In this episode of our podcast, Talent Draup, Brian Heger, longtime internal practitioner and founder of the blog Talent Edge Weekly, joins Tanya Early, VP of Sales at Draup, to discuss the evolving priorities of HR teams in a world that’s being rapidly reshaped by AI.

Brian, with two decades of HR experience in industries like telecom, retail, and pharma, says that HR should focus on addressing real business problems. AI initiatives should start by understanding business challenges, he says, as workforce planning has grown both urgent and complex. He highlights the importance of change readiness over traditional change management plans in fostering organizational resilience. Brian advocates for simplifying complexity through the creation of practical tools and leadership development to enable teams to take much quicker action.

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Quotes:

“HR is heavily shaped from an internal HR practitioner standpoint, meaning […], we always start with how does this add value to the business with what we're doing?” – Brian Heger

“Don't start with the technology. Start with what's the business problem that we're trying to solve here.” – Brian Heger

“Complexity gets in the way of execution, and when […] people can't really understand the topic or the issue […] we can't move it into some type of action.” – Brian Heger

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#aiinhumanresources #hrtrends #workforceplanning #talentmobility #organizationalchange #changereadiness #hrfutureofwork #hrstrategy #hrleaders #changefatigue #talentstrategy #hrinnovation #draup #hrpodcast #aiusecases #businessproblemsolving #hrinsights #workforceanalytics #leadershipdevelopment
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Moments You Can’t Miss:

02:03 - The three HR priorities emerging globally: AI’s impact on work, workforce planning, and change fatigue
05:14 - Why AI prioritization must start with the business problem, not the use case
07:54 - AI as a “thought partner” in workforce planning and talent mobility
10:42 - The danger of not seeing the collective view of organizational change
12:55 - Moving from “change management plans” to building everyday change readiness
13:45 - How one-page frameworks help simplify complex HR topics and unlock execution

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Key Takeaways:

- Start with the business challenge: AI should solve a validated business problem, not be adopted because it's available.
- Workforce planning is now harder and more critical: AI reshapes tasks, roles, and skills continuously, requiring scenario modeling and skill-based planning.
- Build change readiness, not more change plans: With employees facing 5–10 major changes at once, organizations need capabilities that help teams anticipate, discuss, and adapt to future scenarios.
- Simplification is a strategic skill: HR leaders who can cut through noise, frame issues clearly, and tell a compelling story can move execution forward faster.
- AI unlocks capacity for more strategic work: 2026 will mark a shift from experimentation to real implementation, giving HR teams more time for high-value priorities.

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More About Talent Edge Weekly & Brian Heger:
Brian Heger is a longtime internal HR practitioner with experience across telecom, retail, and pharma. He writes Talent Edge Weekly, a leading HR newsletter with over 55,000 readers, where he shares practical insights on workforce planning, talent management, AI use cases, and organizational effectiveness. His work focuses on helping HR teams simplify complex issues and deliver high-impact business value.

More About Draup:
Draup is an AI-powered intelligence platform that supports over 200 global organizations in enhancing their talent and sales strategies. Draup enables enterprises to make informed decisions in workforce planning, talent acquisition, and account-based marketing by provi

In this episode of Talent Draup, Dr. Dieter Veldsman, Chief HR Scientist at AIHR, joins Vishnu Shankar, VP - Data & Platform at Draup, to talk about how HR can transform from policy-led procedures to people-first operating models in the age of AI.

Dieter emphasizes that instead of replacing human experience, AI must enhance it. In his view, HR must be able to integrate AI while maintaining high-touch interactions, accountability, and trust. He elaborates on how HR can transform workflows, close the insight-to-action gap, and rethink workforce strategy in an age when AI collaboration is de rigueur through examples from learning, talent acquisition, and performance management.

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Quotes

“We are entering a new chapter of work, which is going to call on us as HR professionals to rethink what our mandate and what our value is in the organization.” — Dr. Dieter Veldsman

“If you can't fix skills, structure will never help you. If you don't have the right structure with the skills tied to it, you can never deliver on strategy.” — Dr. Dieter Veldsman

“We sometimes operate from this assumption that everybody wants to be promoted, everybody wants to be pushed into extreme projects and stretched, et cetera. And that's not the reality for a lot of people.”— Dr. Dieter Veldsman

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Moments You Can't Miss

04:39 - Approach HR as a product house, employees as the consumers of HR solutions
08:44 - AI for performance management: where restraint and human context trumped full automation
09:59 - Three levels of governance for AI in HR: strategy, enablement, and transition, with ethics as the overarching guide
12:15 - Placing decision-making at the frontline while keeping centralized guardrails
17:14 - Understanding that career choices are life choices: HR needs to factor in the human context

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Key Takeaways

Decentralize ownership: While maintaining responsible governance, bring decision-making closer to the location of work.
Connect insight to action: Turn talent intelligence into effective, well-designed interventions that impact outcomes.
Trust by design: AI should complement human judgment, not substitute for it; human-centered HR supports employee trust.
Clarity of strategy: To effectively deploy resources, define the HR mandate, areas of concentration, and success metrics.

