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The growth in importance of artificial intelligence (AI) in recent years cannot be attributed to individual factors, but rather to the synergy of various interconnected and mutually reinforcing advances.

According to recent studies, five factors are contributing to the rapid development of the "AI movement". The main drivers are Moore's Law, the digitalisation and dematerialisation of products, services and processes, their interconnection in a global network, big data and new emerging technologies. It also analyses the growth of investment in the field of AI over the last 10 years.

Moore's Law and the effects of exponentiality

If the automotive industry had developed at the same speed as the computer industry, the progress would be astonishing. Imagine a VW Beetle from 1971: If it had developed at the same rate as computer technology, it could be travelling at a staggering 300,000 miles per hour today and would only cost a few cents.

To better understand the concept of exponential growth, consider the following thought experiment:

If a person takes 31 linear steps, each of which is one metre long, they would cover a total distance of about 31 metres.

However, if the person takes 31 exponential steps, where the step length doubles with each step, the distance travelled increases exponentially. By the 31st exponential step, the person would have covered more than a billion metres!

This concept of exponential growth serves as the basis for Moore's law. Gordon Moore formulated this "law" in 1965 on the basis of empirical observations and established that the performance of integrated circuits doubles approximately every two years. Moore's Law illustrates the astonishing pace of technological progress and the exponential increase in computing power over time. Today, as we enter the age of digital transformation, the spirit of Moore's Law serves as both a marker of our progress and a beacon guiding us to the next horizon of AI potential.

Digitalisation and dematerialisation of products, services and processes

The current market situation is characterised by the transition from tangible to intangible products as digitalisation and dematerialisation take hold. This transition to the digital representation of information and communication reduces our dependence on physical objects by reducing material and energy consumption in economic activities. Examples of this shift include mobile phones replacing landline phones, digital navigation systems replacing paper maps, and digital wallets replacing traditional payment methods. Similarly, administrative and entertainment media have moved online, leading to a decline in physical documents and data carriers, and counselling services now often use digital assistants instead of face-to-face counsellors.

This trend goes beyond products and encompasses a broader networking paradigm epitomised by the Internet of Everything (IoE). The IoE builds on the concept of the Internet of Things (IoT) and comprises a networked system of products, services, processes, animals and people. This connectivity enables improved communication for business operations and personal connectivity with applications ranging from connected home appliances and office processes to AI-powered monitoring and analytics. Sensor technology continues to evolve, driving down costs and enabling more and more devices and processes to be connected, making ever-increasing amounts of data available to AI.

The IoE is creating platforms for voice and image interfaces to generate more diverse data. It is also paving the way for body hacking, where individuals can enhance their bodily functions through technologies such as implanted chips. Advances such as LPWAN are fuelling further connectivity of IoT devices over long distances, paving the way for additional AI-powered solutions.

Analysis from Cisco suggests that the IoE could generate billions in profits and savings by 2022 through better asset utilisation, increased productivity, supply chain optimisation, improved customer experience and innovation. While the exact figures are yet to be determined, the far-reaching impact of the IoE is evident and requires immediate attention from organisations.

In the IoE ecosystem, people, data, processes and things converge in connected spaces - at home, in businesses, on the move - and across multiple communication channels, extending the scope of interactions far beyond what the IoT offers in machine-to-machine communication. The growing web of connections in the Internet of Things integrates the digital and physical dimensions and opens up a world of possibilities, with particular attention to privacy and security in this increasingly connected future.


The components of the Internet of Everything (IoE), Source: Own illustration based on Kiesler/Impagliazzo (2023)

Big data and the General Data Protection Regulation (GDPR)

A solid database is essential for the development of AI. Companies rely on big data, i.e. a large and comprehensive collection of data, the characteristics of which are shown in Figure 15. Big data comprises "volume" (amount of data), "velocity" (speed of data processing), "variety" (scope and format of data sources), "veracity" (accuracy and reliability of data) and "value" (significance of data for specific applications).


The criteria for the definition of big data

The abundance of data from technologies such as sensors, digital processes and social media is driving the development of AI by improving its learning ability and predictive accuracy, with applications in various sectors including healthcare and finance.

However, the EU's General Data Protection Regulation (GDPR), which came into force on 25 May 2018, offers both benefits and obstacles to the development of AI. The GDPR's strict rules strengthen consumer trust and ensure data protection. Nevertheless, its restrictions pose challenges for the data collection requirements of AI. European companies may be penalised by GDPR requirements compared to their global competitors who may operate under less stringent data protection laws.

