Generative AI: The future of work and customer dialogue — A comprehensive look
At a time when digitisation is penetrating all areas of life, we are experiencing an unprecedented transformation of the working world through generative AI technologies. Research and case studies show that these intelligent systems not only optimise work processes, but also open up new opportunities for creative and empathetic ways of working. In this article, we summarise relevant studies and articles that shed light on the multi-faceted world of AI applications and discuss how they redefine efficiency, quality, and human interaction in the workplace.
The importance of generative AI for the modern working world
The relevance of generative AI in the business world is undeniable today and is underpinned by an impressive figure: An annual increase in productivity of up to 4.4 trillion US dollars could be possible as a result of its introduction (McKinsey 2023). This underlines the enormous economic potential that generative AI technologies bring. A survey of company executives showed that 96% of companies already regard generative AI as an integral part of their business agenda (Capgemini 2023). In Germany, 76% of CEOs regard generative AI as an important investment priority, a clear indication that management levels recognise the transformation potential of this technology and are prepared to provide resources for it (KPMG 2023).
Another indicator of the increasing influence of generative AI is the increasing use of synthetic content in marketing. According to forecasts, the share of synthetically generated marketing messages from large organisations will grow up to 30% by 2025 — a significant increase from less than 2% in 2022 (Gartner 2023). These figures signal a fundamental change in how companies communicate and interact, while also representing an opportunity for competitive advantage. They illustrate that the integration of AI into business strategies is not just a trend, but an essential component for future business success.
Increasing efficiency and quality through AI
The study “Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality,” conducted by Harvard Business School's Digital Data Design Institute in collaboration with Boston Consulting Group, examined the impact of artificial intelligence (AI) on performance in complex and knowledge-intensive tasks (Dell'Acqua et al. 2023). In a pre-registered experiment with 758 consultants, who made up around 7% of the company's consultants, it was shown that the use of AI led to a significant increase in productivity. The consultants completed 12.2% more tasks on average and were 25.1% faster than the control group without access to AI. In addition, the quality of the results improved by over 40%.
The concept of the “jagged technological frontier” is interesting, as it clarifies that AI handles some tasks effortlessly, while others, which may appear similarly complex, lie outside current AI capabilities. When tasks were within the limits of AI competence, consultants benefited significantly from AI support regardless of their original performance — the below-average consultants improved by 43% and the above-average by 17%. For a task that was deliberately selected outside the AI skill limit, the probability of correct solutions dropped by 19 percentage points when AI was used.
The study also reveals two patterns of successful AI use by people: Some consultants acted as “centaurs” by assigning solution creation activities to either AI or themselves, while other consultants acted like “cyborgs” by fully integrating their workflow with AI and continuously interacting with the technology. These findings not only emphasise the potential of AI to increase efficiency and quality in various task areas, but also the importance of human adaptability and strategy when using this advanced technology.
Productivity using Microsoft's co-pilot as an example
A study on Microsoft's co-pilot (Cambon et al. 2023), based on Large Language Models (LLMs), paints a clear picture of increasing efficiency through AI-based productivity tools. More than 30 studies were carried out, with the aim of evaluating the impact of Copilot on speed, quality and effort in various tasks. The resulting findings support the hypothesis that Copilot significantly increases productivity in a range of typical knowledge worker tasks. This increase is primarily reflected in a significant acceleration of task processing without significant losses in the quality of the results. The positive reaction of users is also reflected in their willingness to pay: People who used Copilot tools were more willing to pay than those who did not, which indicates added value beyond initial expectations.
Explanation: The gray bars, which are all normalized to 100%, indicate the performance of study groups that did not have access to an LLM-based productivity tool. The black bars show the percentage of time spent by participants with access to a tool compared to participants without access.
These findings emphasise the role of LLM-based tools as valuable assets to increase efficiency and quality in the modern working world while reducing the burden on employees. Copilot in particular promoted a high level of self-reported productivity and was perceived by users as less exhausting. The result was a picture in which the technology not only accelerated existing ways of working, but also opened up new ways of working that were not previously possible.
Conclusion and outlook: The new era of customer proximity through generative AI
Recent advances in artificial intelligence, particularly in the area of generative AI, have ushered in a new era for companies and their customer relationships. The ability of AI-based systems such as Microsoft's Copilot to complete specific tasks in less time and with high quality is evidence of a huge leap in work productivity. These technological achievements not only open the door for efficiency improvements, but they also have the potential to fundamentally transform customer interactions and marketing.
An initial study by Microsoft shows that it takes around 11 weeks for users to get used to working with Copilot. This underscores that technological integration requires time and patience. Nevertheless, the positive development in job satisfaction and the balance between work and private life after this familiarisation phase is a strong argument for implementing such AI tools in companies. Better work-life balance, increased job satisfaction, and more efficient meetings are just a few of the observed benefits of using Copilot.
Another key aspect that is being revolutionised by AI Companions such as Copilot is relationship marketing. AI Companions equipped with artificial empathy are able to establish and maintain long-term customer relationships. They offer added value that goes beyond purely functional support and enables a more emotional level of customer interaction. As the study from the California Management Review points out, this could promote deeper ties to brands and thus strengthen customer loyalty in the long term (Chaturvedi, Verma, and Srivastava 2024). Companies that recognise and use this development could secure competitive advantages through improved customer understanding and increased customer proximity.
The future will show how these technologies will continue to develop and what new business models and market strategies will result from them. It is to be expected that AI tools will not only be seen as tools, but as integral partners in a company's value chain. They will increasingly influence decision-making processes, from product development to customer service, and thus permanently change the way we work and consume.
