Slower adoption, less value
Firms need to move beyond the simplest use cases for generative AI to deliver more business value
Generative AI Radar: Europe
Europe’s lower spending levels also correlate with slower and less mature deployments of generative AI initiatives than in North America. And European companies are significantly behind in creating value from their generative AI initiatives.
We asked respondents to indicate the progress of generative AI initiatives along a scale, which ranged from those that had no generative AI initiatives to those that had established generative AI use cases that create business value.
All the European companies in our survey are engaging with generative AI — as was the case in our North America sample. However, a slightly higher proportion is either still in the experimentation phase or in the implementation phase. In Europe, 41% and 36% of respondents are in these phases respectively. This compares to 35% and 30% in North America.
Only 6% of European companies are creating value from generative AI, whereas the proportion is 16% in North America (Figure 4).
Figure 4. Most European companies are still experimenting
Source: Infosys Knowledge Institute
Looking at the data by country, we see that Germany, France, and the UK have similar proportions of respondents that have created value from their generative AI implementations, with Germany slightly ahead (10%) and the UK slightly behind (8%).
However, despite lagging France in spending, both Germany and the UK are delivering more for their investments in generative AI. In other words, despite spending significantly less than France, German companies are achieving the same levels of implementation and value creation.
Similarly, the UK is spending less than both the leaders but is comparable in terms of companies that are creating value from generative AI (Figure 5).
Figure 5. Germany leads in value creation
Often, when it comes to new technologies, large enterprises lag their smaller, more nimble counterparts. This is due to either their inability to pivot quickly or their tendency to adopt a wait-and-see approach to most new technologies. This is not the case with generative AI.
As we discovered in our North American research, the reverse is true for the adoption of generative AI solutions. Larger companies seem to have been faster to adopt generative AI and have a higher incidence of creating value as well.
Indeed, this trend is magnified in Europe, where there is a very big gap between the largest and smallest companies we surveyed (Figure 6).
Figure 6. Large companies are more advanced in their generative AI adoption
The popularity and relative maturity of generative AI in larger companies could have a pair of explanations. Prime among these is that generative AI tools could simply be more accessible and available to larger companies as big enterprise software and technology vendors such as Microsoft, Google, and Nvidia bring their solutions to their largest customers first.
However, larger firms are also better targets for some of the early use cases for generative AI. These range from improving the efficiency and quality of large call center and omnichannel customer communications, to translating and parsing large caches of documents, or even simply summarizing action points from multiple company meetings. Large corporations offer plenty of low-hanging fruit when it comes to generative AI.
Despite much of the excitement around generative AI focusing on content generation, this is not where most companies see the biggest impacts on their business.
When asked about this, over a third of respondents cited “enhanced user experience and personalization” as the main area of value that they expected from generative AI. This was the case whether we asked European or North American companies (Figure 7).
Figure 7. Content-led use cases create the least value
Similarly, in Europe and North America, content generation and creativity were seen as the least common outcome that respondents were looking for from their generative AI deployments.
The companies that move beyond the simplest generative AI use cases and realize the higher order benefits (efficiency, personalization, product development) will be those that embed this technology in their businesses and transform their operating models to become truly AI-first businesses.