Therefore, it is important to maintain a balance between the benefits of exponential data growth and GDPR compliance. While the GDPR emphasises data protection, it can also restrict data collection by AI. Regularly reviewing and adapting the GDPR is crucial to encourage AI innovation without jeopardising data protection and to ensure that the potential of AI is maximised while protecting personal data.

New technologies

The Gartner Hype Cycle provides a model for understanding the development of new technologies from their introduction to general acceptance. The five key phases of the hype cycle are explained below:

  • 1. innovation trigger: technologies emerge for the first time, generate interest and receive media attention. Early developments can still be immature and investments are considered high-risk.
  • 2. Peak of exaggerated expectations: Expectations rise, sometimes unrealistically. Early adopters begin to experiment, although the technology may not yet have been thoroughly tested.
  • 3. Trough of disillusionment: Initial interest wanes as expectations are not met, leading to a decline in interest. However, this phase often leads to better insights and improvements.
  • 4. the path of enlightenment: As development progresses, practical and beneficial applications emerge. Organisations adapt technology more intelligently and develop effective practices.
  • 5. plateau of productivity: Mature technologies reach this stage when they are widely accepted and have demonstrated clear benefits.

It is important for business leaders to identify technologies that have reached the plateau of productivity because they offer reliable value and risk has been reduced. The Gartner Hype Cycle 2023 highlights 25 technologies categorised into four areas:

  • 1. Emergent AI: Includes innovative AI methods that promise to increase productivity and competitive differentiation.
  • 2. Developer experience (DevX): Tools that improve the efficiency of developers, such as software that helps with programming and platform-specific solutions.
  • 3. Pervasive cloud: Advances in cloud technologies are driving innovation in business processes.
  • 4. Security and privacy: This area focuses on technologies that strengthen security measures while taking into account the human aspects required to create more robust systems.

Gartner Hype Cycle for new technologies, source: illustration based on Gartner (2023)

Decision-makers in companies of all sizes are gaining a better understanding of these technologies. More and more organisations are developing strategies for the effective use of AI. The potential benefits are great, but carefully assessing and managing the risks of these technologies is critical.

The rise of investment in the AI sector

AI is experiencing an upsurge fuelled by high levels of global investment and the growth of AI companies, as demonstrated by Google's positioning as a "leading AI company". Between 2013 and 2022, external funding for AI will triple as the transformative potential of AI is increasingly recognised across various sectors. Investment trends show strong confidence in the continued innovation of AI, particularly in the US and China, which are leading the way, while the EU and UK are experiencing more modest growth, possibly due to more cautious investment practices and stricter data protection regulations.

The market value of AI is expected to grow to over three trillion US dollars by 2025, fuelled by technological advances in data processing, algorithmic innovation and the transition to a data-driven economy. This growth will be fuelled by AI's ability to increase efficiency, create competitive advantage and drive new business models. Industries such as healthcare, finance, manufacturing and automotive are expected to benefit greatly from the integration of AI. Companies are advised to build AI competences and adapt their business strategies. The spread of AI also has geopolitical implications and could shift the global balance of power in favour of nations with strong AI capabilities, highlighting the need for government investment and international cooperation. The rise of AI will influence economic, labour market and geopolitical dynamics and requires proactive and adaptive approaches from businesses and governments.

Conclusion

Looking at the dynamic interplay of the various drivers fuelling the AI revolution - from Moore's Law to the emergence of the Internet of Everything and beyond - it is clear to see the profound changes that are shaking the foundations of industry and society. The influx of big data, the regulatory environment shaped by the General Data Protection Regulation and the emergence of new technologies, as described in the Gartner Hype Cycle, are all outlining the contours of a future redefined by AI. Looking at the accelerated growth of AI investments and their predicted market value, it is clear that this is not just a trend, but a paradigm shift. The AI boom, characterised by a tripling of external funding and thriving specialised companies, is paving the way for unprecedented advances and efficiencies in various sectors. The US and China are leading this upswing, while the EU and UK are following at a slower pace, emphasising the strategic importance of innovation and adaptation. Understanding how AI can empower your business and unlock new potential can become a differentiator for organisations in all sectors tomorrow and remain so for many years to come.

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Picture Christian Albring

Author Christian Albring

Christian Albring is Business Developer in the GenAI team at adesso.

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