Engaging Stakeholders In EdTech Innovation Processes

Most stakeholder ‘engagement’ is just a Slack message and a prayer. But engagement doesn’t happen at the end of research. It happens in the middle. If you’re just sending people a link to your insights repo and hoping something sticks, you’re not activating research, you’re archiving it. This is the mindset I’ve been building into my workflow with Condens. Not just to store insights, but to make stakeholder engagement actually happen as the research unfolds. Here’s what that looks like in practice: 𝗦𝘁𝗮𝗸𝗲𝗵𝗼𝗹𝗱𝗲𝗿 𝗙𝗮𝗻𝘁𝗮𝘀𝘆 𝗟𝗲𝗮𝗴𝘂𝗲 Set up a leaderboard: +1 point: attends a session +2: submits a question +3: shares a takeaway Track it in Condens. Celebrate the MVP. 𝗖𝗹𝗶𝗽 𝗥𝗼𝘂𝗹𝗲𝘁𝘁𝗲 Drop a random 30-second highlight from Condens into Slack. Ask: “What would you build based on this?” Best answer gets pinned. 𝗜𝗻𝘀𝗶𝗴𝗵𝘁 𝗕𝗶𝗻𝗴𝗼 Build a bingo board with your most common tags in Condens: “User skipped onboarding” “Trust issue” “I guess I expected it to…” Let stakeholders fill it in during playback. It’s research, gamified. 𝗧𝗵𝗲 𝗦𝘁𝗮𝗸𝗲𝗵𝗼𝗹𝗱𝗲𝗿 𝗦𝗼𝘂𝗻𝗱𝗯𝗼𝗮𝗿𝗱 Use Condens clips + emoji reactions in Slack: 👍 = makes sense 👀 = didn’t expect that 💡 = sparked something Engagement without a meeting 𝗦𝘆𝗻𝘁𝗵𝗲𝘀𝗶𝘀 𝗣𝗮𝗿𝘁𝘆 Host a 30-min co-synthesis jam. Highlight a few clips in Condens. Play music. Invite reactions. Low-stakes, high-reward collaboration. 𝗦𝘁𝗮𝗸𝗲𝗵𝗼𝗹𝗱𝗲𝗿-𝗮𝘀-𝗨𝘀𝗲𝗿 𝗗𝗮𝘆 Have a stakeholder narrate their experience using the product. Upload their recording to Condens. Compare it to real user clips. Perspective unlocked. These are systems for participation and Condens is the infrastructure that makes them possible, fast, flexible, and friction-free. If you want stakeholders to care, stop sending them links. Start giving them reasons to show up. Check out five other ways I engage stakeholders through the research process below. What’s the most creative thing you’ve done to get stakeholders involved?

In the past few months, we've worked with partners who've run into the same challenge with AI adoption. They rolled out policies or guidelines without bringing people into the conversation first—no workshop, no consensus building, just documents that needed signatures or implementation. Unsurprisingly, the result was frustrated staff expected to enforce or follow rules they had no part in creating, and leaders facing resistance instead of adoption. Both AI policies and guidelines are critical for responsible AI adoption, but they have to be built intentionally, with stakeholders driving consensus, or they most likely won't work. After working with hundreds of districts, we've created the resource below. Here are the best practices we recommend. Policies are your compliance layer and are designed to protect your district. We suggest adaptations to existing: ✔️ Acceptable use policies ✔️ Data privacy/FERPA protections ✔️ Academic integrity standards ✔️ Cyberbullying policies (to add deepfakes) Guidelines are your change management layer. They are the "why" that brings people along. We recommend including the following in your AI guidelines: 💡 Vision for GenAI adoption across your district 💡 GenAI misuse/academic integrity response protocols 💡 GenAI chatbot and EdTech tool vetting processes 💡 Digital wellbeing, data privacy, and student safety practices 💡 Implementation tips and instructional supports 💡 AI Literacy training opportunities and expectations What matters most is that both policies and guidelines should be built with stakeholders, not handed down to them. They should evolve with feedback, evidence of impact, and technical advancements. In all of our guideline and policy development work, we always start with AI literacy. It's important to build foundational understanding across stakeholders so that when policies and guidelines are developed, people can contribute meaningfully to the process and understand the "why" behind what they're being asked to implement. Intentional stakeholder engagement isn't a nice-to-have. It's what we've seen drive adoption. #AIforEducation #GenAI #ChangeManagement #AI

