A Swiss Army Knife of AI Transformation: How HR Can Steer the Ship with Cross-functional Collaboration

From Accounting to AI-driven HR

I began my career as an accountant, but quickly realized it wasn’t my calling. During the dot-com boom and bust, I transitioned into what we now call fractional HR, working with companies in rapidly evolving industries.

My journey truly took off when I joined an early-stage mobile startup and caught the “startup bug.” Since then, I’ve spent most of my career helping young companies build their People strategies, establish operations, and, at times, develop their business models from scratch.

Throughout my career, I’ve gravitated toward organizations disrupting existing industries or pioneering entirely new ones — whether at FreshDirect in e-commerce and grocery, or at SolidStreaming, Zeta, and Big Fuel in mobile, digital software, and social media.

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Anthony OnestoOpens new window

VP of Platform & Product Marketing

My roles have ranged from Chief People Officer and Chief Operating Officer to President, General Manager, and now VP of Platform and Product Marketing at 15Five. This path has given me both deep expertise and a broad perspective across functions and industries.

I consistently faced the challenge of building HR functions from the ground up, often without a template. I thrive in these uncharted territories, and early on, I learned to cultivate a “Swiss army knife” network of advisors — peers at different stages, in varied industries, and even colleagues with diverse backgrounds. These advisors, along with the fast-paced entrepreneurs I’ve worked alongside, have been invaluable to my growth and leadership journey.

How to Bridge the Gap between AI's Potential and Results

There's currently a gap between leadership’s expectations, often set by CEOs, and employees' lived reality.

This isn’t a new phenomenon, it echoes what we saw during the digital transformation and outsourcing waves in the 1990s. Leaders frequently assume they can roll out and adopt new technologies immediately, without fully considering the human side of the equation.

Employees experience understandable resistance or what I call a modern "fight, flight, or freeze" response when faced with sudden changes or technology mandates. If organizations introduce AI tools or outsource tasks without setting clear expectations, involving employees in the process and addressing their concerns, adoption and ROI inevitably suffer.

Center People, Empower HR

To address this, I advocate for HR to lead the AI transformation. Just as with previous waves of change, we must center people. My approach is to ensure open dialogue, provide context and support, and empower HR to champion both the human and technological elements of AI adoption. That’s how we bridge the gap between AI’s potential and practical results.

Why HR Must Be at the Forefront of AI Transformation

Having navigated multiple technological shifts, from the rise of the internet to mobile, social, and now AI, I’ve learned that staying relevant means staying relentlessly curious.

Even before the advent of ChatGPT, I recognized AI’s potential to transform HR and leadership. Nearly a decade ago, I founded a company attempting to use AI to answer routine HR questions. While the technology was nascent and the challenge immense, the experience gave me an early appreciation for how profoundly AI could reshape the field.

I now see this wave of AI as even more transformative than the internet itself.

And HR — a profession that has often lagged as an early adopter of new technologies — needs to get on board.

We have to let go of the idea that HR’s role is reactive or administrative. HR is actually uniquely positioned to lead this AI-driven transformation, bridging the gap between people and technology.

As AI becomes more central, HR must be at the forefront, championing the thoughtful integration of human insight and machine intelligence across organizations.

How AI is Overhauling Recruiting, Retention, and Training

HR is all about finding (recruiting), keeping (retaining), and elevating (training) the right people. Here are some examples of overhauls I've done in each category:

Finding

For recruiting, we partner with Sprouts.ai, an AI-driven recruiting solution. This tool helps us craft job descriptions tailored to our needs. It automatically searches for candidates on various markets and LinkedIn, identifying individuals who meet our requirements.

Sprouts.ai then reaches out to these candidates, using our brand voice and go-to-market strategies, to gauge their interest. The platform provides recruiters with a list of pre-vetted, qualified candidates interested in the roles. Recruiters then schedule calls with these candidates.

While the solution can also conduct interviews, our team has not yet implemented those features. We aim to transition to a process where recruiters primarily engage with a strong pool of fully pre-vetted candidates for sales or closing conversations.

Keeping

For retention, we use Suzy.com to survey individuals within our network, not just our employees. Using AI, we conduct a drivers-and-segmentation analysis, identifying various personas linked to an employee's connection with our company. This analysis reveals the key drivers or elements statistically significant to their engagement and eventual success.

Elevating

We use tools like NotebookLM to provide employees with their own "AI coach." This resource is particularly useful during onboarding, as we populate NotebookLM with essential documents, notes, and other materials.

New employees can then create various types of content to enhance their onboarding experience, including audio podcasts, videos, presentations, mind maps, and chatbots facilitating knowledge sharing across the organization.

Author's Tip

I did something similar at a previous company a few years ago. I implemented an AI-powered Slack app that allowed employees to ask HR-related questions in real time. If the answer wasn’t available or the question was too complex, the system automatically created a ticket for the HR team.

Once resolved, we could add the new answer to the knowledge base, making the system smarter with every interaction.

The impact was immediate: We saw a nearly 30% reduction in HR-related emails and Slack messages. Employees got their answers quickly and could return to work without long waits. And the HR team was freed up for more strategic tasks.

How to Build AI Literacy for Effective Transformation

Here are the steps I follow for building AI literacy:

• Empowering HR as champions: We empower HR to lead the transformation, bridging the gap between human insight and machine intelligence.
• Focusing on use cases over tools: We encourage teams to use tools such as Gemini and NotebookLM for specific outcomes like research, data analysis, and summarized learning rather than simply "using AI" for its own sake.
• Creating a "kitchen cabinet" of advisors: We encourage leaders to build a diverse network of peers who share best practices and navigate AI implementation's uncharted territories.
• Encouraging hands-on experimentation: Using platforms like Lovable, team members with limited coding skills are encouraged to ideate and build high-fidelity apps, proving that AI democratizes technical expertise.

