In our latest roundtable, workplace leaders, HR professionals, and industry experts explored a key question:

How can HR leaders adopt intelligent technologies to drive real impact—while balancing innovation with people-first priorities?

The discussion uncovered patterns and practical insights. While many organizations see early benefits, scaling adoption across teams and aligning it with culture remains a challenge. HR is in a unique position to guide this shift—connecting tools to trust, and strategy to experience.

This guide distills those insights into clear actions for those designing intelligent work.

1. Adoption Begins with Practical Use Cases

The “AI adoption gap” reflects a divide in perception, access, and motivation between leadership and frontline employees.

Most organizations begin adoption on the periphery—tactical or exploratory use—before it scales. Quick wins help demonstrate value and ease fears of the unknown.

Use cases include:

• Automating workflows, drafting stakeholder emails, and summarizing meetings.
• GPT-generated learning paths and coaching support.
• Text-to-video training content.
• Chatbots are used in customer support and internal help desks.
• Writing job descriptions, internal comms, and policy documents.

“Start small. Use it for something simple like internal comms or a job description—and you’ll be amazed.” – Anthony Onesto (Suzy, AI in HR Today)

What HR can do:

• Normalize experimentation in a safe environment to try, fail, and play.
• Start with small pilots—run AI alongside current workflows to build confidence and reduce fear.
• Highlight early AI superusers as champions.
• Share prompt libraries and templates across departments.

2. Delegation = Adoption

Those who delegate effectively tend to adopt AI more easily. Delegation signals trust, maturity, and readiness to evolve, and there are clear differences in delegation habits between executives and employees.

Executive-level users:

• Work across functions
• Delegate routinely
• See AI through a capitalist lens: efficiency, productivity, growth

“Delegation is a strong predictor of AI adoption. Executives know how to delegate to humans, so it's less of a cognitive leap to delegate to AI.” – Dr. Rebecca Hinds (Asana Work Innovation Lab)

What HR can do:

• Celebrate task delegation and outcome sharing.
• Coach teams to develop delegation skills, view AI as a partner—not a threat—and shift from a “writer” to “editor” mindset focused on directing, not just doing.

3. Shape the Role of AI Agents Intentionally

If AI tools are seen as co-workers or digital teammates, then HR plays a crucial role in their selection, design, and enablement.

Examples include:

• Chatbots supporting tech teams
• Internal GPT agents for knowledge management
• Smart assistants for goal-setting and policy search

However, AI agents are still treated inconsistently—approved in one area, banned in another. IT, legal, and security teams often implement broad restrictions due to concerns around data protection and uncontrolled tool usage without offering clear alternatives.

This creates confusion and slows innovation.

“Maybe part of this is giving HR use cases or templates to go to their IT and security folks to get approvals for these kinds of things.” – Anthony Onesto (Suzy, AI in HR Today)

What HR can do:

• Collaborate with IT and Ops to standardize use.
• Design roles and behavior patterns for agents, aligned with company values.
• Treat AI agent rollout as part of employee experience design.

4. Build a Culture of Safety and Access

When official access is restricted, shadow use of AI increases. Employees turn to personal accounts and devices to get work done, bypassing company policies and raising privacy and security risks.

In regions with strict regulations like the EU, concerns around GDPR compliance and uncontrolled data sharing add complexity, often leading organizations to hesitate rather than enable safe, sanctioned use.

Employee-level users:

• Worry about being judged as “lazy” or “fraudulent”
• Fear job displacement
• Lack clarity on what is allowed or encouraged

What HR can do:

• Issue enterprise tools with privacy and compliance safeguards.
• Encourage safe experimentation through official channels.
• Provide a “What’s Allowed” cheat sheet for easy employee reference.
• Create cross-functional review boards (HR, IT, Legal) to accelerate approvals.
• Regularly audit and update policies based on real-world usage patterns.

“You can’t stop people from using new tools. You can only guide them to use them well.” – Daan van Rossum (FlexOS)

5. Personalize the Learning Journey

Tailoring adoption efforts by role, region, and mindset is more effective than one-size-fits-all training.

Segments include:

• AI skeptics vs. enthusiasts
• Executives vs. frontline staff
• Technical vs. people-centric roles

Training methods that work:

• Modular learning tracks
• Microlearning through prompt libraries
• Balanced messaging that shows both potential and limitation

“Technology rarely fails because of what it can do—it fails due to human resistance.” – Dr. Rebecca Hinds (Asana Work Innovation Lab)

What HR can do:

• Let GPT-style systems train users on how to use AI.
• Integrate human psychology into enablement strategy.
• Offer role-specific learning paths based on job functions and comfort levels.
• Use microlearning formats (e.g., 5-minute tutorials, weekly tips) to build habits gradually.

6. Match the Tools to Workflows

Adoption thrives when intelligent tools mirror how work already happens. In this way, cross-functional collaboration, async workflows, and open knowledge-sharing matter.

Key factors:

• AI tools can break down silos and spark learning across departments
• Personal GPTs provide quick answers
• Learning catalogs, onboarding, and employee queries are faster when powered by AI

Yet, Gartner observes productivity leakage—time saved by AI is not always reinvested into team output. Workers gain work-life balance, but leadership may not see the measurable gains.

“There’s a gap between executive optimism and employee adoption.” – Daan van Rossum (FlexOS)

What HR can do:

• Track time savings and repurpose for innovation or growth
• Create cross-functional councils for prompt-sharing
• Use tools that support asynchronous work habits

7. Design for Long-Term Integration

The maturity curve mirrors early cloud adoption—initial skepticism, then reliance. AI today resembles the early internet era.

Corporate culture still struggles with:

• Blanket bans driven by fear
• Siloed experimentation
• Lack of governance

Forward-looking companies:

• Involve HR early in AI strategy design alongside IT and Legal
• Shift from controlling access to enabling smart experimentation

“We need to be looking for ways to work differently. The real value is in rethinking the work.” – Edie Goldberg (SHRM, E. L. Goldberg & Associates)

What HR can do:

• Lead change with clear messaging, frequent Q&As, and transparent policies.
• Create an AI enablement roadmap that includes milestones, champions, and check-ins.
• Acknowledge and support the “forgotten generation” with upskilling plans and coaching.
• Build cross-functional AI working groups with IT, Legal, and business leaders.

Conclusion: HR Guides the Evolution of Work

HR leaders are in a pivotal position to shape how intelligent tools enhance, not disrupt, the workplace. By translating hype into purpose, enabling responsible experimentation, and aligning technology with trust, HR ensures that innovation serves everyone. The goal is not just smarter work but more inclusive, human-centered progress where no one gets left behind.

Thank you to all contributors—and to BambooHR for making this roundtable possible.

To explore more resources, visit: bamboohr.com/courses/ai-in-hr