Human First but AI Ready: Finding the Right Balance in Learning Design
August 26 & 27, 2026 • All Online
As AI capabilities expand, learning professionals face increasingly complex decisions about when to rely on automation and when human expertise is critical. Successfully integrating AI requires more than learning new tools; it requires thoughtful decisions about quality, trust, accessibility, and the human connections that support meaningful learning experiences.
In this six-session online conference, you’ll explore practical approaches to integrating AI into learning design and gain a clearer understanding of where automation adds value, where human judgment is essential, and how to balance both in your own work.
You’ll walk away with strategies to:
- Leverage AI effectively while retaining human judgment in critical areas
- Use AI safely in highly regulated or secure contexts
- Integrate AI into professional coaching without losing the human connection
- Streamline development with Articulate’s AI Assistant without compromising quality or accessibility
Connect and exchange ideas with other attendees! At the end of each day, you’ll be invited to gather in small groups in our ThinkSpaces to reflect on key ideas from the sessions, share perspectives, and explore how you’ll apply what you’ve learned.
Program
DAY 1: August 26
101: Cognitive Design for AI-Powered Learning
Shreya Gupta, Amazon
11:30 AM – 12:30 PM ET / 8:30 AM – 9:30 AM PT
As generative AI makes learning production effortless, capability development is no longer automatic. Rather, it must be intentionally designed. Many teams are accelerating content creation using AI. Far fewer are evaluating how those design decisions shape independent thinking, transfer, and mastery over time.
This session introduces the Cognitive Design Model, a practical decision framework that helps learning leaders determine when to automate, when to augment thinking, and when to preserve cognitive effort. you will learn to evaluate AI-enabled learning decisions using three criteria (STM):
Learn more.
201: Speed & Quality? Achieve Both with AI Assistant in Articulate Storyline & Rise
Rose Kapucu, AdventHealth
Supriya Chaudhari, AdventHealth
1:00 PM – 2:00 PM ET / 10:00 AM – 11:00 AM PT
Instructional designers are under pressure to create more learning content in less time while maintaining quality, accessibility, engagement, and compliance. The AI Assistant tool can accelerate development in Articulate Storyline and Rise, but many teams struggle with inconsistent outputs, weak instructional quality, accessibility issues, governance concerns, and inefficient workflows.
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301: Diagnose, Then Design: Using AI to Close the Gaps Training Alone Can’t Fix
Allegra Robinson, Northern Bank
2:30 PM – 3:30 PM ET / 11:30 AM – 12:30 PM PT
Most performance problems get diagnosed as a knowledge, skill, or will gap. But what happens when employees already know what to do, can do it, and want to do it and the behavior still doesn’t change? The missing piece is access: the workflows, systems, and environmental conditions that make the right behavior easy or hard. Traditional diagnosis misses it. And when we skip it, we keep prescribing training for problems training can’t fix.
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DAY 2: August 27
401: Tame SME Chaos with an Efficient AI? Powered Workflow
Rebecca DiMeo, Yale University
11:30 AM – 12:30 PM ET / 8:30 AM – 9:30 AM PT
Instructional designers regularly face the same challenge: SMEs provide a flood of information but little clarity about what learners actually need to do on the job. Designers must sort through excessive detail, conflicting priorities, and vague outcomes, slowing project design while increasing rework and weakening stakeholder alignment.
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501: Getting Real About AI in Professional Coaching: What to Do & What to Avoid
Olivia Savage, Mars Snacking
1:00 PM – 2:00 PM ET / 10:00 AM – 11:00 AM PT
Many learning professionals are being asked to “use AI” without a lot of guidance on what that actually looks like in practice. This session presents an honest answer to that question.
In this case study, we will explore how I integrated AI tools into a coaching program designed for small business owners in the early stages of launching their businesses. These were people with big dreams and a lot of uncertainty, and we wanted to see if AI could help extend the reach and impact of human coaching without losing what makes coaching work in the first place.