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More on Draup:
Draup is an AI-powered intelligence platform that supports over 200 global organizations in enhancing their talent and sales strategies. Draup enables enterprises to make informed decisions in workforce planning, talent acquisition, and account-based marketing by providing multi-dimensional global labor market data.

More on AIHR:
The Academy to Innovate HR (AIHR) is a leading global academy for HR education, research, and digital learning. It offers advanced courses, credentials, and thought leadership to help HR professionals build practical skills in organizational design, people analytics, talent management, and AI-based strategies. These capabilities enable HR leaders to design human-first, data-driven, and future-ready workforce strategies.

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Social media:
Vishnu Shankar: https://www.linkedin.com/in/vvishnushankar/
Dr. Dieter Veldsman: https://www.linkedin.com/in/dieterveldsman/
Draup: https://draup.com/

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#futureofhr #aiinhr #hrtransformation #futureofwork #hrleadership #peoplefirst #talentstrategy #humanresources #aiforhr #hrinnovation #organizationaldesign #hrtechnology #employeeexperience #talentintelligence #hrstrategy #workforcefuture #digitalhr #hrleaders #hrtrends #hrpodcast

In this episode of Talent Draup, Mickey Mohit Raie, who leads skills analytics and insights at Accenture, speaks with Vijay Swaminathan, CEO of Draup, on everything predictive skills architecture and the evolution of talent intelligence in the age of AI.

Mickey has driven Accenture’s journey toward a truly data-driven, business-aligned skills framework. His work thrives on cross-functional partnerships and co-creation, bringing together HR, technology, and business leaders to ensure that every skills taxonomy reflects both external market shifts and the company’s unique strategy. Continuous learning and customer-centric innovation are at the core of his approach, leveraging AI to translate workforce data into actionable insights.

He recalls the days of managing skills on disparate spreadsheets. Tracking certifications, learning completions, and project assignments manually, before migrating to centralized systems. This evolution to a unified skills taxonomy revolutionized how Accenture staffs and upskills its people. By embracing tools like Draup, they have unlocked a more dynamic, proactive model for identifying both current and future skill needs.

With the advent of AI, Accenture has further refined its talent strategies. Mickey and his team integrated machine learning to infer latent and proximate skills from existing data, creating graph-based algorithms and affinity analyses that surface hidden competencies. This precision enables targeted staffing, matching the right people to the right projects faster and with greater confidence.

Accenture’s shift from broad talent searches to laser-focused, proximity-based skill mapping has driven higher resource utilization and improved bench conversion. By ranking candidates based on exact and related skills at varying proficiency levels, the organization dramatically expanded its viable talent pool, turning once rigid talent categories into adaptable pipelines ready for rapid redeployment.

Accenture’s skills architecture now forecasts emerging skill demands and recommends targeted learning or hiring interventions. This precision-driven approach has enhanced internal mobility, reduced bench strength, and elevated the strategic impact of HR. By leveraging buyer-intent–style data on workforce trends, staffing teams can engage more meaningfully, and learning teams can curate hyper-relevant development paths.

Mickey emphasizes the need for relentless innovation across HR, technology, product development, and operations. AI and predictive analytics are not add-ons but enablers of higher efficiency and strategic decision-making. By adopting tools that deliver granular, real-time insights, Accenture has streamlined staffing workflows, boosted conversion rates from bench to billable, and slashed time-to-fill for critical roles.

Vijay and Mickey highlight the importance of metrics and KPIs in measuring success. They agree that every HR and business unit must define clear targets—skill gap reduction, learning adoption, internal mobility, and resource utilization—and continuously explore how AI can enhance these metrics. Embedding AI into each talent management process strengthens the organization’s ability to innovate and sustain competitive advantage.

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#predictiveskillsarchitecture #talentintelligence #workforceplanning #hrtech #ai #skillsanalytics #skillsgap #futureofwork #workforcedata #peopleanalytics #upskilling #reskilling #talentmanagement #hranalytics #workforcetrends #digitalhr #hrinnovation #aiforhr #skillmapping #talentstrategy #hrdigitaltransformation #workforcedevelopment #talentacquisition #hrleadership #datafirsthr #hrmetrics #humancapitalmanagement #organizationalagility #learninganddevelopment #talentbenchmarking #skillstransformation #workforceoptimization #talentinsights #hrtechnology #strategichr #employeeexperience

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Timestamps:

01:48 – From skills architecture to predictive skills architecture