Picture this: your L&D manager asks an AI to create a compliance assessment for 5,000 employees. Instead of generating a basic quiz, the system analyzes your existing training materials, checks regulatory requirements, builds role-specific question banks, and schedules deployment — all while the manager grabs coffee. That’s the difference between AI agents and the chatbots most learning platforms are peddling as innovation.
During my recent conversation with Sammir Inamdar, CEO of Enthral.ai, and Asma Shaikh, Managing Director, I witnessed this distinction firsthand. While demonstrating their platform to our team at Brandon Hall Group™, they showed how their AI agent Craft didn’t just respond to commands — it executed complex workflows autonomously. As someone who evaluates dozens of learning platforms annually, I can tell you this level of sophistication remains rare in 2025, though granted, not for much longer.
The Learning Platform Market’s AI Reality Check
While every vendor claims AI leadership, most have simply bolted chatbots onto legacy architectures. Organizations investing millions in digital transformation deserve better than surface-level automation masquerading as intelligence.
Today’s leading platforms each bring distinct approaches, though with notable constraints:
Adobe Learning Manager
- Leverages Adobe Sensei for content recommendations and learning paths
- Strong integration with Creative Cloud for content development
- Requires significant investment in the broader Adobe ecosystem for full efficacy
- AI capabilities primarily focused on content discovery
Absorb LMS
- Strategic learning system with AI-driven insights
- Create AI tool assists with course development
- Serves large enterprises with complex compliance needs
Docebo
- Skills Graph technology maps content to competency development
- Strong marketplace approach with pre-built content
- AI features require investiment in additional modules
Cornerstone OnDemand
- Extensive talent management suite beyond learning
- AI powers skills inference and career pathing
- Complex implementation often requiring consulting support
- Better suited for full HR transformation than standalone learning
TalentLMS
- TalentCraft AI simplifies course creation for small to mid-sized businesses
- User-friendly interface with quick deployment
- AI capabilities limited compared to enterprise platforms
- Lacks advanced features for complex organizational structures
360Learning
- Collaborative learning approach with peer-generated content
- AI assists in content curation and quality control
- Focused primarily on collaborative rather than formal learning
- May not meet compliance-heavy industry requirements
Where Agentic AI Changes the Game
Enthral.ai’s approach differs fundamentally from these competitors through the use of true agentic AI—autonomous agents that complete complex tasks without constant human oversight. Here’s what sets their implementation apart:
Multiple Specialized Agents Working in Concert
- Izzy handles general platform navigation and support queries
- Craft autonomously creates assessments from documents, videos, or existing content
- Role-play agents deliver personalized sales coaching at scale
- Each agent specializes in specific workflows while sharing context seamlessly
Cost-Effective Custom AI Avatars
- Organizations create branded AI coaches matching their culture
- Avatar-based simulations cost under $0.50 per minute versus $1-2 for competitors
- Behavioral customization allows aggressive customers or empathetic doctors
- Multi-language support with accent variations for global deployment
True Workflow Automation Beyond Content
- Agents handle end-to-end processes like assessment creation, deployment, and analysis
- On-the-job training verification through AI-reviewed video submissions
- Automated skill gap identification triggering personalized development paths
- Integration with performance management for closed-loop talent development
Organizations Primed for Autonomous Learning Platforms
Based on my analysis of Enthral.ai’s client base and platform capabilities, several organization types stand out as ideal customers:
Global Manufacturing and Retail Operations (10,000+ employees)
- Complex compliance requirements across multiple jurisdictions
- Frontline workers needing mobile-first, multilingual training
- High turnover requiring rapid, consistent onboarding at scale
- Key benefit: AI agents handle localization and compliance mapping automatically
Financial Services and Insurance Companies
- Extensive partner networks requiring consistent certification (like SBI Life’s 250,000 users)
- Sales teams needing continuous product knowledge updates
- Regulatory training with audit trail requirements
- Key benefit: AI-powered proctoring ensures assessment integrity without physical oversight
Technology and Professional Services Firms
- Rapid skill evolution requiring continuous upskilling
- Project-based learning tied to client engagements
- Knowledge workers expecting consumer-grade learning experiences
- Key benefit: AI analyzes project requirements to recommend just-in-time learning
Healthcare and Pharmaceutical Organizations
- Strict compliance standards (21 CFR Part 11 for pharma)
- Role-specific competency requirements
- Need for validated learning processes
- Key benefit: AI ensures regulatory compliance while personalizing clinical education
Multi-Brand Conglomerates or Franchise Operations
- Diverse business units with unique training needs
- Decentralized administration with central oversight
- Mix of corporate and franchisee employees
- Key benefit: Multi-tenant architecture allows customization within governance frameworks
The Strategic Reality of AI-Powered Learning
Enthral.ai’s position as a bootstrapped, profitable company pursuing funding presents an interesting market dynamic. Unlike venture-backed competitors racing to show growth at any cost, they’ve built sustainable technology over multiple years. Their claim of implementing AI capabilities 2.5 years ahead of the market appears credible based on the sophistication I observed.
However, adoption challenges remain real. As Sammir acknowledged, only 4,000 of one customer’s 250,000 users actively engage with AI features. This reflects broader market hesitation around data security and organizational readiness rather than technology limitations. The platform’s perceived complexity — which both executives acknowledged — may also slow initial adoption despite AI agents simplifying actual usage.
The ability to deploy on customer clouds addresses security concerns while their flexible commercial model (per-use, active user, or subscription) reduces barriers to entry. More importantly, their approach to building on existing systems rather than requiring wholesale replacement acknowledges the reality of enterprise technology landscapes.
Looking ahead, the learning platform market will likely differentiate between vendors offering surface-level AI features and those delivering true autonomous capabilities. Enthral.ai’s native AI architecture positions them well for this shift, particularly as organizations move beyond pilot programs to scaled implementations. Their biggest challenge may be educating a market that doesn’t yet fully understand the technology.
For learning leaders evaluating platforms in 2025, the question isn’t whether you need AI —it’s whether you need AI that merely responds or AI that truly works. Based on what I’ve seen, Enthral.ai belongs firmly in the latter category, even if the market needs time to catch up to that distinction.