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601: Use AI Effectively & Safely in High-Risk Environments
Kevin Pledger, Lawrence Livermore National Laboratory
2:30 PM – 3:30 PM ET / 11:30 AM – 12:30 PM PT
As AI tools become increasingly integrated into learning design workflows, many organizations are focusing on what AI can do, often overlooking the more critical question of what it should do. When instructional decisions carry real consequences, the use of AI introduces not just opportunity, but risk, especially when accountability cannot be delegated.
Learn more.
101: Cognitive Design for AI-Powered Learning
11:30 AM – 12:30 PM ET / 8:30 AM – 9:30 AM PT Wednesday, August 26
- Stakes: How costly is error in this task?
- Transfer: Does capability need to extend beyond the immediate task?
- Mastery: Is long-term expertise required for sustained performance?
Through structured scenario analysis, live decision mapping, and guided redesign exercises, you will apply the model to decisions affecting AI-assisted content drafting, assessment generation, feedback automation, learner use of AI for synthesis, and performance support design. You will redesign one AI-enabled learning flow to strengthen independent reasoning rather than unintentionally weaken it.
This session is not about resisting AI. It is about designing AI-powered learning that builds durable expertise.
You will learn how to:
- Apply the Stakes-Transfer-Mastery model to evaluate AI use cases in learning design
- Distinguish between automation that accelerates performance and automation that undermines mastery
- Identify risks such as cognitive offloading, automation bias, and fluency illusion in AI-supported learning
- Redesign AI-enabled learning experiences to preserve depth of capability
Shreya Gupta
Learning and Development Program Manager
Amazon
Shreya Gupta is a Learning and Development Program Manager with 9 years of experience, including 7 years in enterprise learning strategy and instructional design. She has led large-scale learning transformations across 10+ global business units, supporting complex, distributed workforces. At Amazon, she contributed to AI-enabled learning solutions that accelerated program launches and strengthened performance ecosystems. She is a peer reviewer for the Academy of Management (AOM) and has spoken at the Amazon LXD Conference, IDTX Conference, and other industry forums. Her work focuses on designing future-ready learning systems that balance innovation with long-term capability development.
201: Speed & Quality? Achieve Both with AI Assistant in Articulate Storyline & Rise
1:00 PM – 2:00 PM ET / 10:00 AM – 11:00 AM PT Wednesday, August 26
This session demonstrates real-world workflows for integrating AI Assistant into Storyline and Rise without sacrificing instructional integrity. Grounded in our real-world experimentation, we’ll provide practical guidance on using AI Assistant in quiz creation, storyboard development, branching scenarios, narration, image generation, localization, and accessibility support, as well as using AI Avatars and AI Tutor. We will highlight both successful implementations and failed attempts to show where AI adds value, where human oversight remains essential, and how to establish scalable quality-control processes. You will engage in prompt critiques and workflow redesign activities while reviewing Storyline examples, Rise templates, and governance checklists.
You will leave with:
- Tools, templates, prompting strategies, and quality-control processes you can use immediately
- The ability to balance enthusiasm for AI-assisted development with realistic application of governance and human oversight
Rose Kapucu
Instructional Designer III
AdventHealth
Rose Kapucu is a Senior Instructional Designer and Developer with more than 20 years of experience creating innovative learning solutions in healthcare, higher education, and corporate environments. She currently works at AdventHealth, developing enterprise-scale eLearning for more than 90,000 employees using Articulate Storyline 360 and Rise. Her expertise includes interactive course design, accessibility, multimedia production, instructional technology, and AI-assisted learning workflows. Rose is also a member of AdventHealth’s AI Champion group, supporting organizational AI adoption, responsible AI practices, and workforce education related to emerging AI technologies. She has led initiatives involving AI onboarding, ChatGPT Enterprise training, accessibility standards, and enterprise learning design practices. She collaborates with executives, subject matter experts, and learning leaders to develop learning solutions aligned with organizational goals and performance outcomes. Her specialties include instructional design methodologies, adult learning theory, WCAG accessibility standards, copyright compliance, gamification, and AI-assisted content creation. Rose has presented at national and state conferences on instructional technologies, digital tools, and online learning practices. Her background provides practical insight into AI implementation in Storyline and Rise, with a focus on governance, accessibility, and real-world enterprise learning development.
