The pace of AI adoption is often described as unprecedented, but hearing it through the lens of research paints a clearer picture. According to Deloitte, the AI journey for HR can be divided into three broad phases:

Early excitement (2022–2023)

This period was marked by questions about accuracy, hallucinations, and whether AI could be trusted for people-related work. Teams were curious but cautious.

Tool-first experimentation (2023–2024)

Vendors emphasized use cases. HR leaders were pitched scenario modeling, policy search, case summarization, and automation promises. But many early pilots stalled because organizations focused on capabilities rather than readiness or workflow change.

Human-centered adoption (2024–2025)

In the past year, the shift became clear. HR now understands AI enough to:

• Ask better questions
• Define their own use cases
• Expect measurable impact
• Push for strategic alignment rather than novelty

As Claire explained, potential customers no longer need to be convinced. They arrive with specific problems in mind and a clear sense of how AI can support their teams.

“We’re seeing proactive HR leaders come in with their use cases already defined. That is a major shift from just a year ago.”
— Claire Schmidt

AI is no longer viewed as an abstract threat or a distant opportunity. It’s becoming a practical part of day-to-day decision support.

Why cocreation is replacing best practices

One of the most surprising insights from Kyle was the shift from best practice thinking to cocreation. For decades, organizations looked to consultants and vendors for the “right answer.” Today, those answers don’t exist.

Why cocreation works better now

• Every company is at a different stage of AI maturity
• Every workforce has different demographics and constraints
• AI models depend heavily on the organization’s own data quality
• HR’s tech stacks and operating models vary widely
• Leading practices are often only “three months ahead,” not years

This has changed how HR leaders engage with AI partners. Instead of asking for perfection upfront, they’re asking:

• What can we build together?
• How do we tailor this to our strategy?
• What will this look like when our people use it?
• How do we make this sustainable and trustworthy?

“In AI, the leading practice is usually someone who’s only a few months ahead of you.”
— Kyle Forrest

The cocreation mindset encourages experimentation and aligns AI with the organization’s real needs instead of generic templates.

Digital twins and the evolution of organizational modeling

A standout moment in the conversation was the exploration of digital twins — a concept that’s existed for years in manufacturing but is now entering HR and knowledge work.

A digital twin of a person

This is a virtual representation of an employee’s patterns, knowledge, and workflows. It raises complex questions about:

• Access to data
• Permission-based visibility
• Privacy laws (especially in the EU)
• Accountability and accuracy
• Delegation of tasks or decision authority

A digital twin of an HR function

This is where it becomes especially interesting for HR leaders. Imagine:

• Running multiple “what-if” scenarios on workforce planning
• Testing org design changes before implementing them
• Simulating how changes to job architecture affect capacity
• Modeling service delivery at different headcounts

For HR leaders planning for 2026, this could redefine strategic planning.

Digital twins won’t replace judgment, but they could dramatically expand HR’s ability to test decisions before executing them.

The new HR tech stack strategy in an AI-first world

When asked how AI is reshaping tech stack strategy, Kyle outlined three major changes:

The hybrid model is winning

The old “one platform versus best-of-breed” argument is evolving. Organizations want a strong core HCM with selective best-in-class tools that integrate seamlessly. Not everything needs to be consolidated, but it does need to be connected.

Enterprise AI tools are becoming unavoidable

Employees expect flexible tools like Copilot, ChatGPT, or Gemini to help with writing, analysis, and research. This affects HR because many use cases (writing reviews, drafting goals, summarizing notes) don’t require a vendor-specific workflow.

AI requires cross-functional integration

Work rarely lives neatly within one system.
If an HR workflow requires Finance or Legal input, the tools must interoperate to deliver value.

Claire added another critical dimension: data sensitivity. For functions like employee relations, exporting data to external tools is risky, which reinforces the need for tight, internal AI capabilities that maintain confidentiality and granular permissions.

This aligns with an emerging principle:
Secure AI will increasingly differentiate HR systems in 2026.

What HR should expect in 2026

The forward-looking portion of the discussion included some of the session’s most compelling insights.

Measurable value will become easier to prove

Deloitte expects clearer ROI examples, especially at the individual and team levels. Organizational ROI may take longer, but 2026 will show meaningful movement.

New HR roles will emerge

Job titles like:

• Human and AI Collaboration Designer
• Work Engineer
• Workforce Innovation Lead

These roles focus on integrating technology into day-to-day work rather than simply maintaining HR systems.

Compute power will continue doubling every 6–7 months

This changes what is possible, how quickly tools evolve, and how HR teams prepare people for new capabilities.

Admin and operations automation will surge

Research shows the highest ROI in AI comes from administrative tasks and ops workflows.
HR teams will increasingly automate:

• Drafting
• Summarizing
• Scheduling
• Process routing
• Basic analysis

This frees HR for strategic work that requires human context.

More integrated insight ecosystems

Employee sentiment, performance, ER cases, and engagement metrics will become interconnected, enabling more predictive analysis.

“When these signals can be tied together, predictive analysis becomes possible.”
— Claire Schmidt

How HR leaders can prepare their organizations for AI

The speakers provided clear guidance for HR leaders preparing for 2026.

Make AI adoption collaborative

Employees should be part of defining where AI is used and how it supports their work. This builds alignment early and increases adoption.

Communicate, then communicate again

The narrative matters. Employees need to know:

• What AI is doing
• What it’s not doing
• How they will benefit
• How their workflows will change

Redesign work, not just tools

AI’s value is unlocked when processes are redesigned around it. Bolting AI onto outdated workflows creates friction and reduces impact.

Build psychological safety around experimentation

HR must create a culture where employees can try AI tools without fear of being judged, replaced, or penalized.

“People need to understand if AI saves them five hours, what happens next. Without that clarity, adoption suffers.”
— Kyle Forrest

Building trust, transparency, and alignment

Trust was a central theme.

Deloitte’s research shows workers prefer consumer AI tools over corporate tools when trust is unclear. To build trust, HR needs to articulate:

• What data is used
• How the AI was trained
• What is retained or logged
• Who can see the outputs
• Why AI is being deployed
• How decisions are made when AI is involved

Transparency reduces fear, increases adoption, and builds long-term credibility.

Claire emphasized that trust is not static. It requires ongoing communication, clarity, and responsible design.

How AI will reshape the nature of work itself

The future of work is not only about AI capabilities — it is also shaped by workforce realities.

HR work will split into AI-supported and human-first tasks

Every employee will eventually maintain their own “two lists”:

1. Tasks where AI adds speed, accuracy, or scale
2. Tasks requiring empathy, context, strategy, or critical judgment

These lists will shift over time as AI matures.

Future skills will become universal requirements

Kyle emphasized four skill areas that every employee — not just HR — will need:

• AI fluency
• Business acumen
• Data storytelling
• Decision literacy

Demographics will drive AI adoption

Aging populations, declining birth rates, and regional workforce variations will influence how organizations use AI to augment work.

This part of the conversation made one idea clear:
AI will reshape work, but HR will reshape how people adapt to it.

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