Artificial intelligence (AI) is rapidly reshaping education, and schools are increasingly being asked to make decisions about adopting emerging technologies. As AI becomes more integrated into teaching and learning, educators need practical ways to evaluate which tools genuinely improve learning, create value for teachers, and students, and are worthy of long-term investment.
One of my biggest takeaways from this analysis is that educational technologies are not worthwhile investments because they are innovative. They become worthwhile investments when they:
- Solve meaningful educational problems
- Create lasting value for learners and educators
- Can be implemented in ways that are practical, sustainable, and scalable
Working as a Coordinator of Educational Technology, I regularly evaluate emerging technologies, support implementation, and make recommendations that influence technology adoption within my school division. As NotebookLM gained momentum in teaching and learning over the past year, I found myself increasingly curious about its potential. That made it a timely choice for my Educational Venture Analysis (EVA), allowing me to explore the platform beyond the initial excitement and critically evaluate its educational value, market opportunity, and long-term investment potential.
| My Analysis Explored: | Hands-On Product Testing Included: |
| Market opportunity Competitive positioning Educational value Implementation Challenges Long-term investment potential | Audio Overviews Video Overviews Socratic Tutoring |
My recommendation is to Invest with Conditions, but that recommendation is only part of the story.
I hope this analysis encourages others to look beyond product features and consider the broader educational, market, and implementation factors that ultimately determine whether a venture is worthy of investment.
Explore the NotebookLM Educational Venture Analysis (EVA)
Hi Sam,
I thought that your analysis was a nicely balanced evaluation of NotebookLM’s strategic value within the educational AI market. Your hands-on product testing with current research to support your recommendation was helpful, and certainly welcome as a teacher interested in the value it may offer to my students. One thing you mention several times is that NotebookLM is a “source-grounded AI learning partner” rather than simply another generative AI tool. Do you see this aspect remaining a sustainable competitive advantage, or is it more of a short-term differentiator as the market evolves?
Additionally, I was left wondering about your recommendation to “invest with conditions.” It seems your opportunities and risks focus on an educator’s perspective, with references to multimodality, adaptive support, cognitive offloading, etc, but what is Google’s business case for continued investment? Which metrics, such as user growth, institutional adoption, Workspace retention, or internal investment as compared to other products, would best indicate long-term success?
On a related note, which factors would have to change/improve for you to adjust your recommendation simply to “invest unconditionally?”
Thanks very much for your analysis. As someone who has only recently discovered and started using NBLM, I found it really informative and well-grounded in research.
Hi Jason,
Thanks for the feedback and questions, Jason! Based on your questions, I think you picked up on one of the areas I found most challenging in approaching NotebookLM through an EVA lens.
I do think source grounding is currently one of NotebookLM’s strongest differentiators as it gives users greater control over the information being used to generate outputs. However, I’m less convinced that source grounding alone will remain a sustainable competitive advantage as similar capabilities become more common across AI platforms. We actually saw how quickly this market can change and as we developed our AI Learning Partners OER. We published it on July 13 using NotebookLM and only three days later Google rebranded its platform as Gemini Notebook. While the functionality is essentially the same, having the product change during our study of it is a tangible reminder of how fast-paced AI products, positioning, and ecosystems can evolve. For me, that makes Google’s broader ecosystem integration and ability to sustain adoption particularly more important than any single feature.
I also like your question about Google’s business case. While my analysis focused primarily on the investment decisions from an educational institutional perspective, from a Google perspective, I would be interested in institutional adoption, sustained active use, Workspace retention, and continued internal investment relative to Google’s other AI products. The distinction between investment in the adoption of technology and investing in the venture itself is something I’ve come to appreciate more much through this course.
For me, to move from Invest with Conditions to Invest, I would want stronger evidence of sustained institutional adoption, clearer long-term pricing/product commitment, and evidence that implementation can preserve educational benefits while mitigating risks such as cognitive offloading or learner dependency.
Thanks for the thoughtful response! You make a great point about how quickly things changed during our own OER development. The fact that NotebookLM was rebranded just three days after we published really highlights how difficult it is to think about long-term competitive advantage in AI.
I also agree with your conditions to upgrade your decision. As an educator, I think the final point (…evidence that implementation…) should take precedent, but the EVA in me looks more toward the evidence of sustained institutional adoption.
I guess that raises the question: could strong institutional adoption actually be considered a sign of success if we don’t yet know whether it is improving learning?
Hi Jason,
Thanks for the follow up. I think that distinction is really important. From an EVA perspective, strong institutional adoption could certainly indicate market success, particularly if it translates into sustained use, retention, and continued investment. However, I don’t think adoption alone necessarily tells us whether a technology is fully successful in education.
One of my biggest takeaways from this course has been that adoption and educational value need to be considered alongside one another. A tool can be widely adopted because it is convenient, well-integrated, or institutionally supported without necessarily improving learning. With NotebookLM specifically, I would want to know both whether schools continue to use it, and how students and educators are using it, and the results of that on their impacted learning.
This also brings me back to cognitive offloading. NotebookLM increases efficiency and engagement, but students increasingly outsource processes such as synthesis, questioning, or sense-making. High adoption could actually mask educational concerns rather than demonstrate success.
So maybe, reflecting on this conversation, I might refine my original investment conditions further as sustained institutional adoption would tell me there is a viable market, but evidence of learning outcomes and responsible implementation would tell me whether it is a venture worth sustaining in education.
Thank you for this insight and conversation, it really sparked me to reflect what I actually mean by “success” when evaluating an educational venture.