Eric Connors, Chief Product Officer at ICIMS – Interview Series

Eric Connors, Chief Product Officer at ICIMS, leads the company’s product strategy and product management organizations, shaping the vision, roadmap, delivery, and go-to-market strategy for its portfolio. He brings more than three decades of experience spanning enterprise software, SaaS, financial technology, data, and product leadership. Before joining ICIMS in 2024, Connors served as Chief Operating Officer and previously Senior Vice President of Product Strategy & Management at ICE Mortgage Technology, where he oversaw areas including strategy, product management, compliance, and corporate development. Earlier, he held senior leadership positions at CoreLogic and Yodlee, where he helped scale product operations, launch new offerings, and support Yodlee through its 2014 IPO and subsequent acquisition. His career also includes strategic and product leadership roles at Oracle, PeopleSoft, Campbell Software, and Gap. In parallel, he has operated Eric L. Connors Consulting since 2015, advising software and data companies on product strategy, organizational scaling, executive leadership, and growth.

ICIMS is an enterprise talent acquisition technology company whose platform helps organizations attract, engage, hire, and advance talent across the recruiting lifecycle. Its product suite spans applicant tracking, candidate relationship management, career sites, onboarding, internal mobility, high-volume hiring, analytics, and AI-powered recruiting capabilities. The company is increasingly positioning its platform around intelligent and agentic hiring workflows, including AI-powered sourcing, hiring, and interview-scheduling agents designed to automate repetitive recruiting work while keeping hiring data and workflows connected. In 2026, ICIMS also outlined its broader vision for an Intelligent Hiring Platform, building on more than two decades of recruiting data and workflow expertise as AI becomes more deeply embedded in how employers source and evaluate talent.

You’ve spent much of your career leading product strategy across major enterprise software and data businesses, including Yodlee, Oracle, PeopleSoft and ICE Mortgage Technology before joining ICIMS. How has that experience shaped your view of what AI agents need to get right before enterprises are willing to trust them to take meaningful actions on their behalf?

Every business I have worked in was trusted with something that mattered to people, whether that was their financial accounts, a mortgage closing or a payroll run. In those environments, software earns responsibility in increments. Companies hand more work to a system once it has shown it understands the rules of the business, behaves predictably and leaves a clear record of what it did and why.

AI agents have to clear the same bar, and I think three things need to be true. The agent has to understand context, including the company’s policies, permissions and workflows and the specific situation in front of it. Its actions need guardrails that the customer sets and controls. And everything it does has to be visible and traceable. The technology to do this is already here. What holds companies back is readiness, meaning how willing they are to cede control in a domain as high-stakes as hiring. When enterprises get this right, the results show up in hiring itself. Decisions move faster, recruiters spend less time on follow-up and teams hire with more confidence in the people they choose.

ICIMS describes recruiting technology as evolving from a passive system of record into an intelligent system capable of understanding context and taking action. What does that transition ultimately look like, and how different will the recruiting platform of the future be from the applicant tracking systems organizations use today?

The recruiting platform of the future actively participates in hiring. It knows the recruiter’s service levels, the hiring manager’s preferences and the team’s policies, and it acts on them. If a candidate cancels an interview, the system already knows who else could step in and proposes the fix before anyone has to chase it down.

The most visible difference from today’s ATS is that far fewer people will log into it. Recruiters, hiring managers and candidates will work through the tools they already use, such as Teams, email, messaging and voice. Underneath, the platform coordinates agents, pulls signals together and brings decisions to the right person at the right moment. While the ATS may become invisible as people interact with it less directly, it will also become more important, because every agent working on top of it depends on the context, governance and hiring data it holds.

That is the direction behind the ICIMS Intelligent Hiring Platform, which brings trusted AI, hiring intelligence and automation together across the hiring journey. For enterprise hiring teams, that means candidates spend less time waiting between stages and hiring managers decide with better information, which leads to faster time to hire and stronger quality of hire.

The new ICIMS Hiring Agent brings candidate reviews, feedback and approvals directly into Microsoft Teams. Is this indicative of a broader shift in enterprise software where users interact less with individual applications and AI agents increasingly become the interface connecting those underlying systems?

Yes, and hiring is one of the clearest examples. Hiring managers play a central role in recruiting, but reviewing candidates and giving feedback is a small part of their day. When those tasks require logging into a separate system, requests sit and recruiters end up following up by hand.

