HR Tech Founder Says Most AI Projects are Just “Digital Lipstick” on Broken Processes
Discover how an HR tech founder uses AI to automate routine work, improve employee experiences, and help HR teams become more strategic without losing the human touch.
Jay Polaki
Co-founder and CEO of HR Geckos
AI-Impact: AI reshapes HR by automating processes, offering insights, and enabling informed decision-making.
Challenges: Key HR challenges include administrative burdens and fragmented data, limiting strategic potential.
Opportunity: AI can elevate HR from support to strategy with predictive analytics and personalized experiences.
Ethics: Ensuring ethical AI usage in HR requires maintaining human oversight and avoiding bias amplification.
Quick Wins: Start AI adoption with tasks like automating FAQs, workflows, document management, and reporting.
Jay Polaki is co-founder and CEO of HR Geckos, an HR technology company that helps organizations automate HR processes while keeping people at the center. She previously held director-level roles in HR.
We caught up with her to learn how she is using AI to revolutionize HR processes. Here's what she had to say.
Leveraging AI for strategic HR transformation
Hi, I am Jay Polaki, the CEO and Chief Gecko at HR Geckos. To borrow a term from botany, I have had a variegated start — a very colorful start — to my HR career. My education and background in I/O Psychology led me to work for organizations in various industries and sectors, from large multinational corporations and government agencies to smaller consulting firms. I learned so much about how people are the lifeblood and lifeline of every organization.
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HR Geckos, my HR technology company, was born out of these experiences in my HR career. My mission is to automate HR processes, preserve the human touch, and connect HR systems around what matters most — people.”
Why AI is reshaping HR leadership and organizational design
I leverage technology to solve challenges plaguing HR departments today, including providing a consumer-grade employee experience, delivering data-driven insights, and streamlining workflows.
After more than twenty years leading HR teams, I saw a recurring pattern. Brilliant, dedicated HR professionals wanted to make a strategic impact, but a few key pain points consistently held them back.
First, the administrative treadmill! I saw firsthand how manual processes consumed much of HR’s time — answering the same policy questions, chasing paperwork, or navigating outdated systems.
Second, the data disconnect. We had employee data in our HRIS, candidate data in our ATS, payroll data in another system, and engagement survey results in a spreadsheet.
Answering a seemingly simple question from my CEO, like “What’s the turnover rate for high-performers in our engineering department?” required a massive, manual effort to export, clean, and merge data. We were data-rich but insight-poor, and this hindered our ability to be true strategic advisors.
The frustration of wanting to make a bigger impact, yet being bogged down by administrative burdens and data disconnects, greatly motivated me.
My role is shifting from solving everything to designing conditions for better decisions, faster execution, and clearer accountability. In an AI-first world, leadership is about clarity, guardrails, and judgment, not just oversight.
I’ve let go of the assumption that the best organizations are the most centralized ones. AI is enabling more distributed decision-making, but it also reinforces that human judgment, empathy, and context still matter most in the moments that define culture and trust.
How to avoid treating AI as "digital lipstick"
It’s an incredibly exciting time, and the opportunities are immense. I see huge opportunities in shifting from process automation to capability augmentation. AI and automation can elevate HR from a support function to a strategic powerhouse, enabling predictive analytics for workforce planning, personalized employee experiences, and seamless compliance. This allows HR to become a predictive, data-driven function rather than a reactive one.
However, the biggest pitfall is treating digital transformation as a one-time project or simply layering technology onto broken processes — a sort of “digital lipstick” on a broken workflow.
Without thoughtful change management and a focus on user experience, we risk low adoption and even greater frustration with the tech tools. True transformation requires rethinking workflows, training teams, and shifting the collective mindset of the department.
Also, if we automate without care, we risk creating a cold, impersonal employee experience. You should never automate a compassionate conversation. The goal is to use technology to handle transactional tasks so humans have more time for meaningful, empathetic interactions, especially during sensitive moments like performance issues or personal crises.
Lastly, AI models learn from the data we give them. If historical hiring or promotion data contains hidden biases, AI can unintentionally perpetuate or even amplify them at scale. It’s critical to choose ethical AI partners and maintain human oversight.
The key is a human-centric approach. Keep people at the center of transformation and use technology to enhance, not replace, the human touch in HR.
How to find quick wins with AI
To unlock strategic capacity, I advise teams to start with high-volume, low-judgment, and rule-based tasks. These quick wins deliver immediate ROI by reclaiming time.
My top four quick-win use cases would be:
- Tier-1 employee questions: This is the lowest-hanging fruit. An AI-powered knowledge base or chatbot answers common policy, payroll, and benefits questions, providing immediate relief to the HR team and giving employees instant answers.
- Onboarding and offboarding workflows: These are process-heavy and involve multiple stakeholders (IT, payroll, hiring manager). Automating checklists, notifications, and paperwork ensures a consistent, compliant, and superior experience for everyone involved.
- Document generation and management: Think offer letters, employment verification letters, and policy acknowledgments. Automating the creation, signing, and filing of these documents eliminates significant administrative burden and reduces errors.
