Ghada Ismail
Since the rise of modern technologies & AI-powered robots, there has been a scorching hot unsolved debate on the future of the world with machines replacing humans and whether we can still count on humans only, machines only, or machine-assisted humans and vice versa in our everyday lives.
Scientists and tech-savvies conducted millions of research papers and studies on the theme of “Humans vs Machines” where they displayed aspects of the competition between human beings and automated machines, particularly in the context of various tasks and activities. The comparison every day becomes more relevant with the rapid evolution in technology and artificial intelligence prevailing in almost every aspect of our lives and businesses in particular.
Almost everybody then came to one conclusion that humans excelled in areas as they have the tendency to be significantly the masters being creative, emotionally intelligent, skilled at complex problem solving, and ethical and moral decision making, while machines outperformed humans in aspects like speed, efficiency, data processing, 24/7 availability and safety in hazardous environments. This led to a logical conclusion that a combination of human capabilities and machine automation shall make the most convenient equation.
This is known as "human-machine collaboration" or "augmented intelligence," where machines and humans coexist and assist each other. Machines provide assistance to humans in tasks that align with their strengths while allowing machines to handle tasks suited to their capabilities with one main aim to create a co-dependent relationship that leverages the strength points of both humans and machines to achieve better outcomes across various domains.
Businesses & Organizations turning to integrate and invest in generative AI tools
In a detailed report issued by Capgemini Research Institute, namely “Generative AI in Organizations 2024”, we found out that most organizations are tending to maximize their use of generative AI, and there has been an increase in investment in the technology over the last year, but before we dive in the report findings, let’s explore what Generative AI is?
Generative AI, or gen AI, is a set of algorithms, that is capable of generating seemingly new, realistic content—such as text, images, or audio—from the training data. The most powerful gen AI algorithms are built on top of foundation models that are trained on a vast quantity of unlabeled data in a self-supervised way to identify underlying patterns for a wide range of tasks.
Thus, gen AI is a type of AI technology that can generate various types of content, including text, imagery, audio, and synthetic data that can be applied extensively across a wide array of business fields and become useful and versatile material serving everybody, each for his own certain purpose. The recent buzz around generative AI has been driven by how easy and smooth, assisted by these tools, can create high-quality text, graphics, and videos in a matter of seconds.
Back to Capgemini’s report, researchers found out about 80% of organizations have pumped more investment in generative AI since 2023, and 20% have kept the same investment level, whereas, 24% of organizations have integrated generative AI into some or most of their locations or functions. This represents a significant surge increase compared to only 6% reported just a year earlier.
The report extracts data from a global survey of 1,100 executives at organizations with more than $1 billion in revenue across 14 countries and 11 industries and sectors.
The data came revealing that generative AI is increasingly integrated into organizations, causing changes in operational patterns. Over the past year, it has been significantly observed that the application of generative AI has surged across all sectors, and most organizations embrace generative AI at their workplaces, with only 3% enforcing a complete ban on publicly available generative AI tools for work purposes.
Those organizations that have already adopted generative AI reported experiencing benefits, including improved operational efficiency, enhanced customer experience, and increased sales.
Speaking generally, the report states that organizations have witnessed a 6.7% improvement in customer engagement and satisfaction in the areas in which generative AI has been integrated. Consequently, businesses have started to adjust their strategic approaches and explore innovative ways to harness generative AI’s capabilities.
On the other hand, The McKinsey Global Institute issued a report namely “The Economic Potential of Generative AI: The Next Productivity Frontier” that unfolded an analysis of the impact of technological automation on work activities and modeling scenarios of adoption in 2017. Back then, researchers estimated that workers spent half of their time on activities that had the potential to be automated by adapting technology existing at that time. Then they set a range of potential scenarios for the pace at which these technologies could be adopted and affect work activities throughout the global economy.
Researchers found out that technology adoption at scale does not occur overnight. The potential of technological capabilities in a lab does not necessarily mean they can be immediately integrated into a solution that automates a specific work activity, as developing such solutions takes time. Even when such a solution is developed, it might not be economically feasible to use if its costs exceed those of human labor, which proves that humans cannot be fully substituted (maybe partially). Additionally, even if economic incentives for deployment exist, it takes time for adoption to spread across the global economy. Hence, these adoption scenarios, which consider such factors together with the technical automation potential, provide a sense of the pace and scale at which workers’ activities could shift over time.
Final verdict
Across human history, we’ve already seen how new technologies have the potential and capability to reshape societies and change the anatomy of work for good. We can safely count on artificial intelligence to change the way we live and work and accomplish the simplest everyday tasks, starting from helping us generate content, analyzing data, or draft emails, to conducting the most advanced tasks, such as optimizing business processes or making recommendations about the next product to buy. This rapid development of generative AI is highly expected to significantly augment the impact of AI overall, generating trillions of dollars of additional value each year and transforming the nature of work.
However, it seems like technology could also come with a side-effect and come up with new and significant challenges. Tech users must act as much quick as they can, given the pace at which generative AI could be adopted, to prepare to address, and most importantly to be able to handle both the opportunities and the risks that come with the package.
