Cornerstone AVP Anna Goldberg Interview on HRTech Strategy

Welcome to HRTech Cube, Anna. We’re delighted to have you. Could you start by sharing a bit about your professional journey and what led you to your current role as AVP, Product Management at Cornerstone?
Thank you for having me. My professional journal has been a wild ride. Following graduate school and receiving a degree in Community Development at UC Davis, I started a job as a Leadership Development Specialist at Year Up, a National Nonprofit focused on Workforce Development, where one of my first assignments was implementing Cornerstone’s learning and talent development platform.

I went from being a Cornerstone customer, presenting at user groups and conferences, to joining the Cornerstone team. At Cornerstone, I started as a Customer Success Manager and then transitioned to working in product. I’m truly passionate about what Cornerstone can help organizations achieve and strongly believe that most of the career growth and learning an employee does in their career happens at work. In that way, Cornerstone empowers employees to reach their full potential, which is why I feel privileged to grow my career here.

Cornerstone Galaxy represents a major leap in AI-driven workforce enablement. How does it differ from traditional learning and talent development platforms?
Cornerstone Galaxy leverages AI to optimize employee development in ways that set it apart from traditional learning and talent platforms. We use AI to deliver true personalization by analyzing an employee’s skills, current role, career aspirations, and learning behaviors to create tailored, dynamic development paths. Traditional platforms often rely on one-size-fits-all curriculums, but Galaxy adapts to individuals.

Another differentiator is our advanced skills intelligence. Cornerstone Galaxy uses real-time workforce data to map skills across the organization, identifying skills gaps and emerging requirements. Traditional platforms rely on manual skills mapping or manager assessments, which can quickly become outdated. Our system enables more proactive upskilling and reskilling.

Finally, Cornerstone Galaxy offers a unique, unified experience that brings learning, development, performance management, and career planning under a singular platform, making it easy for employees to navigate.

You’ve described Cornerstone Galaxy as a unified system powered by AI agents. How do these multi-role agents enhance personalization and productivity across the employee experience?
Agents create deep personalization across different roles and contexts, helping organizations understand and respond to the unique needs of every employee, regardless of position or experience level. Cornerstone’s AI agents work behind the scenes to learn from interactions and use insights to tailor recommendations for learning and development.

They also act as adaptive teammates that support productivity across the employee experience, offering timely reminders that keep development moving. By showing up at the right moment with the right guidance, AI agents help create a more responsive and tailored experience to help employees grow with clarity, and managers to lead with confidence.

Many organizations still view AI as a technology project rather than a capability shift. Why is it important for workforce planning and development to drive AI adoption instead?
When AI is embedded in workforce planning and development as a true capability, it becomes a practical and instrumental tool for identifying skills gaps across the organization and providing employees learning experiences that will help them grow. Treating AI this way also helps organizations stay ahead of change rather than react to it, ensuring organizations are ready for the future.

Cornerstone’s conversational and immersive learning experiences sound transformative. Could you elaborate on how features like Cornerstone Immerse Companion are redefining how employees learn and engage?
Cornerstone Immerse Companion leverages AI-powered conversational interfaces to simulate real-world scenarios in a safe, supportive environment. Employees can practice communication, problem solving, and leadership interactions with an assistant that adapts to their responses, offers coaching, and guides them through different scenarios. It also supports rich and immersive environments using VR and AR to provide interactive simulations that let employees role play complex or high-stakes situations before they encounter them on the job.

This immersive experience goes beyond traditional e-learning by providing personalized experiences and on-demand assistance, helping employees practice hands-on skills while becoming more engaged learners.

Compliance and responsible AI are top concerns for HR leaders. How does Cornerstone AgentReady ensure that AI agents are workforce-ready and aligned with organizational standards?
Cornerstone AgentReady goes beyond basic guardrails to make sure agents are workforce ready with skills validation, policy alignment, continuous monitoring, and integration with organizational standards all within Salesforce. Each agent is trained, tested, and certified prior to deployment, ensuring that responsible, compliant AI solutions enhance workforce productivity without compromising ethical or regulatory commitments.

With Cornerstone Galaxy integrating SkyHive’s Knowledge Graph, how does this partnership enhance workforce intelligence and skills-based planning?
SkyHive’s Knowledge Graphs brings real-time labor market intelligence into Cornerstone Galaxy, providing organizations an accurate and dynamic view of their workforce capabilities. Rather than relying on static job descriptions or outdated skill inventories, leaders can see what skills their employees have today, how internal skills compare to the external market, and where gaps are emerging. This level of precision transforms workforce planning into data-driven strategy.

