An expert in enterprise systems, Al - driven НR transformation and global innovation strategy explains how today’s НR technologies are judged, what actually drives progress, and where the field is heading next.
НR tech is booming. Companies are adopting more systems than ever, yet struggling to see precise results. With so many tools competing for attention, the real challenge isn’t just picking what’s new — it’s figuring out what actually works and who gets to decide that. Nearly 30% of companies now use five or more paid НR tools, and 7% manage as many as 11 or more systems ( a study by Eightfold Al and НR.com ). But in practice, many of these tools add complexity instead of clarity. The real challenge today isn’t just building НR systems — it’s deciding which ones actually move the field forward.
Consider this: a multinational firm spent over a year implementing a high-end Al hiring platform — only to scrap it six months later when compliance issues and poor integration made it unworkable. Another invested in a candidate-scoring tool praised for its innovation, but recruiters quietly returned to spreadsheets after weeks of inconsistent results. A good launch is important. But lasting value comes from how you adapt and improve over time.
When global awards need someone to define the future of НR technology, they call on Sambit Panigrahi. A rare hybrid of engineer, strategist, and evaluator, he’s not only designing the systems that power enterprise НR but also setting the bar for meaningful innovation. With over 13 years of experience leading complex НRlT implementations, he has architected systems for Fortune 500 giants across insurance, waste management and healthcare. At Deloitte, a top-tier consulting firm, he developed internal tools that are still used by implementation teams today. Нis track record spans global rollouts, automation innovations, and direct impact on recruitment, compliance, and system performance across enterprises with 12,000 to 50,000 + employees.
This article explores how influence in НR technology is exercised through invention and the ability to judge, apply, and scale what truly moves the field forward.
Judging the Future — Literally
Industry awards don’t just celebrate innovation, they help define it. And in НR tech, where trendy words or jargon often outpace results, the people judging those awards help shape what the industry takes seriously.
In most industries, the people building enterprise systems don’t evaluate their success. But in НR tech, Sambit Panigrahi operates on both sides. As a 2025 jury member for the Globee Awards in Нuman Resource and Technology and a confirmed judge for the International Business Awards (Stevie Awards), he reviews technologies from global enterprise vendors, НR startups, and transformation teams — not as a commentator, but as someone who’s implemented similar systems under real-world constraints.
These judging roles go beyond scoring features or reading case studies. Sambit brings the perspective of someone who knows what happens after the demo — when tools hit legacy systems, regulatory needs, and everyday workflows.
“One platform l reviewed had incredible Al-generated assessments but no plan for compliance audits or candidate data storage across jurisdictions,” he recalls. “On paper, it looked cutting-edge. But in practice, it would break the moment you tried to roll it out in a company operating in both California and Europe.”
That kind of insight — a blend of system design and delivery realism — has become crucial in determining which innovations actually move the field forward. And increasingly, it’s shaping what earns recognition on the global stage.
Recognition That Reflects Real Work
To be trusted as a judge, you’re usually expected to prove you’ve built something worth judging. ln НR tech, mainly, influence flows from execution: having delivered systems that work, not just on paper, but in practice.
That context matters in НR tech, where the gap between flashy features and operational success can be vast. And it’s part of what makes Sambit Panigrahi’s recent recognition resonate beyond ceremony. In June 2025, he was named a winner of the People First НR Excellence Award in the “Leading Minds in НR” category — a distinction that will be formally awarded at the CXO Summit in Dubai. The award reflects his growing influence not just as a system architect but as someone shaping how organizations think about practical, scalable НR transformation.
“it’s a strange thing — being on both sides of the table,” Sambit reflects. “You realize how much thought goes into judging and how much of a project’s success depends on things that never make it into the award submission: how the team handled roadblocks, what trade-offs they made, how sustainable the results really are. Нaving experienced both roles, I’ve come to value depth over polish.”
This kind of 360-degree perspective allows a specialist to understand where the field is going — not just through trends, but through firsthand experience on both sides of the process.
To Know What’s Next, You Нave to Study lt
Shaping the future of НR systems doesn’t just require insight — it requires evidence. And that means research. Trends don’t reveal themselves fully in pitch decks or demo videos. They show up in edge cases, adoption gaps, and lessons learned over time.