Supriya Chaudhari
Instructional Designer II
AdventHealth
Supriya Chaudhari is an experienced instructional designer and eLearning developer with more than 15 years of experience creating engaging, performance-driven learning solutions for healthcare, higher education, corporate, and international audiences. At AdventHealth, she develops enterprise-scale eLearning for over 90,000 employees using Articulate Storyline 360 and Rise, specializing in interactive learning design, accessibility, and multimedia production. She partners with stakeholders and subject matter experts to analyze content, create storyboards and scripts, and build scalable web-based training programs grounded in adult learning principles and modern instructional design methodologies. Her background includes healthcare, finance, safety, compliance, mobile learning, LMS administration, project management, and team collaboration. Supriya also brings practical expertise in AI onboarding and ChatGPT Enterprise training, with a focus on integrating AI into eLearning workflows. Her work emphasizes real-world application, gamification, learner engagement, scalability, and balancing innovation with compliance and organizational needs in large enterprise environments
301: Diagnose, Then Design: Using AI to Close the Gaps Training Alone Can’t Fix
2:30 PM – 3:30 PM ET / 11:30 AM – 12:30 PM PT Wednesday, August 26
This session draws from real-world application in a financial services environment to explore how to use AI as a reasoning partner in performance diagnosis. Throughout the session, you will work through a four-part framework, apply it to a real challenge from your own organization, and leave with a clearer picture of what’s actually blocking performance and what kind of intervention will actually help.
You will learn to:
- Diagnose performance gaps more accurately using a Knowledge, Skill, Will, and Access framework
- Identify hidden access barriers that training alone cannot fix
- Use AI to pressure-test a diagnosis and surface root causes you might otherwise miss
- Decide with more confidence whether training is the right solution
Allegra Robinson
Learning & Development Specialist
Northern Bank
Allegra Robinson is a Learning & Development Specialist at a regional bank, where she designs onboarding and development programs focused on real behavior change. She came to corporate L&D after years leading hiring, training, and onboarding in high-volume restaurant environments which gave her a deep appreciation for learning that works when people are busy, distracted, and just trying to get through the day. Allegra’s work is grounded in diagnosing what’s actually blocking performance before reaching for a training solution. She regularly uses AI as a reasoning partner in that diagnostic process not as a shortcut, but as a thinking tool and has applied the Knowledge, Skill, Will, and Access framework across onboarding, retail operations, and leadership development initiatives. She’s opinionated about where AI genuinely helps and where human judgment still has to lead, and she brings that honest, practical perspective to everything she facilitates.
401: Tame SME Chaos with an Efficient AI? Powered Workflow
11:30 AM – 12:30 PM ET / 8:30 AM – 9:30 AM PT Thursday, August 27
This practical session introduces an AI-powered workflow for transforming unstructured SME input into a clear, usable learning blueprint while keeping instructional judgment firmly in human hands. Using real-world case examples, the session demonstrates how AI can be applied at three key points:
- Preparing stronger SME interview questions
- Analyzing raw intake materials after meetings
- Drafting a structured design brief that aligns business goals, learner needs, and instructional strategy
We will examine examples of AI outputs that worked well and those that missed the mark to highlight common pitfalls, lessons learned, and best practices. You will practice identifying gaps, challenging assumptions, and using instructional design principles to refine AI?generated analysis. We will emphasize transferable prompts, review strategies, and safeguards that you can apply across tools and organizations. You will leave with a repeatable, scalable approach that reduces analysis time, improves clarity early in projects, and supports better learning design decisions.
