While engineering leaders are looking to artificial intelligence to improve features and functionality in their products, they run into significant challenges.
According to a recent survey by Gartner, 77% of engineering leaders identify building AI capabilities into applications to improve features and functionality as a significant or moderate pain point.
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The survey of 400 software engineering/application development leaders also found that the use of AI tools to augment software engineering workflows was the second largest pain point, with 71% of engineering leaders considering it significant or moderate.
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AI Technologies Not Easy To Implement
Interest in tech like AI agents is gaining the most traction since CEOs have identified AI as the technology that will have the biggest influence on their sector. However, even while executives are paying more attention to AI and its popularity is growing, it is not always straightforward to implement.
Emerging vendors and established hyperscalers have developed and continue to enhance their platforms to alleviate the pain points experienced by enterprises. Many emerging and established vendors are operating and innovating in this market. Gartner estimates the current market size of the AI application development platforms market to be $5.2 billion.
According to Gartner experts, instead of combining many vendors, large language models and AI services, leaders should choose AI application development platforms or those with the best ecosystem. In a still fairly new area of software engineering and technology, this method allows for consistency, scalability and reuse.
AI Assistants, Agents To Affect Talent
Currently, AI agents are acting as a learning peer to software engineers, enabling them to focus on complex as well as creative aspects of software engineering. This is leading to more people entering the engineering role without having the traditional computer science background.
Gartner predicts that generative AI will enable 40% of software team members to come from nontraditional software engineering or technical educational backgrounds by 2028, up from 20% today.
AI won't be able to replace all software engineering tasks, and organisations will need to focus on reviewing the output from AI-augmented tools in the short term, Gartner said. Engineers with strong foundational skills, such as logic building and developing algorithms, will thus be required. People from nontechnical backgrounds, such as design, arts and philosophy, will also provide creative ways to solve logical problems using AI.
Organisations can use AI techniques and skills data to design tailored learning paths for both new and existing employees. As per the survey, 38% of respondents said that using AI for learning a new skill is the most effective technique.
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