The integration also strengthens skills-based development at the individual level, providing employees recommendations not only on internal career paths, but on current market demand and adjacent skills possibilities. Cornerstone Galaxy and SkyHive have created a continuously updated skills ecosystem that helps organizations meet business needs while providing employees actionable learning and development opportunities.

As a product leader, what personal strategy do you follow to balance innovation with the need for scalability and user trust in AI-driven systems?
My approach starts with focusing on AI use cases that clearly drive productivity and value for our customers. Innovation only matters if it solves a real problem, and AI for the sake of AI will not drive outcomes for our customers. By grounding strategy in specific workforce agility needs, like developing necessary skills or improving employee experience, we ensure that our products deliver real value.

What advice would you give HR and product leaders who are just beginning to explore AI in their learning or talent management strategies?
Start by making sure the use cases you’re solving for meet real needs of HR leaders and employees. AI should remove friction and enhance decision making, not add complexity. If the problem it’s solving isn’t meaningful, the AI solution won’t be either.

Finally, what’s next for Cornerstone Galaxy? How do you see the platform—and AI’s role in HR tech—evolving in the coming years?
At Cornerstone, we’re continuing to innovate through basics. Even as we expand to more AI-native workflows, we are working to ensure we keep strengthening the core learning and talent development experiences our customers rely on. The fundamentals still matter, and AI should enhance what already works.

We’re also moving from “in the flow of work” to “in the moment of need ,” making sure admins and employees get the exact data, guidance, or insight they need when they need it. That level of responsiveness is where AI can make a meaningful difference.

Looking ahead, you’ll see more conversational experiences across the platform. We want customers to engage with content, recommendations, and insights in ways that feels natural, while still ensuring compliance.

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Achieving Human Centric Workplaces in the Age of AI for Workplace Transformation

As artificial intelligence continues to reshape the workplace, its influence is expanding well beyond productivity tools and task automation. In fact, employees that reported using AI in their role a few times a year or more jumped from 21% to 40% over the past two years.

Heading into 2026, AI is increasingly tied to how workplaces remain functional under pressures like aging infrastructure and tightening budgets. While use cases for AI continue to expand, leaders must prioritize flexible workplace design that keeps human needs at the center to ensure employee satisfaction and productivity.

Humans At the Center

A human-centric workplace prioritizes human needs including employee well-being, purpose, and connection as the foundation of the work experience. Technology is meant to support human value, not replace it.

AI, when implemented properly, can help eliminate friction from daily work, automate repetitive tasks, deliver insights that improve decision making, and ensure the physical environment remains in peak condition for its occupants. But the goal isn’t more technology; it’s using technology so people can focus on creativity, problem solving, and meaningful interactions.

Navigating AI Adoption in The Workplace

Encouraging AI adoption requires positioning AI as an enabler of human potential, not a substitute for it. In a time where the nature of work is changing dramatically, this framing helps overcome skepticism and adoption pushback.

One of the biggest challenges organizations face is the risk of over-automation: leaning too heavily on AI and removing the “human” element that employees value. Another is the rapid introduction of tools without clear communication, which can overwhelm employees and create resistance. Without proper guidance, employees may see AI as something being imposed on them, rather than something designed to support their success. AI needs to be paired with a purpose for successful adoption.

Overcoming resistance requires honest communication about AI’s uses and benefits. Leaders must demonstrate how AI helps solve real pain points, such as freeing time for focus work or personalizing the work environment. Involving employees in pilot programs that create employee champions of various AI tools, providing ample and thorough training, and gathering regular feedback is key to building employee confidence in AI.

Creating Dynamic Workplaces with AI

Low employee engagement costs the global economy an estimated $8.9 trillion on average. AI can be used to optimize the physical workspace and make it easier for employees to interact. Rather than forcing employees to adjust to rigid spaces, data-informed design allows organizations to flex space usage, reduce friction in scheduling and collaboration, and support different workstyles without disruption or expansion.

The next era of workplace strategy will be defined by flexible environments that can adapt as different technological needs and employee preferences evolve. AI can learn from aggregated, anonymous data to optimize conveniences for employees like recommending the best workspace for tasks, from collaboration hubs to wellness-oriented spaces. It can also adjust amenities like lighting and temperature to enhance comfort.

