AI agents are reshaping how deals get done and redefining the skills people need in an agent-powered workplace.
Sydney Scott
Editorial Strategist, AI
Workday
A car buyer in Philadelphia recently pressed a single button on a website and went about her day. While she worked, ate lunch, and picked up the kids from soccer practice, an AI agent negotiated with multiple car dealerships on her behalf.
It created a private phone number, handled every message, pushed back on overpriced quotes, and ultimately secured more than $1,500 in savings—without the customer taking a single call. The deal was done before dinner.
At the same time, across the Atlantic, a professional soccer player weighing a contract offer from a London club skipped hiring an agent altogether. Instead, he fed the offer into ChatGPT, explained his situation, and asked the AI to help him shape a counterproposal. He used the tool to refine his message, understand his leverage, and lock down terms that worked for him. He later described the system as the “best agent” he’d ever had—an extraordinary statement for a sport built on human negotiation.
Both stories sound like novelties, but they aren’t. They’re windows into a much larger shift already underway inside organizations around the world.
Negotiation—detail-heavy work that once required people sitting across a table—is being reshaped by AI systems that can hold conversations, analyze context, and act on behalf of employees and enterprises. And this shift is changing not only how deals are done, but how people work, learn, and lead.
When agents can handle the heavy lifting of negotiation, the real value shifts. Leadership becomes about defining intent, not drafting every message.
—Jerry Ting, VP, Head of Agentic AI and Evisort, Workday
Report
To understand what’s actually happening, it helps to see AI agents not as simple chatbots, but as highly capable digital co-pilots.
Unlike traditional software, which waits for commands, these agents observe a situation, decide on the next move, then carry out actions within rules set by humans. This autonomy is already reshaping core business functions.
Procurement teams are starting to use agents to scan massive contract histories and surface savings opportunities that would otherwise stay hidden simply because of their volume and complexity. By handling thousands of supplier agreements in parallel, these agents help teams proactively identify and renegotiate areas that traditionally receive less focus, unlocking meaningful financial gains.
In the front office, sales teams use agents to accelerate the early, transactional negotiation stages of a deal. Instead of writing the first draft of every message or digging through CRM systems for context, sales reps allow the agent to handle the heavy lift of initial price structuring and proposal refinement.
Even legal teams, often wary of automation, are finding immense value in agentic negotiation and contract intelligence. Instead of pushing contracts through slow, linear review processes, legal teams let AI agents surface risky clauses, propose alternatives, and flag compliance issues before a human ever touches the document. Work that once sat idle in inboxes now moves with the speed of software—all without removing the lawyer’s final say.
This shift is most transformative when facing challenges of massive scale. For example, when NetApp had to review approximately 90,000 contracts following a headquarters relocation from the Netherlands to Ireland, a traditional manual review process was out of the question. By deploying advanced contract AI, the company was able to streamline the process, ultimately leading to massive cost savings.
The rise of agents isn’t only changing enterprise workflows. It is changing how individuals advocate for themselves.
Workers now use AI agents the way athletes use training partners. They run practice negotiations, test out difficult conversations, and receive instant feedback on tone, phrasing, and strategy. Instead of waiting for a manager to offer coaching, they can rehearse anytime, with an agent that adjusts its responses in real time. Some organizations are already offering this through formal training programs, giving every employee access to a personal digital practice partner that can help them grow faster than traditional workshops ever could.
This accessibility doesn't just improve individual skills; it drives a cultural shift toward self-advocacy and ownership. By providing a continuous, low-stakes practice partner, organizations establish a new norm where learning and skill refinement are daily activities, not periodic events. This empowers every employee to proactively own their development, reducing reliance on managerial coaching and fostering a workforce confident in its ability to successfully navigate difficult conversations.
Employees are beginning to lean on AI agents to handle the everyday coordination tasks that quietly consume so much time—approving schedule changes, managing shift swaps, clarifying HR requests, and routing small operational decisions that would otherwise require a string of emails or chats. Workforce-management platforms already automate much of this routine back-and-forth, giving employees and managers quick, rule-aligned answers without the usual administrative cycles.
