AI is changing more than how work gets done. It is profoundly reshaping the implicit deal – the “ social contract” between organizations and employees. Traditionally, the employee-employer compact has been predicated on reciprocity: Employees contribute their time, capabilities, judgment, and adaptability; in return, employers provide compensation, opportunity, support, and a credible path forward.
In the age of AI, organizations are introducing an entirely unprecedented array of expectations of employees:, adapt and learn at lightning speed, validate machine-generated output with judgment, be comfortable with deep uncertainties about the future of work, and remain accountable for work now partly produced by AI. Employees, meanwhile, are left to wonder: what do they get in return?
This imbalance matters. A meaningful employer-employee compact has long been the bedrock of effective workplaces. As AI becomes embedded across work, leaders must redefine that compact—and determine with intentionality what employees receive in exchange for embracing and integrating AI.
Seramount’s latest research into workplace dynamics brings together market studies, interviews with senior workplace leaders, and more than 10,000 responses from Employee Voice Sessions. Together, the findings point to four priorities for leaders reshaping the employee-employer compact to realize the transformative promise of AI.
1. Candor About What Is Changing
The average job has seen approximately one-third of its skills change in three years. In many cases, the title remains the same while tasks, skills, decision rights, and performance expectations shift. Given this reality, no leader can credibly promise immunity to change — only clarity about what’s changing.
That clarity starts with open communication. Employees need to understand how their work is changing, which capabilities will become more valuable, how success will be assessed, and where new opportunities may emerge. That matters because employees are not equally positioned to absorb disruption. Some have stronger networks, greater access to reskilling, or managers who can help them navigate what comes next. Leaders can bridge those gaps.
Candor does not require having all the answers. It requires communicating consistently about what is known, what remains uncertain, and when employees can expect to hear more. It also means creating space for employees to share questions and concerns. Leaders must not ask employees to navigate profound change while leaving them to guess where it’s headed- they owe them a map and a compass, beyond mere mandates.
2. The Support and Authority to Exercise Judgment
As AI absorbs more routine and automatable tasks, employees are increasingly becoming reviewers, interpreters, and decision-makers. They are increasingly required to determine how to best deploy AI and assess whether AI-generated results are accurate, appropriate, or ready to be used. As such, AI clearly does not eliminate the need for human expertise. It changes where and how that expertise is applied—from producing the work to evaluating, refining, and standing behind it.
These new responsibilities requires both time and authority. Research from Glean estimates that employees spend an average of 6.4 hours each week “botsitting”: providing AI with context, checking its output, correcting mistakes, and cleaning up confident but inaccurate answers. Employees also need the authority to act on clear standards: what good AI-assisted work looks like, when human review is required, when to escalate a concern, and who ultimately owns the decision.
And they need managers who translate enterprise direction into daily expectations, inclusively enough that employees feel safe using it. Seramount’s EVS data highlights the importance of that relationship. Employees with inclusive managers are about four times as likely to receive adequate feedback and more than four times as likely to feel valued and respected. Those inclusive practices—which foster psychological safety and invite employee contributions—will be central to helping employees use AI as a thinking partner while retaining their own judgment.
Accountability without preparation and managerial support is not empowerment. It is exposure.
3. Access to the Opportunity AI Creates
As organizations exhort employees to become AI-fluent, they must also give employees access to the opportunities that build that fluency.
Training is part of the answer, but fluency is developed through work Employees need latitude to experiment and iterate, and have access to visible AI projects and meaningful stretch assignments. They also need encouragement from managers and sponsorship into the higher-value, judgment-intensive work AI creates.
Who gets those opportunities matters and sponsorship is often the mechanism that decides this. Feedback, sponsorship, stretch work, visibility, and recognition compound over time, but it’s sponsors who convert that accumulation into real access and opportunity. AI is now part of what sponsors influence: whose experimentation gets seen, whose judgment gets tested on high-stakes work, whose name comes up when the next assignment is handed out. The real divide won’t be between employees who use AI and those who don’t. It will be between those whose AI use is being sponsored into opportunity, and those whose is happening in isolation, unseen.
Our EVS data makes the stakes concrete: Employees with a sponsor are more than nine times as likely to have a high-impact network and more than four times as likely to believe they will advance to a senior role. Without deliberate attention, organizations risk building a two-tier workforce: those invited to shape the AI future and those simply expected to adapt to it.
AI can open access to knowledge and capabilities that once required years of specialized experience. But opportunity does not distribute itself- sponsorship does. AI may raise the performance floor. Culture still decides who gets to climb — and sponsors are a key means by which culture shows up.”
4. A Protected Voice and Human Recourse
Knowing when to challenge AI is a skill. Feeling safe enough to do it is a culture issue.
I helped develop Employee Voice Sessions to capture both quantitative patterns in employees’ experiences and the qualitative voices behind them, in essence their experience of corporate culture. Among employees who explained why they had not spoken up at work, 54% cited fear of retaliation and 38% believed speaking up would not make a difference.
Although this data does not track employees’ propensity to speak up specifically about AI, they do show that important barriers to speaking up that exist within workplaces which are inherently defined uneven power dynamics. These barriers are increasingly consequential – and concerning-if employees are expected to identify flawed AI output, question automated recommendations, or admit that they do not know whether a result can be trusted.
Leaders need to further ask whose concerns are most likely to be heard. An employee who questions an AI recommendation may be exercising precisely the judgment the organization says it values. Yet workplace culture and power dynamics shape whose skepticism is considered expertise, and whose as resistance, and who decides it is safer to remain silent.
Employees need protected, penalty-free ways to raise concerns and a clear path to a human decision-maker with the authority and judgment to review them. Without that, the greater risk is not employees pushing back too hard on AI. It is employees who stop pushing back at all. The greatest threat to AI transformation may not be employee resistance. It may be quiet compliance.
The Compact Was Already Changing
These new priorities are emerging within a relationship that was already in flux. Seramount’s 2025 State of the Workforce research found declines in employee engagement, job satisfaction, connection to company mission, and average tenure. At the same time, trust in corporate employers has grown relative to other institutions.
These seemingly opposing trends reflect rising expectations of the employer-employee compact. Employees have seen organizations respond rapidly to profound social and economic disruption, andincreasingly expect businesses to demonstrate the competence and capacity to act.
As employees are being asked to learn, adapt, validate, exercise new forms of judgment, and remain accountable for results, they deserve a new compact: a credible path through change built on candor, meaningful support and opportunity, capable managers and sponsors, and the ability to speak without fear.
Reciprocity within the employee-employer compact is not a soft or new concern. It is- and always has been- an operating requirement, a differentiator for winning organizations. The compact is one that is constantly evolving and is in dire need of clear articulation in this moment. Employees who understand the change, have the authority to exercise judgment, see a future within it, and believe they can question it safely are better positioned to help organizations turn AI adoption into meaningful outcomes.
AI may be rewriting the deal between employers and employees, but technology does not get to set its terms. Leaders do.