You will learn to:
- Generate stronger SME interview questions using AI Convert unstructured inputs into a draft learning design brief
- Distinguish essential vs. non-essential content using AI analysis
- Apply a human review checklist to validate AI output
Rebecca DiMeo
Technology Training Consultant
Yale University
Rebecca DiMeo is a Technology Training Consultant at Yale Medicine, where she helps clinical and administrative teams make sense of complex technology and use it confidently in their day-to-day work. With over 10 years of experience in instructional design, higher education, and technology training, she specializes in designing practical, human-centered learning experiences that actually stick. Rebecca holds a Master of Arts in Teaching and a Bachelor’s degree in English Literature, and she brings a strong foundation in adult learning, storytelling, and communication to every project. Her work spans eLearning development, blended learning, onboarding, and large-scale platform implementations. Lately, she’s been experimenting with AI-enhanced workflows using generative AI to streamline content creation, evaluation, and administrative work and helping L&D teams think realistically about how AI fits into their practice. She’s especially passionate about reducing friction for learning professionals, building AI literacy, and helping organizations prepare their workforce for what’s coming next.
501: Getting Real About AI in Professional Coaching: What to Do & What to Avoid
1:00 PM – 2:00 PM ET / 10:00 AM – 11:00 AM PT Thursday, August 27
We will examine what worked really well and what didn’t. I will share outcomes that surprised us as I walk through our design decisions and show where we saw genuine value, where AI fell short, and what we would do differently. You’ll map your own programs against an AI-readiness framework and receive a downloadable AI Coaching Integration Checklist, a practical one-page tool that walks through key questions to ask.
You will leave with:
- A realistic picture of what AI-assisted coaching can and cannot do
- Practical design principles for building AI into a coaching without losing the human connection
- A framework for identifying which parts of your coaching are good candidates for AI support
- Honest lessons learned that can save you time, budget, and frustration if you are exploring something similar
Olivia Savage
Manager, Learning and Development
Mars Snacking
Olivia Savage has spent over 20 years doing work she genuinely loves: helping people and organizations learn, grow, and show up better. She’s brought that passion to some pretty well-known places, including Nestl , Disney, Kellogg’s, and Mars, where she’s designed and led learning programs that actually stick. She’s also the author of two books, The Leadership Pivot and The Human Brand, which came out of years of watching what separates good leaders from great ones. Spoiler: it’s rarely the strategy. Outside of her corporate work, Olivia runs her own nonprofit and knows firsthand what it feels like to build something from scratch. That experience as a small business owner keeps her grounded and gives her a real appreciation for the people she coaches who are doing the same thing. She believes learning works best when it’s honest, practical, and a little bit human. This session is all three.
601: Use AI Effectively & Safely in High-Risk Environments
2:30 PM – 3:30 PM ET / 11:30 AM – 12:30 PM PT Thursday, August 27
This session explores the practical boundaries between human decision-making and AI-supported work in instructional design. It introduces a clear distinction between traditional automation and generative AI and examines how each can be used effectively without compromising accuracy, compliance, or defensibility. Grounded in experience across military, education, and DOE-aligned training environments, this session focuses on the realities of designing training in high-consequence, regulated contexts where decisions must be auditable and outcomes must be defensible. Through real-world examples and contrasting use cases, we will explore where AI can act as a true force multiplier, where it introduces hidden risks, and how to distinguish between the two.
You will:
- Understand the safe use of AI in highly regulated contexts
- Distinguish between effective and potentially risky uses of AI in learning design
- Apply a practical framework for evaluating when and how AI might be used appropriately and which elements must remain human-owned
Kevin Pledger
Training Specialist
Lawrence Livermore National Laboratory
Kevin Pledger is a Technical Training and Development Specialist supporting national security programs, with over fifteen years of experience designing training in high-consequence, regulated environments. His background spans the U.S. Navy’s nuclear program, K 12 education, and DOE-aligned training, where instructional decisions must be accurate, defensible, and auditable. He integrates both traditional automation and generative AI into instructional design workflows while maintaining compliance and accountability. His current focus is on defining where AI can effectively accelerate learning design and where its use introduces unacceptable risk.