• by Laurie Sullivan , Staff Writer @lauriesullivan, August 14, 2023

The U.S. is slightly below the global average with 92% of companies planning to increase generative artificial intelligence (GAI) spending, according to recent data.

Lucidworks, which supports technology and enterprise search, conducted a global study of GAI practices of more than 6,000 participants from companies with 100 or more employees across 14 industries and nine functional departments.

The study, fielded between May and July 2023, evaluated 80 best practices and identified four stages of development to help businesses create industry-specific and custom roadmaps.

India and Chinese companies are leading when it comes to making decisions to embrace GAI, with 100% of Chinese companies and 98% of Indian companies gearing up to boost their GAI investments.

Ninety-six percent of Australian companies, 95% of French companies, 94% of U.K. companies, and 92% of German companies plan to invest in GAI.

Lucidworks categorized companies into four stages: about 10% of those participating in the study are Trailblazers, while 14% are Leaders, 60% are Challengers, and 16% are Rookies.

The company found that the strategies for GAI implementations are “highly practical,” with businesses focused on governance, cost reduction, serving customers, and growth.

Technology and data-science departments lead in GAI investments, with 96% saying they will invest the most in GAI.

Ninety-three percent of research or product development departments say they will make investments, and 92% of finance or accounting divisions.

The number of initiatives companies plan to launch is also important to note. Among the 80 identified GAI Best Practices, the average company will launch a mere 7.5 initiatives, as they test the waters.

The technology sector leads the way, and on average, technology companies have launched 10.7 GAI best practices.

The retail sector follows close behind, with an average of 7.7 launched best practices. Retailers are harnessing the power of generative AI to enhance customer experiences, improve the customer and shopper digital experience, and create personalized marketing strategies.

On the other end of the spectrum, healthcare, professional services, government, and hospitality sectors are lagging in their adoption, as each has less than six launched best practices

The data also highlights a significant correlation between companies that do not intend to increase their generative AI spending and the prevalence of concerns related to the technology.

The top concerns cited are implementation, including the security of company data; transparency in understanding how AI-based decisions are made; the accuracy of AI-generated outputs; ensuring responsiveness in terms of timeliness and tone, and the need to avoid bias.

The fear of job displacement is a prominent concern, as companies grapple with the potential impact of generative AI on their workforce and organizational dynamics.

The data underscores the importance of informed decision-making when it comes to generative AI adoption.

Companies willing to increase GAI spending have a higher level of confidence in addressing these concerns.

By allocating resources toward the development of AI best practices, these companies can invest in security protocols, work toward more interpretable AI models, enhance the accuracy of AI outputs through continuous learning, and develop AI practices that promote responsiveness and fairness in interactions