The easiest part of building #optimization and #decisionintelligence solutions is writing the code. Yet, I've found few references dealing with the more critical parts of successfully delivering the right solution. Here's my step-by-step approach to increasing the likelihood of delivering a solution with high business impact. 1) Understand the business process: Expanding your view from the problem presented to the process in which it is embedded allows for more holistic solutions and de-risks solving the wrong problem. 2) Interviews with business users and stakeholders: Understanding how users perceive their business process gives a better picture of the communication flow. This is important for change management as you roll out your solution. In addition, it provides a first glimpse to assessing the client's "tech maturity" which influences how you architect your solution. 3) Present an initial solution in plain English: Write a document with a clear problem statement, a high-level description of the solution, and the expected metrics improvements without technical jargon. This serves a double function as an exercise to have mental clarity and a means to #communicate and align with stakeholders. 4) Build a "scrappy" prototype and get it to stakeholders: This is one of the best ways to keep stakeholders engaged, validate that it's on the right path, and streamline change management. The prototype should include the solution, a method to evaluate the relevant metrics, and an interface for stakeholders to interact with your solution. 5) Build a metrics tracking mechanism: Create a dashboard that will be used to review the latest performance metrics of interest so that you can clearly build the story of how your solution is improving them over time as you iterate. 6) Build a CI/CD pipeline: After the prototype's initial validation, build a pipeline that allows you to ship new releases quickly to stakeholders. Establish cadenced checkpoints and demos to get feedback and review metrics. This is an important part of your change management. 7) Pilot: Once the metric improvements have been achieved, run a pilot where you follow how your solution is used as part of the business process. Make any final necessary tweaks to secure adoption. 8) Documenting and closing: Once adoption is satisfactory, close out the project by properly documenting your artifacts for your stakeholders. Include a section identifying other potential improvements to the process and an estimate of their impact for future work. Successful projects go far beyond models and algorithms, they ensure business impact and adoption. This is how we'll make #decisionintelligence the most widely adopted #AI in business. What steps would you also include?

Are we generating content just for the sake of it? As Learning & Development professionals, we live in an exciting era where Gen AI is transforming how we create learning resources. These tools enable us to design courses, write scripts, generate videos, and even deliver personalized learning experiences at a speed and scale we’ve never seen before. But as tempting as it is to lean fully into this technology, we must remember that the success of any learning solution depends not just on how quickly it’s created but on whether it solves the right problem. Without this context, even the most innovative AI-driven solution can fall flat. The benefits of Gen AI are undeniable. It allows us to produce content quickly, freeing up time for more strategic work. It opens doors to personalization, tailoring learning materials to the unique needs of individual learners. However, these advantages can also lure us into a dangerous trap: focusing on the efficiency of creation rather than the effectiveness of the solution. This is why context matters. Before we dive headfirst into content creation, we need to step back and consider the bigger picture. Is the problem we’re trying to solve rooted in a lack of knowledge, skills, or motivation? Or are there systemic or cultural issues at play that a training program alone cannot address? Understanding the root cause is critical. Also a one-size-fits-all solution—no matter how polished or innovative—will fail to resonate if it doesn’t align with their goals, challenges, and work environments. It’s equally important to ensure that learning initiatives align with organizational priorities. A solution that doesn’t support broader business goals or long-term strategy risks being a wasted effort. Finally, we must think about relevance and application: Will the learning be actionable? Can learners apply it effectively in their real-world contexts? Even the most cutting-edge Gen AI solutions will miss the mark without addressing these questions. So, how do we ensure we’re getting it right? It starts with consultation and needs analysis. Engaging stakeholders—managers, teams, and learners—can provide invaluable insights into the challenges and outcomes that matter most. Conducting a needs analysis through surveys, interviews, focus groups, or data can help identify the real gaps and priorities. Defining clear success metrics is essential to ensure the solution not only addresses the problem but delivers measurable impact. Gen AI can then be used as a powerful tool to create drafts and prototypes, but these must be refined through your expertise, learner feedback, and pilot testing. Generative AI is a game-changer, but it’s not a shortcut to meaningful learning. As L&D professionals, our true value lies in crafting solutions that drive real impact and require us to lead with strategy, not technology, focusing on the why first and not the how. #AI #learning

