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AI in HR CONFERENCE
Industry initiative by
AI-native performance and enablement platform
executive summary
AI can reshape HR end to end. The real priority now is redesigning how the work gets done around it.
AI now fits across the entire HR life cycle, but most teams have deployed it only in recruiting. The blocker is not the technology, it is the readiness of the processes and data underneath.
WHERE THE MARKET STANDS
Most HR teams haven't adopted AI yet
39%
of companies use AI inside HR
64%
of HR AI use is in recruiting
95%
of AI pilots fail on integration into real workflows
60%
of large firms use AI in HR, against about 30% of small ones
Key trends
01
From buying tools to preparing processes
The hard part is no longer choosing the tool. It is getting the work ready for it: clean data, clear workflows, defined roles, and enough manager trust to let AI actually create value.
02
Training becomes a continuous loop
Learning is moving from a slow, centralized content model to a continuous system where expertise turns into practice, performance data shows what needs to improve, and training evolves as fast as the work itself.
03
Pushback on tool sprawl
With a new AI tool launching every week, teams are moving away from buying a niche product for every task. The shift is toward getting more value from the platforms and LLMs they already pay for.
04
Data governance is the first filter
For sensitive HR work, the question is no longer what the tool can do, but where employee data lives, who can access it, and whether the system has the controls to be trusted.
AI workflows
01
Clear your inbox before 9am
- Set up Claude with Skills that read your inbox and Slack through MCP
- Flag what needs a reply today
- Draft the responses into your drafts folder, and summarize unanswered threads
- Schedule it to run every morning in the cloud with your laptop closed.
02
Use AI as a second reader on sensitive work
- Bring an anonymized description of the situation to the model
- Ask it to stress-test your approach: what am I not asking, what would a reasonable person challenge, what am I assuming
- The judgment and the conclusion stay yours. Start with documentation, the lowest-risk entry point.
03
Automate return-from-leave
- Build an agent in Make or n8n that checks your HCM each day for employees coming back from leave
- It sends them a welcome-back message, reminds the manager to reconnect
- Then it collects feedback, and hands unusual cases to HR
- Every returning employee gets a consistent check-in and HR stops tracking returns by hand.
04
Build a reusable content repository in MS Copilot
- If your team runs on Microsoft 365, stop rebuilding the same context every time
- Save the prompts you reuse in Copilot's Prompt Gallery
- Keep your recurring HR assets in its Library, things like strategy and competency models, interview guides, onboarding toolkits, and succession templates
- Group them in a Notebook so Copilot works from them on every task
- Use its audio overview to turn a long document into a podcast you can listen to on a walk.
Where to start
Fix what is broken
Clean your data and your messiest process, usually onboarding, before any AI sits on top.
Start with a problem, not a tool
Define what success looks like in numbers.
Keep the toolkit small
One paid LLM with Projects and Skills covers most of the work.
Keep a person in the loop
on anything that matters. AI assists, it does not decide.
Protect your data
No sensitive information in public tools; check each vendor's security.
Give it 6 to 12 months
and measure against the goal you set.
Available on demand
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Alexandra Gyetvai
Head of Operations, Superlinked
Suzanne Lucas
Founder, Compass HRC
James Baker
Head of Growth, Evolve
and 3 more speakers with real cases, tools, and processes you can bring to your team in the coming months
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