Beyond workspace preferences, AI can support well-being. Smart HVAC systems can regulate air quality and temperature and flag potential maintenance issues before they occur, while desk and room data can be used to ensure employees aren’t overbooking themselves and burning out. AI-driven apps used by employees can also prompt movement breaks or recommend quiet spaces for focus and recharge sessions.

At a strategic level, organizations can leverage AI to right-size real estate portfolios, optimizing resource allocation and operational costs while preserving a positive employee experience, leading to stronger engagement, productivity, and long-term business growth.

Ensuring Employee Privacy and Inclusivity

Leveraging AI to personalize and optimize the human-centric workplace requires protecting employee privacy and ensuring inclusivity. While acceptance of AI has increased, employees need confidence that AI is there to support them, not monitor them. Without safeguards, well-intentioned tools can erode trust. When using data to personalize experiences, establish clear governance policies that limit personal identifiers, give employees visibility into data use, and prioritize opt-in participation.

Protecting the sensitive data behind these systems is also extremely important. This includes providing proper AI training, monitoring potential misuse, and putting guardrails in place against risks like data leaks or AI attacks.

Equally important to privacy is providing equitable access to AI tools regardless of role, department, or work arrangement. Regular audits of tools can help identify and reduce unintended bias, while “human override” models empower employees to challenge or bypass AI recommendations. Finally, build choice into systems, so employees have autonomy in how they interact with workplace resources.

When privacy and inclusivity are prioritized from the start, organizations can strengthen trust while creating workplaces where employees feel supported.

The Future of Human-Centric Workplaces

When evaluating whether your AI-enabled workplace strategy is truly “people first,” key indicators include employee feedback on workplace satisfaction, utilization data paired with well-being indicators, retention and engagement levels among those using AI tools, and inclusion metrics that assess whether all employees experience equitable access to resources.

AI will make the workplace more adaptive and less static. Offices will function as dynamic ecosystems where spaces evolve in response to employee needs, workstyle preferences, and organizational priorities. AI’s role in the workplace isn’t about replacing people or adding more technology for people to manage. It’s about creating environments that respond to human needs with intention.

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HRTech Cube View on HRTech and Strategic Workforce Planning

HRTech brings people and technology together through a modern digital workplace, showcasing diverse professionals connected by intelligent HR solutions and data-driven innovation.



How HRTech is Transforming Human Resource Practices

In an era where businesses compete on agility, employee experience, and data-driven outcomes, HRTech has emerged as a cornerstone of modern human resource strategies. Instead of viewing technology as a support function, forward-thinking organizations now embed it into every aspect of talent acquisition, management, engagement, and retention. HRTech is not merely about automating tasks; it’s about enabling smarter decisions, unlocking workforce potential, and shaping resilient cultures. The rise of cloud platforms, artificial intelligence, analytics, and connected systems is redefining how HR teams deliver value and drive organizational performance.


What Is HRTech
HRTech refers to the suite of digital tools and platforms designed to support, automate, and enhance human resource functions. This includes systems for hiring, payroll, performance management, learning, engagement, workforce analytics, and more. Unlike traditional HR systems, modern HRTech solutions leverage automation, machine learning, and real-time data to provide actionable insights and streamline processes that once required extensive manual effort. At its heart, HRTech is about optimizing the employee lifecycle while aligning people strategies with broader business goals.


Core Components of HRTech
HRTech spans a wide range of technologies that address different HR needs:

Talent Acquisition & Recruitment Platforms
Modern hiring tools use automation and data to improve sourcing, screening, and candidate engagement. These systems reduce time-to-hire and improve hiring quality by identifying best-fit talent using predictive models.

HR Information and Core Administration Systems
These include HRMS and payroll/benefits platforms that centralize employee data, simplify compliance, and automate routine administrative tasks for HR teams.

Learning and Development Tech
Continuous skill development is vital in a fast-changing economy. Learning platforms powered by intelligent recommendations empower employees with personalized growth opportunities and support internal mobility.

Employee Engagement & Experience Solutions
Tools for feedback, recognition, wellness, and collaboration help foster a positive work environment. They enable HR leaders to gauge employee sentiment, address concerns proactively, and cultivate a culture of trust and inclusion.

Analytics and Insights
Workforce analytics tools transform raw HR data into insights that inform strategic decisions. From attrition forecasting to performance trend analysis, data analytics is reshaping how HR leaders assess organizational health.

