What happens to the risks, freed time and whether a person will be thrown out of the AI ​​link. 10 Big Trends in Generative Artificial Intelligence

On the website of the World Economic Forum, experts presented a report on the use of Generative AI to increase jobs and productivity of the GenAI workforce. Here are 10 main trends:

1. The benefits of GenAI are best suited to organizations that manage data. These organizations have a long history of building reliable data quality, infrastructure, governance and security. They don’t necessarily identify GenAI use cases faster, but when they do, they already have everything in place to deploy quickly.
2. Organizations are cautious about scaling GenAI. Some of the early adopters of GenAI are taking their time with the implementation process and trying to test solutions more in small groups before wider deployment. This helps identify problems at an early stage and prevent employees from losing interest if things don’t go according to plan.
3. Awareness of risks. Most of the organizations represented in the report are well aware of the risks associated with the adoption of GenAI in the workforce. This applies to data leakage, confidentiality and bias of results or other ethical aspects. To avoid reputational damage and conflict with regulators and authorities, many take a cautious approach, conducting experiments and piloting projects in the relatively safe environment of their organization.
4. GenAI improves productivity, but some organizations don’t know what to do with the freed up time. The report talks about productivity improvement mostly at the organizational level. However, there are examples where the company claimed that requests that once took weeks to process now take mere minutes thanks to automation. Another example of optimization of routine work thanks to AI. Speaking of which, more than a quarter of respondents said GenAI enables employees to do more enjoyable, creative and rewarding work. However, a number of surveyed organizations do not have a clear plan for what employees should do with their free time.
5. Improving the quality of work is another important factor for the deployment of GenAI. If properly implemented, this technology has the potential to be more accurate, consistent and error-free than humans, and therefore can lead to higher quality and customer satisfaction.
6. People are not always satisfied with the results of using technology. IT professionals have been among the fastest adopters of GenAI. At the same time, the greatest impact is felt in departments that do a lot of administrative work, leading to uncertainty among these teams. Trust can be built through training that demystifies technology, as well as reskilling and upskilling that gives employees the potential to grow into new roles. This will be vital in the near future, as 44% of workers' skills will be lost in the next five years, according to the Forum’s Jobs Initiative, which works to create good jobs for all in the context of such labor market disruptions.
7. GenAI cannot be implemented without change management. The report highlights the importance of understanding the impact on organizational culture and the change in mindset it requires from employees. Effective leadership from the top of an organization is vital. In addition, middle managers who understand workflows and processes are crucial, and therefore where GenAI can have the greatest impact.
8. Most organizations don’t know exactly what percentage of their workforce is using GenAI. In fact, the companies surveyed reported figures ranging from 20% to 80%. Some stated that almost everyone uses the technology, or at least could, because the entire organization gained access to GenAI tools. How accessible these tools are to the workforce depends on the company’s risk appetite—some respondents provide access to all employees, while others limit access to specific departments or require licenses.
9. Few organizations have developed a strategy for the sustainable use of AI. Compared to smaller, task-oriented AI models, large language models such as ChatGPT consume a lot of energy because each prompt requires computations that consume a significant amount of energy. While this is an issue recognized by most organizations in the report, few have yet strategized how to act on it, and environmental considerations do not appear to be central to decisions about GenAI workforce deployment.
10. Removing people from the loop is still considered an error. Most of the organizations interviewed for the report monitor the risk, quality and responsible use of GenAI through internal committees or boards that set rules and frameworks and evaluate use cases. Almost all also say they have developed training programs for responsible use of the tools. With scandals surrounding discriminatory algorithms and new laws such as the European Union’s Artificial Intelligence Act, companies are acutely aware of the importance of validation, verification and human intervention. «The biggest mistake you can make is to cut people out of your processes,» said one respondent.

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