AI’s role in software development is reaching a pivotal moment — one that will compel organizations and their DevSecOps leaders to be more proactive in advocating for effective and responsible AI utilization.
Simultaneously, developers and the wider DevSecOps community must prepare to address four global trends in AI: the increased use of AI in code testing, ongoing threats to IP ownership and privacy, a rise in AI bias, and — despite all of these challenges — an increased reliance on AI technologies. Successfully aligning with these trends will position organizations and DevSecOps teams for success. Ignoring them could stifle innovation or, worse, derail your business strategy.
From luxury to standard: Organizations will embrace AI across the board
Integrating AI will become standard, not a luxury, across all industries of products and services, leveraging DevSecOps to build AI functionality alongside the software that will leverage it. Harnessing AI to drive innovation and deliver enhanced customer value will be critical to staying competitive in the AI-driven marketplace.
From my conversations with GitLab customers and monitoring industry trends, with organizations pushing the boundaries of efficiency through AI adoption, more than two-thirds of businesses will embed AI capabilities within their offerings by the end of 2024. Organizations are evolving from experimenting with AI to becoming AI-centric.
Harnessing AI to drive innovation and deliver enhanced customer value will be critical to staying competitive in the AI-driven marketplace.
To prepare, organizations must invest in revising software development governance and emphasizing continuous learning and adaptation in AI technologies. This will require a cultural and strategic shift. It demands rethinking business processes, product development, and customer engagement strategies. And it requires training — which DevSecOps teams say they want and need. In our latest Global DevSecOps Report, 81% of respondents said they would like more training on how to use AI effectively.
As AI becomes more sophisticated and integral to business operations, companies will need to navigate the ethical implications and societal impacts of their AI-driven solutions, ensuring that they contribute positively to their customers and communities.
AI will dominate code-testing workflows
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