As artificial intelligence moves beyond merely assisting work tools to begin changing the very standards of organizational operations, it is predicted that corporate recruitment methods, data management systems, and technology investment priorities will also be restructured. The assessment is that the focus of corporate competitiveness is shifting from simply adopting AI to the sophistication of talent selection, governance structures, and data interpretation frameworks.

In its data and analytics outlook released in Seoul on March 16, Gartner predicted that the proliferation of AI will bring about cascading changes across leadership, talent strategies, and market structures. According to this forecast, by 2027, 75% of all hiring processes will include evaluation factors that verify a candidate's ability to utilize AI in the workplace.

Talent acquisition was cited as the area that will change the fastest. This means that for organizations to secure personnel suited for an AI-centric work environment, procedures to verify actual application capabilities—in addition to career history or job experience—will become necessary. Rita Salam, a senior VP analyst at Gartner, explained that companies must measure the gap between their AI adoption goals and the readiness of their internal workforce in a more rigorous manner.

Changes in the business software market have also been predicted. Gartner forecasted that the proliferation of generative AI and AI agents will bring about structural changes worth approximately $58 billion in the productivity software market by 2027. This means there is a high possibility that document creation and editing, user interfaces, various plugins, and even file formats will be redesigned around AI.

In the mid-to-long term, the sources of data are also expected to change. Gartner predicted that by 2029, data generated by AI agents operating in physical environments will reach ten times the amount of data from digital AI applications. Furthermore, it forecasted that by 2030, half of organizations will utilize autonomous AI agents to automate the enforcement of governance policies. However, a lack of execution management and issues with system integration were identified as obstacles to widespread adoption.

Along with this, Gartner predicted that by 2030, AI startups generating $2 million in annual recurring revenue per employee will emerge, and that executives who prioritize interpersonal skills are highly likely to lead the securing of AI competitiveness. Furthermore, it forecasted that the Universal Semantic Layer will establish itself as a core digital infrastructure alongside data platforms and security systems.