The ICIMS Hiring Agent is an AI agent that brings candidate reviews, interview feedback, approvals and recruiter collaboration directly into Microsoft Teams, where many hiring managers already work. It also helps them prioritize what to do next based on hiring context and urgency. When hiring managers can review candidates and approve requisitions within their existing workflow, candidates move forward sooner, recruiters spend less time chasing feedback and time to hire improves.

ICIMS remains the system of record underneath, and every action taken in Teams flows back into the hiring workflow with the same data, permissions and controls. I expect that pattern to spread across enterprise software. Interfaces will gather around where people communicate, and the systems underneath will matter more because agents rely on their context and governance. We are starting with Microsoft Teams and plan to extend to additional collaboration platforms in 2027.

There is a significant difference between an AI assistant that recommends an action and an agent that actually executes one. How do you determine which recruiting decisions can safely be delegated to AI and which should always require explicit human judgment or approval?

We look at how consequential an action is and how easily it can be reversed. Coordination work such as sending reminders, scheduling interviews, updating status and running outreach from pre-approved messaging takes a lot of effort, carries low risk and is easy to correct. That is where agents should carry the load. Decisions that shape a person’s opportunity, such as advancing, declining or extending an offer, belong with people.

Our products are built on that principle. With the ICIMS Hiring Agent, hiring managers make every decision, and the agent handles the follow-through with reminders for outstanding tasks, prioritized next steps and faster access to candidate context. The ICIMS Sourcing Agent identifies, matches and engages qualified candidates from an organization’s existing talent data, and admins decide when, where and how much autonomy it has. That control should stay with the customer, because organizations will be comfortable at different levels and that comfort will grow as they see results. Handing coordination to agents gives recruiters time back and keeps candidates from stalling between stages, while people stay accountable for the decisions that shape quality of hire.

The ICIMS Sourcing Agent can already identify candidates and support outreach, while the new Hiring and Interview Scheduling Agents extend agentic AI further into the recruiting workflow. How do you see these specialized agents eventually working together? Could we reach a point where multiple agents coordinate an entire hiring process while humans primarily supervise exceptions and important decisions?

That is where this is heading. Each ICIMS Agent can work on its own today, and customers can adopt them one at a time, but the vision is for them to work together. The ICIMS Sourcing Agent finds and engages talent. The ICIMS Interview Scheduling Agent will use AI to check availability, book interviews, manage changes and keep candidates and hiring teams informed. The ICIMS Hiring Agent will keep hiring managers and interview teams moving. As handoffs between sourcing, scheduling and hiring manager review happen automatically, time in stage shrinks and requisitions get filled faster. 

We are starting with customer-configured automation and building toward coordinated intelligence that supports people across the entire workflow. Over time, agents will run most of the operational steps from requisition to offer, and people will focus on exceptions, judgment calls and the decisions that define a hire. The pace depends mostly on how quickly organizations build trust and adapt workflows that have been in place for decades.

Recruiting is an unusually sensitive environment for autonomous AI because its actions can directly affect people’s career opportunities. What technical safeguards, auditability and transparency do you believe must be built into recruiting agents before companies should give them greater autonomy?

Governance has to come first, and it has to be built in from the start. At ICIMS, our Responsible AI program governs how we design, build and deploy AI across our platform. It starts with a code of ethics that commits our AI to being human-led, transparent, private and secure, inclusive and fair, technically robust and safe and accountable. Cross-functional committees review every AI capability we develop and oversee annual bias audits and AI risk assessments. The program is also independently validated. ICIMS was the first enterprise recruiting software provider to earn TrustArc’s TRUSTe Responsible AI Certification, and our practices align with the NIST AI Risk Management Framework, the OECD AI Principles and ISO 42001.

Agents raise the stakes, so we have added three requirements. Autonomy should be configurable, so the customer decides how far an agent can go and can adjust that over time. Agents should inherit permissions from the system of record, so they only see and do what the person they’re acting for could. And every action needs to be explainable to a candidate, a regulator or a board.

Many talent acquisition teams are adopting AI faster than they are governing it. Our research found that 82% of companies say transparency and explainability in AI systems are important, yet 45% do not have a formal AI governance framework in place. When that gap goes unaddressed, decisions about who moves forward get made in ways no one can fully explain. That creates legal exposure, since existing anti-discrimination laws already apply to AI-informed hiring decisions and regulations such as NYC Local Law 144, the Colorado AI Act and the EU AI Act add new requirements. It also erodes candidate trust, and quality of hire slips when strong candidates drop out or get screened out without anyone noticing.

When governance is in place, recruiters trust AI recommendations enough to act on them. Hiring managers make faster decisions on shortlists they know were built on defensible criteria, and candidates get a fairer, more consistent process. That foundation is what makes it possible to give agents more autonomy over time.

