New AI education initiatives show the way for knowledge retention in enterprises

Two of the biggest names in artificial intelligence are independently developing new AI tools that encourage learning, at a time when the technology has been criticized for dumbing down smart users in the enterprise and discouraging critical thinking. While the new initiatives from OpenAI and Anthropic are aimed at transforming how AI is used in higher education, the opportunities they open up extend beyond universities.

The approach taken by the two AI firms, emphasizing learning, retention, and critical thinking, has implications for enterprises that are increasingly integrating AI into their workflows.

Such education-focused initiatives arrive at a crucial moment, as research increasingly shows that improper use of AI in workplaces leads to what experts call “cognitive atrophy” — a decline in employees’ ability to think critically when AI handles too many cognitive tasks.

Learning-first approach can benefit enterprises too

Anthropic’s newly announced Claude for Education introduces a new “learning mode” to its AI assistant, designed to guide students through problem-solving rather than simply providing answers. By employing Socratic questioning techniques, the AI prompts users to think through problems independently.

“In Learning mode, Claude helps students develop their independent thinking by guiding rather than answering: Asking ‘How would you approach this problem?’ instead of providing immediate solutions,” Anthropic said in a statement.

OpenAI has been developing education-focused tools for over a year through its ChatGPT Edu initiative. The company recently committed $50 million to AI research in collaboration with 15 colleges through the NextGenAI Consortium and made its ChatGPT Plus subscription free for all US and Canadian college students until May to “help them through finals.”

While targeting academic institutions initially, these learning-centered designs reveal a potential blueprint for enterprise AI implementation — one that preserves human expertise rather than replacing it.

Expertise erosion

Research confirms what many enterprise leaders fear: Overreliance on AI can diminish critical thinking. A study by Microsoft and Carnegie Mellon University found that professionals who rely heavily on AI tools engage in less independent reasoning over time.

“Used improperly, technologies can and do result in the deterioration of cognitive faculties that ought to be preserved,” the study said of generative AI.

This problem extends beyond basic workplace tasks. The National Bureau of Economic Research (NBER) found that AI can disproportionately impact different skill levels, with highly skilled professionals becoming complacent.

Abhivyakti Sengar, practice director at Everest Group, explains the core issue: “AI shouldn’t be a shortcut to answers: It should be a scaffold for better thinking. As enterprises adopt tools like ChatGPT and Claude, there’s a growing risk of expertise erosion, where tacit knowledge fades as teams defer too readily to AI.”

How education initiatives could transform enterprise AI

The link between these education initiatives and enterprise concerns becomes clear when examining their design principles. Both OpenAI and Anthropic are developing AI systems that prioritize human development over mere efficiency in a direct response to the problems identified in workplace studies.

These education platforms essentially serve as testing grounds for more responsible AI implementation models that could transfer to enterprise settings. The Socratic questioning in Anthropic’s Learning Mode and OpenAI’s focus on deeper engagement suggest a fundamental shift in AI design philosophy, from tools that provide answers to tools that enhance human capabilities.

“To counter cognitive atrophy, organizations must design for active engagement: Teams should be encouraged to interrogate AI outputs, not just accept them. Think ‘copilot,’ not ‘autopilot,’“ Sengar said.

He suggested that businesses adopt techniques inspired by AI-driven education models. These include Socratic prompting that encourages critical thinking, progressive disclosure of information rather than immediate answers, and requiring decision rationales to ensure human judgment remains sharp. Each of these approaches mirrors what’s being pioneered in educational settings but with adaptation for workplace contexts where preserving institutional knowledge is particularly crucial.

Education for the future of work

How students learn to interact with AI today will likely determine how they use these tools in future workplaces. The educational approaches being pioneered could create a generation of workers who use AI as an enhancement to their thinking rather than a replacement for it.

For enterprises concerned about knowledge retention, these educational AI models offer promising strategies for integration. By designing AI systems that stimulate rather than suppress critical thinking, companies may be able to address the “digital amnesia” problem while still gaining efficiency benefits.

“Without these mechanisms, we risk cultivating a workforce that’s faster, but not necessarily smarter, and systems that optimize for output over understanding,” Sengar warned.