European Consumers Are Optimistic About Generative AI But More Needed to Close Trust Cap – Report

The European generative AI market is growing steadily, providing considerable opportunities, however, firms need to still overcome key challenges to ensure people feel comfortable with the tech. This, according to an update from Deloitte.

Trust, which is considered to be a cornerstone of “widespread” acceptance, is particularly crucial, the Deloitte report noted while adding that as innovation surges, the future of generative AI will depend on effectively “closing the trust gap” between different organizations, consumers, as well as the worers who depend on these tools.

The report from Deloitte explained that Generative AI is continuously changing the tech landscape, both in Europe and internationally.

The European generative AI (gen AI) market is evolving at a rapid pace with rising investments approaching $47.6 billion in value during 2024 and a surge in startups, especially in France, Germany, the Netherlands, and the United Kingdom.

In Deloitte’s State of Generative AI in the Enterprise quarter three (Q3) report, 65% of European business professionals confirmed that they are increasing their investments in gen AI due to the “substantial value realized so far.”

But the update from Deloitte also noted that gen AI’s “success” will not be defined simply by which firm invests the most or develops the best algorithms.

Instead, the report from Deloitte pointed out that it will depend on how effectively employees use these tools and how “confident” consumers are in gen AI’s benefits.

Deloitte defines trust as demonstrating a “high degree of competence” and the right intent.

According to the update from Deloitte, both of these factors are critical for the successful adoption of any innovative tech, particularly gen AI.

Is the tech reliable, and does it have the interests of its stakeholders in mind?

The pace and scale of its adoption will largely be determined by the “trust” employees and consumers have in its capabilities.

Deloitte recently surveyed over 30,000 consumers and employees across 11 European nations in order to assess their trust in gen AI and “readiness” to adopt these tools.

The research study findings shared by Deloitte reveal both optimism and notable concerns regarding the potential risks, signaling a “critical trust” gap that businesses must address.

To ensure gen AI’s long-term success, organisations must prioritise responsible implementation and build trust among employees and consumers.

From June 28 to August 12, 2024, Deloitte surveyed 30,252 consumers and employees in Belgium, France, Germany, Ireland, Italy, Poland, Spain, Sweden, Switzerland, the Netherlands, and the United Kingdom.

Of these respondents, 44% had used gen AI, 22% had not used it but were aware of it, and 34% were either unaware or unsure of any gen AI tools.

Respondents unaware of any gen AI tools were “excluded from the analysis.”

All respondents (consumers and employees) familiar with gen AI answered questions about the “general use and potential impact of these tools.”

Employees have reportedly responded to an additional subset of questions, specifically addressing their use of gen AI in the workplace.

The samples are said to be “nationally representative” within each of the 11 countries and reported data weighted by age, working status (interlocked with gender), and region.

In addition, education as well as social grade (for the United Kingdom only) were used for “weighting where applicable.”

In order to conduct a “worker-leader gap” analysis, Deloitte said that they also leveraged the European cut of Deloitte’s State of Generative AI in the Enterprise Q3 survey data.

This survey has reportedly included insightful data from 705 senior industry professionals based in European nations such as the United Kingdom, France, Germany, Italy, the Netherlands, and Spain.

Deloitte explained that it defines generative AI as a branch of artificial intelligence that is able to “generate text, images, video, and other assets in response to a query.”

These systems, often built using large language models, are able to interact with humans.



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