To mitigate harm and improve EdTech, start by listening to teachers! - That is the big takeaway on the use of AI in education from this new research. “Teachers have to be on board. And teachers’ input about their students is supremely important in creating these tools. Because if a teacher is not bought in, they are not going to use it with fidelity… So yes, I get principal buy-in and support is important. But do not forget the teachers… The teachers are supremely important in making all of this happen. So listen to them” (pp. 14). The paper from Cornell University, "Do not Forget the Teachers: Towards an Educator-Centered Understanding of Harms from Large Language Models in Education", makes one thing clear. AI in education will only succeed if teachers are part of the process from the beginning. Too often, AI tools are designed without considering how teachers and students will actually interact with them. This research highlights a clear disconnect. EdTech companies focus on technical risks such as bias, privacy, and hallucinations. Teachers are more concerned about the long-term impact on student learning, teacher workload, and equity. One of the key findings is that AI tools should be designed with teacher input from the start, not added as an afterthought. Teachers need the ability to shape AI tools based on their real-world classroom experiences and provide direct feedback on how students are engaging with them. If we want AI to truly enhance education, we need a fundamental shift toward educator-centered AI governance. That means: - Teachers involved in AI tool design and development. - AI tools built to align with evidence-based teaching practices. - School leaders ensuring teachers have the final say in how AI is used in their classrooms. Thank you to the authors, Emma Harvey, Allison Koenecke, and Rene Kizilcec of Cornell University The research was shared by Ben Williamson from The University of Edinburgh. Link to download the paper in the first comment. #aiineducation #edtech #teachers #educationpolicy #aigovernance

𝐓𝐡𝐞 𝐇𝐢𝐝𝐝𝐞𝐧 𝐏𝐨𝐰𝐞𝐫 𝐨𝐟 𝐒𝐭𝐚𝐤𝐞𝐡𝐨𝐥𝐝𝐞𝐫 𝐄𝐧𝐠𝐚𝐠𝐞𝐦𝐞𝐧𝐭 One of the biggest lessons in my career came from an initiative that failed—not because the idea was bad, but because we didn’t listen to the right voices. I was leading a bold innovation initiative, and we were taking an unconventional approach to bring a new product to market. Our team had strong conviction, purpose, and a consumer-first mindset, but these things also gave us a false sense of confidence. We discounted advice from stakeholders—partly because we thought we knew better and partly because we didn’t like what we were hearing. In the end, the initiative failed for the very reasons we ignored. The problems—and potential solutions—were there all along; we just weren’t listening. From that point on, I made stakeholder engagement a cornerstone of my leadership toolbox. I learned to not just accept it, but to seek it out— from the board to the teams on the front lines. It became a secret weapon because many leaders overlook it, and even those who attempt it often miss its true potential. It’s about more than just listening—it requires openness to act on new (and sometimes inconvenient) perspectives and a willingness to change your mind. The benefits of stakeholder engagement are numerous, especially when it comes to strategic planning. It can help drive: 𝐌𝐨𝐫𝐞 𝐃𝐢𝐯𝐞𝐫𝐬𝐞 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬: Stakeholders, whether internal or external, offer unique perspectives that can help uncover blind spots in strategy. Their input can highlight risks or opportunities that leadership alone might not see. 𝐒𝐭𝐫𝐨𝐧𝐠𝐞𝐫 𝐁𝐮𝐲-𝐈𝐧: When stakeholders feel included in decision-making, they’re more likely to support the strategy. Engaging key decision-makers and those responsible for execution early helps mitigate resistance and creates a sense of ownership. 𝐈𝐧𝐜𝐫𝐞𝐚𝐬𝐞𝐝 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧: Engaging stakeholders promotes cross-functional collaboration, ensuring alignment between functions like finance, marketing, R&D, and sales to drive execution excellence. 𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐝 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧: Effective stakeholder engagement involves more than gathering input. It requires maintaining two-way communication to keep stakeholders aligned with the organization’s goals throughout strategy development and execution. 𝐖𝐚𝐧𝐭 𝐭𝐨 𝐮𝐩 𝐲𝐨𝐮𝐫 𝐠𝐚𝐦𝐞 𝐰𝐢𝐭𝐡 𝐲𝐨𝐮𝐫 𝐬𝐭𝐚𝐤𝐞𝐡𝐨𝐥𝐝𝐞𝐫𝐬? 𝐋𝐞𝐭’𝐬 𝐭𝐚𝐥𝐤. Together, we can create a custom, AI-powered plan to accelerate decision-making and drive stronger results. www.avenirstrategies.net #StakeholderEngagement #StrategicPlanning  #Leadership #Innovation #CPG #FMCG