Artificial intelligence is reshaping the global workforce and rapidly expanding the expectations placed on today’s learners. The World Economic Forum predicts that technological advancements like AI, alongside economic and demographic factors, will lead to a net increase of 78 million global jobs this decade. Educational institutions now face a pivotal moment. They must evolve how students learn, how instructors teach, and how technology supports each step of that journey.
For decades, the education sector adopted new technologies cautiously. However, the profound impact of AI on the workforce has accelerated interest and experimentation. Our latest research at Cengage Group shows that both positive perceptions of AI and classroom usage are rising. While this enthusiasm is a promising step toward ensuring learners are prepared for an AI-forward future, it’s critical that institutions approach AI responsibly.
With new AI tools launching at unprecedented speeds, it can be difficult to determine which will truly enhance learning outcomes. In some cases, rapid launches have created more friction for educators and confusion for students. To ensure responsible deployment, the conversation must shift from racing to market and instead toward measured, purposeful development aligned with how learning actually occurs.
WELL-INTENTIONED, BUT MISSING THE MARK
Many big tech companies have rushed to develop AI-based educational tools. But while tech innovators have made strides in exploring AI to enhance the educator and student experience, the critical reality is that education is an incredibly complex ecosystem. Education is simply not fit for plug-and-play solutions.
Google’s recent “homework help” feature is one example. Designed to give students an AI overview of what appeared on the screen including assessment answers, the tool inadvertently made it harder for instructors to validate work and accurately gauge understanding. Instead of reducing friction, it increased workload for both educators and students, ultimately leading to a pause in deployment.
A similar challenge emerged this past summer with OpenAI’s Study Mode. While designed to guide students and ask questions rather than provide answers, it is just one click away from ChatGPT, where answers are readily available. Without a deep understanding of teaching fundamentals, and how and when real learning happens, technological developments can lead to unintended consequences that disrupt rather than improve learning.
These examples highlight an important truth. Innovation alone is not enough. Educational impact requires domain expertise, intentional design, and clear boundaries that promote understanding rather than shortcuts.
BALANCE MEANINGFUL INNOVATION AND REINFORCE LEARNING
To deliver educational support that blends innovation with learning outcomes, AI product development must balance the needs of both educators and students. Faculty are increasingly being asked to do more with less. AI should lighten that load, not add to it. For example, AI can surface classroom trends, flag areas where students are struggling, and help educators personalize instruction.
Students, meanwhile, need support tools that build understanding, and don’t just provide answers. Success in student deployment lies in cultivating curiosity and critical thinking. For example, AI can provide study support outside of classroom hours, deliver personalized feedback, and encourage further exploration to strengthen learning.
This balanced approach requires maintaining human oversight. Collaboration with institutions and faculty ensures AI experiences align with course objectives and reinforce, rather than disrupt, proven teaching practices.
THE PATH FORWARD: PRIORITIZE PEDAGOGY
As AI continues to evolve, pedagogy must be at the core of all innovation, ensuring academic integrity and quality content that builds trust and drives meaningful student outcomes. Through controlled, confined subject knowledge and consistent training to ensure accuracy and academic integrity, AI tools can prioritize pedagogy and remain narrowly focused on driving specific student learning outcomes.
AI should act as a supporting coach who helps break down problems, prompts curiosity, and encourages persistent learning so students can confidently reach the correct answer on their own. This purpose-built approach to AI complements the human teacher and enhances instruction by confirming student understanding and pinpointing knowledge gaps to support educators in delivering more personalized learning.
The key to unlocking AI’s potential in education goes beyond speed to market, and lies in thoughtful development rooted in intentional and responsible design. With pedagogy at the core, AI becomes more than a tool. It becomes a partner in improving learning outcomes for students and reducing the educators’ load.
Darren Person is EVP and chief digital officer of Cengage Group.