ICIMS argues that its advantage in AI comes partly from more than 25 years of hiring context and billions of hiring interactions. As foundation models become increasingly commoditized, do you expect proprietary domain data, workflow knowledge and organizational context to become the real competitive moat for enterprise AI agents?

Yes. Once every company has access to roughly the same models, the models become table stakes. What sets companies apart is context, meaning years of hiring manager preferences, interview outcomes, what actually predicted a good hire, how a specific team works and what candidates responded to. Intelligence turns that data into a decision worth trusting, and trust is what makes a company willing to let an agent act.

That is why we built the Intelligent Hiring Platform on more than 25 years of hiring data and workflows. ICIMS supports hiring activity for thousands of organizations around the world and more than 691 million candidate profiles. In 2025 alone, we processed roughly 243 million applications and helped our customers make more than 5.1 million hires through our platform. Every interaction creates signals, and those signals build the context behind better decisions. That context shows up in results. Research found ICIMS customers see more qualified applicants, greater recruiter efficiency and more business improvement goals met than organizations using HCM suites or point solutions. Companies that bolt AI onto a shallow data set risk automating their guesswork and reaching the wrong answer faster, and that gap compounds every year.

AI agents can potentially reduce administrative work for recruiters, but they could also fundamentally change what the recruiting profession looks like. Which parts of a recruiter’s role do you expect AI to absorb, and which human capabilities become more valuable as agents take over more of the operational workload?

AI will take on the operational drag, including screening logistics, scheduling, status chasing, following up with hiring managers and repetitive sourcing work. Those tasks take up a big share of a recruiter’s week and do little to improve the quality of a hire. The ICIMS Sourcing Agent is an early example. It rediscovers silver medalists, past applicants and dormant profiles already in a company’s database, which helps teams fill roles faster and spend less on external sourcing.

What remains is work that requires human judgment. Recruiters will shape talent strategy with business leaders, handle complex negotiations, build close relationships with candidates and advise hiring managers on who is right for the team. In that sense, recruiters become talent advisors. The market is still early in this shift. Our research found that 69% of companies use AI in talent acquisition, while only 12% have adopted agentic AI that can act on a user’s behalf. As that gap closes, the recruiters who do well will treat agents as added capacity and put the time they get back into the parts of the job that drive hiring outcomes.

Agentic systems also introduce a new integration challenge: enterprises may eventually have recruiting agents, HR agents, productivity agents and general-purpose agents operating across the same organization. How important will interoperability between agents and platforms become, and who should ultimately control the permissions and context shared between them?

It will be essential. Enterprises will run many agents across recruiting, HR, productivity and general-purpose tools, and hiring touches all of them. The ICIMS Hiring Agent working inside Microsoft Teams is an early example of a recruiting agent operating in a productivity environment, and that kind of connection will become normal. Open ecosystems matter a great deal here, which is why we have invested in extensibility with more than 800 marketplace partners and more than 10,000 API-based integrations. Connected agents also give candidates and hiring teams a smoother experience, since work moves across systems without the manual handoffs that slow hiring down.

Control should sit with the enterprise, with the system of record enforcing its rules. Candidate data is personal and often regulated, so agents should only get the context they need for a task, under the same permissions a person in that role would have. Each platform should govern its own domain and share context through clear, auditable rules the customer sets. In hiring, the ATS plays that governance role, which is a big part of why I believe the platform grows in importance as agents multiply.

Looking beyond the agents ICIMS has announced today, what do you think will be the next major breakthrough in agentic recruiting AI? What capabilities that still seem difficult today do you expect recruiting platforms to be able to deliver as the technology matures?

I think the next breakthrough is agents working on both sides of the hiring relationship. Candidates will increasingly be represented by AI career agents that know their validated skills, work history and market value and continuously scan for opportunities they might never have found on their own. Hiring managers will work with an agent that translates a business need into a skills profile, surfaces ranked candidates with available performance data and structures the evaluation itself. The manager still makes the call, with far more confidence and far less guesswork.

The other shift is connecting hiring to performance. Most hiring systems stop learning once someone accepts an offer. As platforms link hiring decisions to how people actually perform and grow, they will get better at predicting quality of hire, and the line between recruiting and retention will start to blur. The result will be hiring that moves faster, better predicts performance and keeps more of the people companies hire. Much of the technology to do this already exists. The companies building AI fluency, governance and deep context now will define what great talent acquisition looks like on the other side of this transition.

Thank you for the great interview, readers who wish to learn more should visit ICIMS.