Emergence and Evolution of Next Generation Services (EE-NGS) 

The project seeks to understand how Professional Services are changing in  the age of AI and Big Data, and the role of digital services in driving that change. The project draws on evolutionary economic geography to identify   and understand where the next generation of services will emerge. The emergence of next generation of services ecosystems requires a balance of incumbents and start-ups, human and financial capital infrastructure, and a sophisticated client base.  By identifying the knowledge space that links start-ups, corporates and investors, the EE-NGS project aims to provide evidence and insights that facilitate the creation and emergence of the next generation services within high-potential ecosystems in and outside the UK. 

Working with near-real-time data, rather than using traditional Standard Industrial classifications (SICs) of economic activity, the research utilises dynamic categories of industries, markets and technologies. Understanding the intricate economic geography of sector evolution allows us to compare regional (city, region, country) competitive advantage, worldwide. Last, because we believe that policy should be adaptable to trends in the business sector, but stable in the tools and support it provides - we aim to provide longitudinal findings, follow trends, and shifts of Knowledge Spaces over time.

The importance of identifying - General Purpose Technologies (GPTs)

In recent years, identifying potential General Purpose Technologies (GPTs) have caught increasing attention as their emergence is intimately related to broader technological innovation. If a technology has a substantial and pervasive effect across application sectors, or the business ecosystem, it is often called General Purpose Technology. Good examples of GPTs consist of the electricity, the steam engine, information and communication technology (ICT), among others. As they initially have much scope for improvement and it takes time before they are widely adopted, mapping emergent GPTs becomes an essential task to encourage productivity. If, nowadays, a new GPT is yet to be discovered in its infancy, this could drive business transformation and enhance growth.

Artificial intelligence (AI) has been signalled as a new GPT, researchers have agreed in its potential to become a GPT. What is less clear, however, is how AI has been transforming different application sectors and therefore the extent to which AI relates to them. Hence, many questions arise from, e.g., what is the level of penetration of AI in different application sectors? To what extent AI has triggered a transformation? What is the potential of AI to keep transforming businesses? What other technologies complement AI in the business transformation?

In our research, we sustain that AI is driving a transformation in the advanced professional services fostered by sector coalescence, such as Finance is becoming FinTech, Legal services is becoming LegalTech, Health is becoming HealthTech, etc. In this sense, we need to find evidence that supports that relationship between the adoption of AI and the growth and R&D that firms are experiencing. This is due to the need to prove that AI as an emerging technology, hence it implies higher risk than more mature technologies, this can be regarded as representing a significant strategic opportunity.

At the same time, services firms are understandably cautious when investing in AI technologies. This is particularly the case where there is not an established ‘industry standard’ in the sub-sector let alone the sector, and the technologies could have a transformational impact on the firm.

Our preliminary findings show that AI has characteristics of a GPT, yet like this, other technologies have also potential to become a GPT. AI and other technologies are highly connected with different branches of the global Advanced Professional Services (APS). We presume that such connections are the forces that are driving change in APS, and hence transforming these to specialisms as LegalTech, FinTech, PropTech, HealthTech and AdTech.

Further analyses on the identification of a GPT will allow to propose policy advice. Precisely, a challenge for firms, city-regions and national governments is ensuring that the institutional arrangements are in place to support and scale the adoption of different technologies. Artificial intelligence, among other technologies, can drive already existing businesses to transform into more specialized new type of services. By means of related variety and knowledge complexity it is possible tailoring regionally bespoke smart specialization policy. Ultimately, our data-driven approach, based on sector coalescence, could be cornerstone to enhance digital transformation and the growth of the services’ global economy.

Project Reports