Agentic AI Can't Optimize HR Without This First Step
Agentic artificial intelligence (AI) is transforming how HR, payroll and IT teams work, but it can only deliver on its promise if data is properly integrated.
As organizations adopt agentic AI, many discover the same constraint: Their systems lack sufficient communication for agents to function seamlessly end-to-end. That's why data integration should be the foundation of every agentic strategy, especially for HR, payroll and IT leaders hoping to unlock meaningful automation at scale.
Data integration or agentic AI: Which comes first?
Agents require access to data from multiple software systems to think, plan and act with sufficient context. Even the most advanced agent can't effectively automate a multistep workflow if it can't use integrated data.
"Agents need to work across multiple software systems to be truly effective," says Anthony Maggio, vice president, general manager, ADP Marketplace. "Today, agents operate within a system, which is useful and a great starting point, but they need to partner with other systems to deliver high-value business outcomes. Now, just because agents can work across multiple systems doesn't mean they can correlate or map data within those systems. That's why we have data integration. It's fundamental to getting the most out of agents."
Solution: Application programming interfaces (APIs) and connectors help integrate data from multiple systems, providing agents with a stable, interoperable environment to make informed decisions and deliver effective workflow automation.
Agentic AI workflows, without data integration
In a multisystem environment where agents lack access to integrated data, they may operate individually, leading to constant rather than minimal human intervention.
"To unlock the full potential of agentic AI, we must connect single-system silos through proper data integration," says Shivang Patel, chief product officer, ADP Marketplace. "Otherwise, we're relying on constant monitoring to fill in the gaps, undermining the whole purpose of automation."
Disconnected operation means missing organizational context, inaccurate and incomplete insights, surface-level recommendations and irrelevant steps, all of which require significant oversight to correct.
In such environments, leaders may find agents ineffective, and still be heavily involved in:
- Completing onboarding tasks: Creating, editing, sending and continually updating new-hire welcome emails, uploading onboarding forms, tracking completion and manually following up
- Setting up candidate interviews: Drafting interview invitations, scheduling meetings, generating meeting links, creating and sending reminders and updating system statuses
- Comparing data with colleagues: Exchanging spreadsheets and coordinating updates with various departments to reconcile discrepancies
These steps are time-consuming, error-prone and dependent on practitioners being the connective tissue between disconnected systems.
Agentic AI workflows, with data integration
When data is properly integrated, agents gain access to a comprehensive informational picture, letting them make connections and orchestrate workflows with sufficient context. With the ability to access and influence HR, payroll, recruiting, time and attendance, benefits and finance systems, agents can complete multistep tasks, including onboarding, interview scheduling and data reconciliation, all with minimal human involvement. That's the power of data integration.
How it works: APIs, connectors and prebuilt solutions, integrated with industry-leading service providers, keep data mapped, synchronized and current, giving agents a trusted foundation for cross-system action.
"Agents working with integrated data can help organizations strengthen decision making and automate workflows," Patel says. "With the right connections and agentic partnerships, leaders can make better, necessary decisions using insights from the agents themselves. Teams can also implement agentic workflows, which are becoming more sophisticated and autonomous every day."
How can HR, payroll and IT achieve data integration?
HR, payroll and IT: HR, payroll and IT can support data integration by collectively examining their organization's technology ecosystem and deciding which data is most important to the business. Are there data sources that help generate new customers or clients, improve operations or enhance decision making, for example? Don't get bogged down by bits and bytes that don't drive business value. Focus on data that matters, then ensure the data is accurate, complete, consistent and up to date through careful data management processes.
HR: HR can support data integration by standardizing fields, cleaning up duplicate records and documenting how employee data should flow through the life cycle. These processes are crucial to enhancing consistency and giving agents a reliable framework for automation. HR can also champion workforce data privacy and the need for user consent.
Payroll: Payroll can support data integration by aligning pay codes, job codes and earning types, ensuring consistent arrival of time and attendance data and phasing out manual spreadsheets.
IT: IT can play a critical role in data integration by shifting to marketplace-driven APIs and connectors, platforms that enable custom integrations and developer agents as they become available. Well-governed APIs, monitoring and access controls can also help IT maintain reliable data flows. This transition can help reduce long-term maintenance, standardize security, expedite code creation and safeguard integrations as vendors update their software.
Top priorities: Human oversight and ethical data management
While agents can act independently, they still need people — experts, seasoned professionals, skilled workers — to prepare data, guide outcomes, validate outputs, create guardrails, enforce ethics policies and intervene when complex problems can't be solved by agents alone. In some cases, agents aren't autonomous but semiautonomous, meaning they operate not as independent actors but under predefined rules and parameters with humans providing oversight as necessary.
Regardless of autonomy level, don't think of agents as hands-off, as they may be able to access employee data and other company information, depending on the specifics of their operational environment. Strong governance — with consent, transparency, security and oversight — is critical and should be implemented long before agents are deployed.
The bottom line
Agentic AI can help leaders enhance decision making and workflow automation, but only when supported by robust data integration and human oversight. One of the fastest, most scalable ways to achieve data integration is through a modern marketplace of APIs, connectors and prebuilt solutions integrated with leading service providers. This approach gives agents the clean, connected and consistent data they need to think, plan, act and deliver value across the entire business ecosystem.
If you want agentic AI to deliver on its full promise, the next step is abundantly clear: Adopt a solution with an integration marketplace built for the future. Discover ADP Marketplace today.
Brett Daniel contributed to this article.
