas for new products,
helped write persuasive copy, or
performed detailed data analysis.

On the other hand, it made mistakes in simple mathematical calculations. This “fragmented boundary” poses a challenge for both AI designers and users – it is difficult to predict which seemingly similar tasks will be easy or difficult for algorithms. It is therefore crucial to explore and test the capabilities of AI step by step. The better we understand the “fragmented boundaries” of these capabilities, the more effectively we can integrate the work of humans and machines.

Source: DALL·E 3, prompt: Marta M. Kania (https://www.linkedin.com/in/martamatyldakania/)

How to increase productivity in your company with AI?

In your company, you can conduct a similar experiment to assess how much artificial intelligence can improve work outcomes. It’s worthwhile to start by assigning tasks to employees, such as preparing presentations, reports, business proposals, or solving case studies, both with and without the assistance of AI. This will allow you to measure the real impact on productivity and work quality.

Nevertheless, it is essential to adequately prepare employees. To observe a 40% increase in productivity with AI, similar to the success seen at Boston Consulting Group, training initiatives and the creation of instructional materials will be required.

The effort is almost certainly going to pay off. For example, advertising agencies can generate campaign ideas more quickly, banks can analyze customer data more efficiently, and legal firms can create documents more effectively. Everywhere creativity, information analysis, or text writing is needed—AI will help employees be more productive.

The future of working with AI

The development of artificial intelligence arouses both great hopes and concerns, especially among individuals who have difficulties learning new tools and adapting their work methods to the changing possibilities of technology.

There is no doubt that AI increases productivity by relieving teams from the simplest and repetitive tasks. More and more of these tasks will be automatable. New roles combining human and machine skills will also emerge, such as AI trainers or knowledge brokers. Continuous skill development and learning effective collaboration with AI will be essential.

At the same time, it is crucial to be aware of the threats. Automation may take away jobs from less skilled individuals. There is also a risk of the company becoming overly dependent on technology providers. Therefore, maintaining a healthy distance and critically assessing the information provided by AI is key.

The future of working with AI appears fascinating but also somewhat unsettling, much like in well-written science fiction. On the one hand, there are incredible possibilities, but on the other hand, do we truly have control over everything?

Summary

The results of the experiment show that AI increases productivity today. For some creative and analytical tasks, it speeds up work by up to 40%. Lower-skilled workers benefit the most, but top professionals are also faster and more efficient.

It is critical to understand which tasks can be automated by AI and which require human involvement. Changes in the way work is organized will also be needed to make the most of AI’s capabilities. And the future of work promises to be interesting – it certainly won’t be boring. If you’re curious for an even more detailed description of this study, read the full report (link).

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Author: Robert Whitney
JavaScript expert and instructor who coaches IT departments. His main goal is to up-level team productivity by teaching others how to effectively cooperate while coding.
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