Strategic Benefits of HRTech
Adopting the right HRTech solutions brings significant advantages:

Enhanced Efficiency and Productivity
Automation reduces manual tasks in recruitment, onboarding, payroll processing, and performance reviews, freeing HR professionals to focus on strategic initiatives.

Improved Decision-Making
Real-time data and analytics empower HR teams to anticipate trends, measure program success, and allocate resources effectively.

Better Talent Experiences
From smooth onboarding journeys to ongoing learning opportunities, HRTech enhances each stage of the employee lifecycle and strengthens employer-employee relationships.

Scalability and Flexibility
Cloud-based HRTech platforms adapt to changing business needs, supporting remote work, global teams, and evolving workforce expectations.

Challenges in HRTech Adoption
Despite its promise, HRTech adoption presents challenges:

Integration Complexities
Many organizations struggle to unify disparate systems, which can lead to data silos and inefficiencies.

Change Management
Shifting to tech-driven HR requires cultural adaptation and upskilling across teams.

Security and Privacy
Safeguarding employee data is paramount. HR leaders must ensure compliance with data protection regulations while maintaining trust.

Future Directions for HRTech
Looking ahead, HRTech will continue evolving around several key trends:

AI-Driven Personalization
Intelligent systems will deliver tailored learning paths, career progression plans, and workforce recommendations.

Predictive and Prescriptive Analytics
Beyond explaining what happened, analytics will forecast trends and suggest optimal interventions.

Employee-Centric Platforms
Technology that enhances employee autonomy and experience will become a strategic differentiator in talent markets.

Ethical and Responsible Technology Use
As technology takes a larger role in people decisions, ethical frameworks and governance will be essential to ensure fairness and transparency.

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Conclusion

HRTech has fundamentally reshaped the human resource landscape. By integrating advanced technologies into everyday HR practices, organizations can achieve operational excellence, foster engaging employee experiences, and make informed decisions that drive business success. As HRTech continues to mature, its strategic role will only grow stronger, helping organizations navigate complexity while putting people at the center of transformation.

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AI Driven Candidate Sourcing and Match Consistency

Achieving strong candidate matching accuracy has become a top priority for modern hiring teams. As job roles grow more complex and talent pools expand, traditional sourcing methods often fall short in identifying the most suitable candidates. AI driven sourcing introduces a smarter approach by using data intelligence to connect job requirements with candidate profiles more precisely. This shift enables recruiters to focus on quality matches rather than volume.

Understanding Candidate Matching Accuracy

Candidate matching accuracy refers to how closely a candidate’s skills experience and potential align with a specific job role. Poor matching leads to longer hiring cycles higher attrition and reduced team performance. Accurate matching on the other hand improves hiring confidence and supports long term workforce stability. As hiring demands increase accuracy has become more important than speed alone.

The Role of AI in Modern Talent Sourcing

AI driven sourcing uses advanced data models to analyze job descriptions candidate profiles and historical hiring outcomes. Instead of relying on keyword based filtering AI evaluates context skills relationships and patterns across large datasets. This allows hiring teams to surface candidates who may have been overlooked using traditional resume screening methods.

How AI Improves Candidate Matching Accuracy

AI improves candidate matching accuracy by evaluating multiple data points at once. Skills experience career progression and role relevance are assessed together rather than in isolation. AI systems also adapt over time learning from successful placements and recruiter feedback. This continuous improvement helps refine match quality and reduces the chances of mismatched hires.

Another advantage is consistency. AI applies the same evaluation logic across all candidates ensuring fairness and reducing unintended bias. This leads to a more balanced shortlist and improves confidence in hiring decisions.

Benefits for Recruiters and Organizations

Improved candidate matching accuracy delivers measurable value. Recruiters spend less time screening unsuitable profiles and more time engaging high quality candidates. Organizations benefit from shorter hiring timelines better employee performance and improved retention. Accurate matching also enhances the candidate experience by aligning expectations early in the hiring process.

Human Judgment and AI Working Together

While AI enhances accuracy human insight remains essential. Recruiters provide context around team culture communication style and growth potential that data alone cannot capture. When combined with AI driven insights human judgment ensures that hiring decisions are both data informed and people focused.

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Conclusion

Candidate matching accuracy is a critical factor in building strong and sustainable teams. AI driven sourcing strengthens this accuracy by analyzing data intelligently learning from outcomes and supporting fair evaluation. When paired with recruiter expertise AI enables smarter hiring decisions that benefit both organizations and candidates in the long term.