- Compliance reporting data aggregation: Manually pulling and formatting data for reports like EEO-1 or Affirmative Action Plans is tedious and prone to error. Automation handles data aggregation, allowing HR to focus on analyzing results and developing action plans.
Automating these foundational tasks builds the foundation of operational excellence, giving HR credibility and capacity to step into a more strategic role.
Why AI adoption is more about behavior than technology
Research in 2026 has shown that AI adoption is less about the technology and more about behavior, trust, and redesigning how work happens. I've been surprised by how much AI forces leaders to examine their own assumptions about control.
The best outcomes come when leaders stop trying to make AI fit the old process and instead redesign the process around what humans and machines each do best. For me, that means AI isn’t just a productivity layer. It’s a leadership discipline that requires me to be clearer about workflow, accountability, and where human judgment still matters most.
How to build AI literacy and readiness in HR teams
As an HR practitioner and now HR tech entrepreneur, I’ve thought extensively about what it means to be “AI-ready.” Most conversations about AI focus on tools, automation, and disruption, but they don't focus enough on people.
As HR and business leaders, we know that transformation doesn’t happen when new tech rolls out. It happens when people buy in, trust the process, and feel equipped to thrive.
AI is accelerating faster than most organizations can adapt. Yet the greatest gap isn’t technical, it’s cultural and human. HR isn’t just a function anymore, it’s a strategic compass guiding AI's integration into culture, work design, and talent models.
We steward trust, fairness, and inclusion in AI-driven decisions — from hiring algorithms to performance management. None of us built our organizations to serve technology — we built them to serve people!
The challenge? Organizational readiness.
In our recent "AI-Ready or Not" roadshow, we visited five US cities and spoke firsthand with HR and business leaders. Over 70% of the business leaders cited foundational hurdles like data quality, integration issues, and legacy processes as the biggest barriers to moving AI ideas to real-world impact.
Additionally, almost all admitted that they lack sufficient AI knowledge, highlighting a major need for upskilling and transparency in the HR function.
This is a pivotal moment for HR. As organizations shift from AI experimentation to execution, HR leaders must not only champion adoption but also drive measurable business outcomes — faster hiring, smarter engagement, and better retention — with AI-powered tools.
Yet, the path is rarely smooth: cultural resistance, skills gaps, and unclear use cases often stall progress.
What can HR teams do to accelerate AI readiness and deliver results?
- Invest in education and upskilling: Build AI literacy across the HR team and empower early adopters to share success stories.
- Prioritize data and knowledge fitness: Clean, connected data is the foundation for any successful AI initiative.
- Foster a culture of experimentation and transparency: Involve employees in the process, address concerns openly, and celebrate quick wins to build trust.
- Align AI projects with business priorities: Focus on use cases that solve real problems like automating recruiting, personalizing learning, or improving retention, rather than chasing shiny objects.
How agentic workflows reshape HR strategies with AI
Agentic AI will push HR tech in 2026 from smart tools to semi-autonomous digital coworkers that HR leaders must hire, onboard, govern, and measure as part of the workforce.
We’re closer than people think to narrow, well‑bounded agentic workflows. We’re much farther away from credible, fully autonomous HR.
HR as a function cannot rely entirely on agents. We are too nuanced to automate much of what we do in HR — remember, the "H" in "HR" is still "Human."
Agents excel at repeatable, rules‑based, multi‑step work such as routing tickets, answering policy questions, validating data, and nudging employees through processes. They are not ready — and may never be fully ready — for work that requires deep context, political judgment, empathy in conflict, or reading the "temperature" of a culture.
HR is one of the most context‑heavy, emotionally loaded functions in the business. The same policy applied to two people can have totally different implications based on history, power dynamics, equity, and culture.
That nuance is why we believe agentic AI should take work off humans’ plates, not take humans out of the loop. The ‘H’ in HR stays human—especially where trust, fairness, and dignity are on the line.
HR is one of the most context‑heavy, emotionally loaded functions in the business. The same policy applied to two people can have totally different implications based on history, power dynamics, equity, and culture.
Why HR leaders must treat AI as a work-design challenge
My advice to HR leaders is to stop treating AI as a side project and start treating it as a work-design problem. The winners in 2026 will be the teams that pair a clear use case with strong governance, then redesign workflows, decision rights, and manager habits around it.
For HR leaders: Start small, but start with something real. Pick one painful workflow where AI can remove friction—like HR service, onboarding, knowledge retrieval, or case triage — and measure whether it improves speed, quality, and employee experience. AI adoption still fails when leaders confuse experimentation with transformation, so the goal is to change how work gets done, not just add a new tool.
For all leaders: My broader advice is to lead with curiosity, but also with discipline. AI maturity is not about how many tools you adopt; it’s about knowing where AI creates value, where it creates risk, and where human judgment must stay in the loop.
A simple way to say it: don’t automate the dysfunction. Fix the workflow, define the boundaries, and use AI to make great work easier to do.
Follow along
You can follow along with Jay Polaki's work on LinkedIn, Facebook, or Instagram. Or check out HR Geckos.
More expert interviews to come on People Managing People!
