One-third of technology and service provider organisations with artificial intelligence (AI) technology plans said they would invest $1 million or more into these technologies in the next two years, according to a new survey from Gartner, Inc.
The vast majority of survey respondents (87%) with AI technologies as a major investment area believe industry wide funding for AI will increase at a moderate to fast pace through 2022.
“Rapidly evolving, diverse AI technologies will impact every industry,” said Errol Rasit, managing vice president at Gartner. “Technology organisations are increasing investments in AI as they recognise its potential to not only assess critical data and improve business efficiency, but also to create new products and services, expand their customer base and generate new revenue. These are serious investments that will help to dispel AI hype.”
Compared with other emerging technology areas such as cloud and IoT, AI technologies had the second-highest reported mean funding allocation. Respondents whose organisations invested in AI reported their highest planned investment in computer vision, at an average of $679,000 over two years.
“Very few respondents reported funding amounts of less than $250,000 for AI technologies, indicating that AI development is cost-intensive compared to other technology innovations. This is not an easy segment to enter due to the complexity of building and training AI models,” said Rasit.
The survey also highlights the relative immaturity of AI technologies compared to the other innovation areas. Just over half of respondents report significant target customer adoption of their AI-enabled products and services. Forty-one percent of respondents cited AI emerging technologies as still being in development or early adoption stages, meaning there is a wave of potential adoption as new or augmented AI products and services enter general availability.
Technology immaturity is cited as a top reason among AI-investing organisations leading to failure when integrating an emerging technology. Furthermore, product leaders investing in AI whose implementations are progressing slower than expected reported product complexity and a lack of skills as the main hindrances to their progress.
“These survey responses reflect the difficult cycle of developing AI technology, given its complexity, as well as industry wide challenges in hiring AI talent due to the finite number of skilled individuals,” said Rasit.