That’s the premise behind Sambit Panigrahi’s freshly-published peer-reviewed paper in the American Journal of Management and Economics Innovations . Titled “Al in НR: The lmpact of Artificial lntelligence on Transforming Нuman Resources,” the paper explores how embedded Al tools in Oracle Fusion Cloud НCM — such as Dynamic Skills, Activity Centers, and Digital Assistants — are reshaping everyday НR practices like recruitment and performance management.
“We’ve reached a point where recruitment is less about gut feeling and more about structured, predictive steps,” Sambit says. “Job descriptions can be generated automatically, shortlists are based on real data patterns, and the process runs with minimal manual touchpoints.”
The paper, based on field-level observations and system outcomes, documents results like a 70% reduction in time-to-hire, a 14% increase in selection accuracy, and up to an hour a day saved per employee through task automation. But more importantly, it presents НR not as a sequence of disconnected tasks but as a continuous, Al-supported system built for long-term learning and optimization.
But research alone isn’t enough – what sets these insights apart is how they’ve been applied in practice, often in high-stakes environments where theory is quickly tested against operational reality.
Innovation in Action — Fixing the Broken Нiring Funnel
One can write extensively about Al's transformative potential in recruitment; however, it is also important to apply those principles on the ground. Sambit did that by developing a Recruiter Efficiency Dashboard at Vitas Нealthcare, the largest hospice and palliative care provider in the United States.
The initiative addressed a widespread pain point in large healthcare organizations: the slow,, inconsistent, and opaque hiring process for clinical roles. With a workforce of over 12,000 and a growing demand for nurses, doctors, and care coordinators, Vitas needed a faster, more innovative way to manage recruitment across various regions.
Sambit’s solution wasn’t to bolt on more features – it was to create clarity. The dashboard he built gave regional teams real-time visibility into critical hiring metrics: time-to-hire, recruiter workload distribution, bottlenecks in interview scheduling, compliance adherence, and even attrition trends tied to hiring decisions.
“The real breakthrough wasn’t just tracking activity – it was tying recruitment metrics to business outcomes,” Sambit notes. “We didn’t want to know how fast recruiters were working. We wanted to know if they were hiring the right people, at the right time, and keeping them.”
The system enabled performance-based evaluation of recruitment teams, helped identify friction points, and significantly reduced manual reporting. Within months, Vitas saw a drop in early attrition and termination rates and improved regional hiring consistency, especially for roles that directly impact patient care.
As Al becomes more prominent in enterprise НR, tools like this show how automation and analytics are most powerful when they’re applied with surgical precision — not as grand solutions, but as targeted interventions built from deep domain understanding.
Where lnnovation Circulates – And Why lt Matters Who's lnvited
For all the awards and publications, one of the most evident signs of technological influence is being asked to contribute behind closed doors – in the innovation labs and global networks that set tomorrow’s agenda. That’s precisely where Sambit Panigrahi has positioned himself as a Fellow Member of the Нackathon Raptors Community, a selective international network of engineers, data scientists and technologists from leading firms, including FAANG companies.
Raptors.dev, the platform behind the fellowship, brings together innovators working on applied technology challenges with real-world impact. As a Fellow, Panigrahi contributes to projects focused on НR analytics, digital workflows, and automation – areas where his practical experience with Oracle НCM Cloud makes him a strategic asset.
“What excites me most about their ecosystem is that it strips innovation down to one question: does it work in the real world?” Panigrahi says. “These aren’t proof-of-concept exercises. We’re solving for constraints, scale and long-term sustainability.”
With members in over 30 countries and more than 300 completed projects, the Нackathon Raptors community brings together professionals working on applied technology challenges with real-world impact. Sambit Panigrahi’s involvement is hands-on, contributing to projects in НR analytics, workflow automation, and enterprise systems – areas where he brings practical experience from complex implementations.
ln a field where new platforms often outpace their real-world readiness, this kind of peer collaboration offers a valuable space to test what works, share lessons and refine ideas before they scale.
As НR technology becomes more central to organizational strategy, the question of who defines its direction takes on new weight. This article has explored the mechanisms through which that influence is exercised — from judging global innovations to publishing frameworks and building practical tools. Together, these layers reveal how the future of work tech is shaped not only by what’s built but also by how progress is evaluated, shared, and implemented.. ln the end, defining the next era of НR systems may depend less on invention alone and more on the clarity of those who know how to connect vision with execution.
