HRTech Interview with Doug Stephen, President, CGS Immersive

Doug Stephen, President, CGS Immersive chats to us at HRTech Series to discuss the changing scope of HR amidst the impact of AI powered HRTech systems:

____________

Tell us about yourself and more about Cicero’s new unified AI platform.

As president of CGS Immersive, my team and I help global enterprises modernize workforce readiness through applied technology; not just “tech for tech’s sake.” At enterprise scale, the hard part isn’t the pilot; it’s repeatable performance improvement that holds up across regions, roles, and real-world constraints.

That “performance-first” mindset is exactly why we expanded Cicero roleplay into a unified AI platform. It’s a single, governed environment that connects hiring, learning, coaching, assessment, analytics, and XR collaboration, so organizations can build capability in a closed loop from practice to feedback to measurement to improvement.

A few practical details about the new platform that matter to HR and L&D leaders:

• Speed to value: design and deploy lifelike roleplays company-wide in as little as 15 minutes.
• Realism that drives adoption: in a 2025 evaluation at Medtronic, Cicero was one of the most popular AI roleplay tools piloted, driven by strong roleplay mechanics and a memorable learning experience.
• Enterprise trust: Cicero is designed not to collect PII data and is built to support rigorous security and governance requirements (including alignment to widely recognized ISO/IEC standards) and is on plan for ISO 42001 in early March. It is the first international standard providing a certifiable framework for Artificial Intelligence Management Systems (AIMS), enabling organizations to develop and use AI responsibly, ethically, and safely.

How are AI-powered workforce management tools changing the scope of HR and leadership teams today?

AI is shifting HR from being primarily a process owner to becoming a product owner for workforce performance – designing “systems of work” where people learn faster, get answers in the flow of work, and build the human skills that automation can’t replace (judgment, empathy, influence, decision-making under pressure).

That changes what HR and leaders are measured on. The focus moves from activity metrics to outcomes like time-to-proficiency, quality-of-hire, retention, internal mobility, and manager effectiveness – with technology increasingly expected to make those outcomes measurable and repeatable.

A few market signals underscore the speed of this shift: adoption of AI in HR tasks is rising quickly year-over-year, and a significant share of HR leaders are already piloting or implementing generative AI — often without adding dedicated GenAI roles, which creates a capability gap that must be closed through upskilling and new operating rhythms.

Catch more HRTech Insights: HRTech Interview with Sandra Moran, Chief Marketing Officer of Schoox

How can enterprise brands optimize the use of AI-powered HR tech tools, and what challenges do you often see teams face during implementation?

Optimization starts with one principle: don’t “install AI”; rather, help instrument outcomes. The enterprises that win treat AI as a performance program with governance, change management, and measurement baked in.

A practical playbook:

• Start with high-friction, high-frequency moments (candidate screening consistency, manager conversations, customer interactions, safety-critical decisions).
• Build governance early: data access rules, privacy, auditability, bias monitoring, and clear lines of accountability.
• Pilot for learning, then scale for impact: define success metrics (time-to-proficiency, quality, error reduction, NPS/CSAT, etc.), run controlled rollouts, and operationalize what works.

Common implementation challenges show up consistently:

• Readiness gaps: teams adopt new AI capabilities faster than they build the internal skills to govern, prompt, enable, and redesign workflows around them.
• Data reality: inconsistent job architectures, skills taxonomies, and fragmented content repositories stall personalization and analytics.
• Adoption friction: if the experience isn’t intuitive – or if employees don’t trust the system – usage collapses.

For organizations deploying AI across learning, skilling, and hiring, how can they best balance the machine–human experience?

The best balance is simple to describe and surprisingly hard to execute: let machines scale the repeatable and let humans own the meaningful. AI can standardize, personalize, and accelerate – while humans provide context, ethics, empathy, and final accountability.

A few operating principles that work in the real world:

• Make AI explain itself. If a system recommends a candidate or flags a skill gap, leaders should see the evidence trail (what signals were used and why).
• Keep humans in the loop for high-stakes decisions. AI can structure interviews and simulations; humans still evaluate nuance, values alignment, and the candidate/employee experience.
• Use experiential practice to develop human skills at scale. Employers increasingly expect core skills to shift materially over the next few years, so continuous development is now a baseline requirement, not a perk.
• Blend modalities intentionally. Research on immersive learning shows VR learners can be trained up to four times faster and can be significantly more confident applying what they learned – evidence that “practice that feels real” is a force-multiplier.

Looking ahead, what HR tech trends do you believe will shape the market in the coming years?

From my view, I see five trends converging fast:

• Agentic AI moves from “answers” to “actions.” More systems will execute workflows (not just summarize information), increasing both productivity upside and governance requirements.
• Skills become the new operating system. Organizations that validate skills continuously – through signals, simulations, and performance data – will outpace those relying on static job descriptions.
• Scenario-based hiring and assessment becomes mainstream. As authenticity risks rise, employers will adopt more identity-verified, scenario-driven evaluation that reveals how people think and communicate, not just what’s on a resume.
• Immersive learning scales beyond pilots. The ROI conversation is shifting from “cool tech” to measurable impact: speed-to-competence, confidence, safety, quality, and retention.
• Trust, security, and standards become differentiators. Buyers will increasingly demand governed environments, auditability, and security alignment – not just model performance.

Who are five HR tech innovators (people or brands) you think deserve a shout-out, and why?

Here are five that stand out to me, each pushing the market toward more measurable, modern workforce outcomes:

• Elon Musk (Tesla/SpaceX): polarizing, but undeniably influential in driving first-principles, high-velocity execution cultures that force every leader (including HR) to rethink learning speed, productivity, and what humans plus automation can accomplish together.
• Workday: for pushing the HR suite toward skills, analytics, and AI-infused decision support at global enterprise scale.
• Microsoft: for accelerating AI in the flow of work, which is where adoption actually sticks and where coaching and knowledge must live.
• ServiceNow: for operationalizing employee experience through workflow discipline, turning HR from a ticket queue into orchestrated services.
• Eightfold AI: for pioneering talent intelligence approaches that connect skills, potential, and mobility in ways legacy systems struggled to do.*

Read More on Hrtech : Return-to-Office ROI: How HR Tech Is Measuring Productivity and Employee Well-Being

[To share your insights with us, please write to psen@itechseries.com ]