2023-09-25 17:59:00
Following the end of the pandemic, the first half of 2023 has seen a resurgence of enthusiasm about the potential of technology to catalyze progress in business and society. Generative AI deserves much of the credit for ushering in this resurgence, but it is just one of many advances on the horizon that could drive sustainable, inclusive growth and solve a complex global challenge.
At McKinsey, through its Technology Council, they analyzed and researched the latest technological trends in the market with the aim of creating a detailed and useful study that serves as a basis for executives looking for new ways to evolve their business. During their research, they selected 15 trends based on the impact they are having on the corporate world.
Importantly, while many of these are in the early stages of adoption and scale, executives can use this research to plan for the future by developing an understanding of potential use cases and identifying the critical skills needed. as they hire or upskill talent to make these opportunities a reality.
The analysis examines quantitative measures of interest, innovation and investment to gauge the momentum of each trend. Recognizing the long-term nature and interdependence of these trends, they also delved into the underlying technologies, uncertainties, and questions surrounding each trend. In addition, this year they added a new and important dimension of analysis: talent. Providing data on the dynamics of talent supply and demand for the most relevant roles for each trend.
The report grouped these 15 technological trends into five categories to facilitate their understanding: the AI revolution, building the digital future, the frontiers of computing and connectivity, cutting-edge engineering and a sustainable world. Of course, when considering combinations of trends, there is significant power and potential in analyzing these groups.
These are some of them:
The AI revolution: With AI capabilities such as machine learning, computer vision, and natural language processing, businesses across industries can use data and gain insights to automate processes, add or increase capabilities, and make better decisions. McKinsey research estimates that the potential economic value at stake in applied AI is between $17 and $26 billion, and the proportion of companies seeking that value has been increasing.
Industrializing machine learning: Machine learning (ML) industrialization, commonly known as ML operations, or MLOps, refers to the engineering practices necessary to scale and maintain ML applications in an enterprise. These practices are enabled and supported by an ecosystem of technical tools that is rapidly improving in both functionality and interoperability. MLOps tools can help companies transition from pilot projects to viable commercial products, accelerate the scaling of analytics solutions, identify and resolve issues in production, and improve team productivity.
Generative Artificial Intelligence: Generative AI marks a turning point for Artificial Intelligence, since, unlike previous AI, it can allow the creation of new and unstructured content (such as text, audio, video, images, codes, simulations and even sequences of proteins or consumer journeys) based on information it learns from similar formats of unstructured data. And the technology at its core, the fundamental models, can be adapted to a wide range of tasks, for example, summarization, classification and writing.
McKinsey expert and partner, Felipe Villareal, assures that: “Despite the enormous promise, we still have many challenges when implementing digital transformations and the speed with which technology evolves is impressive. One of the key challenges is managing the risks inherent to these technologies. For example, as generative AI becomes more sophisticated and autonomous, strong ethical and legal frameworks need to be established to ensure its responsible use and avoid unintended consequences..
Next generation software development: These are transforming the capabilities of engineers at every stage of the software development lifecycle, from planning and testing to deployment and maintenance, and enabling more non-technical employees to build applications. They can help simplify complicated tasks and reduce others to single commands. These technologies include AI peer programmers; platforms with or without code; infrastructure as code; integration, implementation and automated testing; and emerging generative AI tools. Adoption may be slow, however, significant productivity increases seen in early testing suggest that widespread use is on the horizon.
The future of mobility: More than a century after mass production of automobiles began, mobility has reached a second major inflection point: a shift toward autonomous driving, connectivity, vehicle electrification, and shared mobility technologies. This change promises to disrupt markets while improving the efficiency and sustainability of land and air transportation of people and goods. For example, autonomous driving technologies are projected to generate up to $400 billion in revenue by 2035.
Electrification and renewable energies: Electrification and renewables help move towards net zero commitments and include solar, wind, hydroelectric and other renewables; nuclear energy; hydrogen; sustainable fuels; and electric vehicle charging.
These are just a few of the many technology trends that are likely to have a significant impact on businesses in 2023, however, those who want to stay ahead should be aware of these trends and start planning how they can leverage them to their advantage.
Therefore, it is important to take into account that the pace of technological change is accelerating, causing companies to become more agile and adaptable. The impact of technology is not always linear, so they must be prepared for unexpected disruptions, and use technology correctly. By understanding the technology trends for 2023, organizations can position themselves for success in the years to come.
See the full report here:
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