AINews & Analysis

High Costs of Deployment, Integration Stand in the Way of AI Investments

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Artificial intelligence (AI) is expected to change the world. AI can help automate decisions and processes, predict and shape future outcomes and optimize employees’ time to focus on higher value work. But challenges stand in the way, believe analysts.

Even though companies across size and industry are upbeat on AI adoption, a new survey shows that it is still early days as high costs of deployment and integration remain the key problem in AI investment.

According to a new Gartner survey, one-third of technology and service provider organizations with AI technology plans said they would invest $1 million or more into these technologies over the next two years. The majority of respondents (87%) with AI as a major investment area believe that industry-wide funding for AI will increase at a moderate-to-fast pace through 2022.

“Rapidly evolving, diverse AI technologies will impact every industry,” Gartner managing vice president Errol Rasit said in a statement. “Technology organizations are increasing investments in AI as they recognize 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 organizations 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 organizations 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.

The Gartner survey shows. Just over half of respondents report “significant” consumer adoption of their AI-enabled products and services, while 41% cited AI emerging technologies as still being in development or early adoption stages.

“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,” Rasit said.

“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.”

There is no magic solution to the AI skills gap, but experts recommend that training staff in data and AI skills, infusing AI technologies to automate mundane tasks, freeing up human workers to upskill and to streamline hiring – companies can close the talent shortage.

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