Gartner predicts that more than 30% of the increase in demand for APIs will come from Artificial Intelligence and tools that use Language Models

Gartner, the world leader in research and advice for businesses, predicts that by 2026, more than 30% of the increase in demand for Application Programming Interfaces (APIs) will come from Artificial Intelligence (AI) and tools that use Language Models ( LLMs). 

Adrian Lee, Vice President and Analyst at Gartner

“With technology service providers (TSPs) leading the adoption of GenAI, the repercussions will be widespread,” says Adrian Lee, Vice President and Analyst at Gartner. “This includes increased demand for APIs for Language Models (LLMs) and Generative Artificial Intelligence (GenAI)-enabled solutions, driving technology service providers to help their customers advance their journeys further. This means they will have to move faster than ever to meet demand.” 

Gartner's survey of 459 technology service providers (TSPs), conducted from October to December 2023, shows that 83% of respondents reported that they have already implemented or are currently piloting GenAI within their companies.  

“Enterprise customers must determine the optimal ways to add GenAI to their offerings, such as using third-party APIs or open source options. With technology service providers leading the way, they provide a natural connection between these enterprise customers and their needs for GenAI-enabled solutions.”

Technology service providers must maximize investments in GenAI for growth:  

Gartner research shows that 50% of technology service providers will make strategic changes to extend their core product/service offerings to realize a complete delivery or end-to-end service solution. Gartner predicts that by 2026, more than 80% of independent software vendors will have GenAI capabilities embedded in their enterprise applications, which represents an increase of 5% compared to the current number.  

“Enterprise customers are at different levels of readiness and maturity in their adoption of GenAI. This gives technology service providers a transformational opportunity to provide the software and infrastructure capabilities, talent and expertise needed to accelerate the journey,” says Lee. 

Throughout the lifecycle, technology service providers need to understand the limitations, risks and costs before incorporating GenAI capabilities into products and services. To do this, they must: 

– Document use cases and clearly define the value users will experience by having GenAI as part of the product; 

– Determine optimal ways to add GenAI to offerings (such as using third-party APIs or open-source model options) and consider how the costs of new features might affect pricing decisions; 

– Address user experience, developing optimizations to minimize user difficulties when dealing with steep learning curves; 

– Review different use case risks (such as inaccurate results, data privacy, secure conversations, and intellectual property infringement), adding specific protection rails for each product vulnerability. 

Gartner customers can read more at “Research Roundup: Enhance Products and Services With GenAI🇧🇷