Agenda – 17 September 2026

Six months ago we asked whether your organization was ready for AI in professional learning. Today we move past that question entirely. Paul Siegel opens the September Summit with a direct assessment of where enterprise AI adoption in learning actually stands — what is working, what is failing, and why the organizations in this room are now ready to go deeper.

— Understand what has changed in enterprise AI learning since May, and why the implementation conversation is the most important one happening in L&D right now.

— Get a clear picture of the day ahead — the sessions, the speakers, and the single most important decision every enterprise needs to make about AI in learning before the end of 2026.

— Hear directly from Starweaver's Founder on what the data and market signals from the last six months reveal about which organizations are pulling ahead and which are falling dangerously behind.

Six months ago we asked whether your organization was ready. This keynote does not ask that question again — it assumes you have started, and now examines what separates organizations that are implementing AI in learning effectively from those stuck in pilot paralysis. This is a frank, evidence-based assessment of where enterprise AI adoption in professional education actually stands, what is working, what is failing, and what the most forward-thinking organizations are doing differently.

— Examine the most common implementation failures organizations are experiencing with AI in learning, including where well-intentioned strategies are breaking down at the point of execution.

— Explore the organizational conditions — leadership alignment, data infrastructure, change management — that determine whether AI learning investments deliver transformational results or expensive disappointment.

— Leave with a clear-eyed view of what a mature AI learning organization looks like by 2028 and the specific capability gaps most enterprises need to close to get there.

AI agents are no longer a future scenario — they are active inside enterprise training functions right now, handling tasks that previously required instructional designers, learning administrators and content managers. This session examines what autonomous AI agents are actually doing inside L&D teams today, what that means for team structure and skills, and how organizations are managing the transition without losing the human expertise that makes enterprise learning credible.

— Understand the specific L&D workflows where AI agents are delivering the greatest impact today, from automated content curation and learner progress monitoring through to intelligent intervention and skills gap detection.

— Explore how forward-thinking L&D teams are restructuring around AI agent capabilities — not replacing human roles but redefining them around higher-order judgment, relationship management and strategic design.

— Learn how to introduce agentic AI into your learning function in a way that builds team confidence rather than triggering resistance, with practical change management approaches drawn from real enterprise deployments.

Every enterprise faces the same question when it comes to AI in learning: do you build proprietary systems, buy off-the-shelf platforms, or partner with specialist providers who bring both technology and content at scale? Most organizations are getting this decision wrong — either over-investing in custom builds that take too long, or under-investing in generic tools that do not reflect their business context. This session provides a practical decision framework built from real enterprise experience.

— Understand the true total cost of ownership for each approach — build, buy and partner — including the hidden costs of integration, maintenance, content quality and expert access that most procurement decisions undercount.

— Explore how leading organizations are using a hybrid model — buying infrastructure, partnering for content and expert networks, and building only the proprietary elements that represent genuine competitive differentiation.

— Learn how to present the build-buy-partner decision to your board or executive team with a business case framework that accounts for speed to value, scalability, risk and long-term strategic fit.

As AI becomes embedded in learning systems across banking, healthcare, government and professional services, the governance question has moved from the compliance team's inbox to the boardroom agenda. Data privacy, algorithmic bias, regulatory compliance and auditability are no longer theoretical risks — they are active concerns shaping procurement decisions, vendor relationships and organizational liability. This session gives enterprise leaders a practical governance framework they can begin implementing immediately.

— Understand the current regulatory landscape affecting AI in enterprise learning across key sectors including financial services, healthcare, pharmaceuticals and government, and what compliance requirements are already in force versus those arriving in the next 24 months.

— Explore the specific governance structures — policies, audit trails, human oversight mechanisms and vendor accountability frameworks — that leading enterprises are putting in place to manage AI learning systems responsibly at scale.

— Learn how to turn AI governance from a compliance burden into a competitive advantage, using transparency and accountability as differentiators when competing for talent and enterprise partnerships in heavily regulated industries.

The most important workforce challenge facing enterprises today is not replacing jobs that AI is eliminating — it is preparing people for roles that do not yet formally exist. The skills, mindsets and capabilities required for the AI-augmented workforce of 2028 are already becoming visible, but most organizations are still designing learning programs for a workforce model that is rapidly becoming obsolete. This session examines what we know about the emerging workforce, how organizations are beginning to future-proof their talent pipelines, and what L&D must do now to stay ahead of the curve.

— Explore the emerging job families and skill clusters that labor market data and AI adoption trends suggest will define the enterprise workforce by 2028, and what that means for skills gap analysis and learning investment priorities today.

— Understand how leading organizations are using AI-powered career pathing and upskilling maps to give individual employees a credible, personalized route from their current role to the roles their organization will need in three to five years.

— Learn how to build a future workforce learning strategy that balances immediate upskilling priorities with longer-horizon capability development, making the case to leadership for investment that pays off beyond the next annual budget cycle.

The implementation playbook becomes real in this live demonstration of Boostr — Starweaver's process automation and analytics platform built specifically for enterprise learning operations. This is not a slide deck walkthrough. This is a live demonstration showing how organizations are eliminating manual workflows, accelerating content management and getting the reporting visibility their leadership teams demand — without rebuilding their existing infrastructure.

— See Boostr's content and process management tools in action, including automated production tracking, delivery reporting and workflow optimization across large-scale learning operations.

— Watch a live walkthrough of Boostr's analytics and visualization dashboards, showing how enterprise L&D leaders are getting real-time visibility into content performance, team productivity and learner outcomes.

— Explore how Boostr's streams and messaging capabilities keep distributed content teams, subject matter experts and stakeholders aligned — reducing the coordination overhead that slows down even the best-resourced L&D functions.

Paul Siegel closes the September Summit — and the full 2026 AI in Professional Education Summit series — with a synthesis of the day's most critical insights and a direct challenge to every organization in the room. This is not a passive wrap-up. It is a call to action and an invitation to keep building.

— Leave with the three most important implementation decisions to make in your organization in the next 30 days, drawn directly from everything covered across both summits in 2026.

— Discover how Starweaver's full platform suite

— Journeybuilder, Boostr and Starweaver Analytics — can accelerate your organization's AI learning implementation starting this quarter.

— Join the Starweaver Expert Network, connect with fellow enterprise L&D leaders in the virtual networking room, and book a direct conversation with the Starweaver team before you leave today.