It hasn't been without its challenges, some of which I've already mentioned:

• The "fight, flight, or freeze" response: Sudden mandates often trigger employee resistance. We’ve learned we cannot roll out technology effectively without providing deep human context and open dialogue.
• Favorite AI tool bias: Different departments often accumulate fragmented tools (e.g., Sales using Rattle vs. Product using Pendo), leading to a lack of cross-functional trust in the data.
• Lagging adoption: Historically, the HR profession has been a late adopter of new tech, requiring a concerted effort to shift from a reactive to a proactive, profit-driving mindset.

Why Cross-functional Collaboration is Needed in AI Rollouts

It's amazing how quickly organizations accumulate a vast array of AI tools, mirroring the proliferation of traditional software across departments. Even with powerful, general-purpose platforms like ChatGPT, Gemini, or Claude, individuals and teams gravitate toward their preferred solutions.

This fragmentation becomes even more pronounced at the department level. Every team seems to adopt its own specialized AI tools. Product might use Pendo AI, while sales leans on Rattle, and so on, even with overlapping functionality.

I call this "Favorite AI Tool Bias". People tend to trust insights from their chosen tool more than those from others, sometimes dismissing outputs from other platforms as flawed.

I think this highlights the importance of alignment and cross-functional collaboration when rolling out AI. It’s not just about picking the best technology, but creating shared understanding and trust in the tools we choose as an organization.

How a Long List of AI tools Fit Together

Speaking of tools, here's my AI stack:

• Gemini (and ChatGPT): Coaching, conversations, research, content creation, image creation, and sometimes data analysis.
• NotebookLM: Learning, training, onboarding, and research output.
• Sprouts.ai: Recruiting and sourcing.
• LinkedIn: Recruiting and sourcing.
• 15Five: Performance, engagement, compensation, and AI coaching.
• ADP: HR core and payroll.
• Ashby: Recruiting.
• Kona.ai: Manager and leader coaching.
• Kona Meeting Assistant: Attends meetings to capture transcripts and summarizes performance data from 1:1s.
• Articulate 360 (aka Rise) LMS: Learning and development (though it has minimal AI). We used Gemini, NotebookLM, and ChatGPT for learning content and quiz creation.
• Jira AI: Atlassian Intelligence answers HR policy questions in Slack.
• Zoom AI: Records meetings, provides transcriptions/notes, and documents action items and to-dos.
• Granola: Records internal and external meetings, providing transcriptions/notes. It also offers coaching based on meeting information and transcripts, and documents action items and to-dos.
• Dado: Onboarding.
• Workato: Workflows, but we recently moved to Dado.
• Lovable: Vibe-code-specific solutions that larger platforms cannot handle.

Why Three AI Tools Stand Out Above the Rest

Three tools stand out, and I use them every day.

Gemini: Because Gemini accesses context from my emails, sits in Chrome, and other places, I use it most. I use it to fill in research gaps, analyze documents and some reports, create images, build GEMs for specific use cases, learn about topics, and summarize long reports. This has allowed me to reduce research time, gain insights normally unavailable, use a live "via voice" coach and thought partner, and create reports or analytics without an analyst.

Granola/Kona Meeting Assistant: Granola and Kona Meeting Assistant take speaker output during meetings, creating transcripts, notes, and providing coaching. At our company, Kona Meeting Assistant attends all meetings, providing notes, actions, challenges, and cross-functional insights from a performance lens. Aggregating meetings, themes, and notes has enabled me to create reports, follow up, and hold folks accountable.

Lovable: Lovable built my personal site, my newsletter, and some other tools. I have always worked in a product capacity, but with limited coding skills, Lovable has been a big help. It has expanded my ability to create apps that solve specific problems or needs, ideate new ideas, and see how they operate in the "real world."

How HR Will Drive AI Transformation

Over the next five years, the HR role will transition from a reactive, administrative function to a strategic driver of AI transformation.

• Dissolving expertise silos: AI will democratize knowledge across technical and commercial boundaries, fundamentally changing how teams operate.
• Flattened hierarchies: Organizations will become more flexible, less hierarchical, and more agile as these traits are essential for survival.
• Human-centric integration: Success in the next five years will depend on HR leading the "human side" of technology adoption, addressing employee resistance.
• Increased productivity: AI tools will transform individual productivity to the level of two-person teams, allowing HR professionals to focus on strategic initiatives rather than routine tasks.

Why a People-first Approach is Crucial During AI Adoption

Here's my advice to HR leaders:

• Put people at the center: When adopting new technology, leaders must consider the human element, ensuring open dialogue, providing context, and involving employees in the process to reduce resistance.
• Stay relentlessly curious: To remain relevant through major technological shifts, leaders must remain constantly curious and willing to learn.
• Avoid mandating technology without context: Leaders should not assume they can roll out and adopt technology immediately. Instead, they must address the "fight, flight, or freeze" response employees may feel toward sudden mandates.
• Foster cross-functional alignment: Rather than just selecting the "best" technology, leaders should focus on creating a shared understanding and trust in the tools they choose across the entire organization.
• Build a diverse network of advisors: Cultivate a "Swiss army knife" network of peers and advisors from various industries and backgrounds to help navigate uncharted territories.

Follow along

To follow Anthony Onesto's work as he pushes for HR to take a lead with AI, check out his personal website and his newsletter, AI in HR Today. Or follow him on LinkedIn.

More expert interviews to come on People Managing People!