By offloading these low-stakes interactions, teams reclaim attention for more meaningful work and avoid the constant micro-tasks that fragment focus throughout the week.
More fundamentally, as agents take on more of the transactional back-and-forth, employees are spending more time on the human parts of negotiation: reading the situation, understanding motivations, building trust, and making judgment calls.
Soft skills once considered “nice to have” are becoming core differentiators. Emotional intelligence, context reading, and relationship-building are emerging as the new premium capabilities—the parts of negotiation AI cannot replicate.
The most important part of agentic negotiation is how the system reasons. When you can see why an agent made a decision, you can trust it to act at scale.
—Amine Anoun, VP of Machine Learning, Workday
The growing presence of agents is subtly rewriting job descriptions. The classic negotiator—someone who drafts every message, crunches every number, and manages every conversation—is evolving into a supervisor, strategist, and curator of AI-driven work. Employees no longer need to perform every step themselves. Their value now lies in setting clear goals for agents, reviewing their outputs, and guiding them toward the right blend of firmness, fairness, and creativity.
This shift is reshaping leadership expectations as well. Managing teams in an agentic workplace will require new forms of oversight, clearer delegation, and a deeper understanding of how agentic systems reach their conclusions. Leaders will need to articulate rules around authority, ethical limits, red lines, and escalation points—because an AI agent can move fast, but it can also make commitments that carry legal or financial consequences if not properly guided.
“When agents can handle the heavy lifting of negotiation, the real value shifts,” said Jerry Ting, VP, head of agentic AI and Evisort. “Leadership becomes about defining intent, not drafting every message.”
Put simply, leaders shift from doing the negotiation themselves to setting the rules and knowing when to step in.
Organizations that mature quickly in this direction will gain a significant structural advantage. They will negotiate faster, operate more consistently, and build knowledge systems that strengthen over time. Those that hesitate may find themselves operating at a structural speed disadvantage, especially in markets where deal velocity translates directly into revenue.
The companies that thrive in this new environment will be the ones that embrace the speed and scale of AI agents while doubling down on responsible governance and human skill development.
As with any leap in automation, agents introduce meaningful risks. The first is bias. An agent trained on outdated or skewed data can reproduce unfair patterns at scale, creating uneven pricing, discriminatory offers, or ethical issues that damage trust. Bias that once affected dozens of decisions could now affect thousands. The only effective safeguard is continuous testing, transparent training data, and an active governance program that treats fairness as a business requirement rather than a compliance checkbox.
A second risk is overreach. AI agents, if not given strict negotiation boundaries, can agree to terms beyond what an organization intends. A single unauthorized commitment—whether on pricing, delivery timelines, or legal language—can cascade into costly disputes. This is why leading organizations are adopting human-in-the-loop checkpoints, where high-risk decisions require a human signoff, no matter how fast the agent moves.
Then there is the issue of trust. Negotiation is built on transparency and accountability. When a customer or supplier believes decisions are being made inside a black box, trust erodes quickly. Companies are responding by building trails, clear records showing how an agent reached a conclusion and what data it relied on. These trails not only support accountability; they also become strategic assets in building long-term relationships.
“The most important part of agentic negotiation is how the system reasons,” said Amine Anoun, VP of machine learning, Workday. “When you can see why an agent made a decision, you can trust it to act at scale.”
Finally, there’s the reputational risk. When an agent handles a negotiation poorly or delivers an offer that feels out of line, customers won’t blame the system. They’ll blame the company. Any misstep made by an agent reads as a misstep made by the brand, which makes oversight and clear behavioral guidelines essential.
At the end of the day, the organizations that win won’t be the ones that deploy agents the fastest, but the ones that deploy them with the clearest boundaries.
We are entering a moment where negotiation—once one of the most human parts of business—is becoming a shared task between people and autonomous systems. The partnership is not about replacement. It’s about leverage. AI agents handle the repetition, data load, and constant back-and-forth. Humans handle the nuance, empathy, and final judgment.
The companies that thrive in this new environment will be the ones that embrace the speed and scale of AI agents while doubling down on responsible governance and human skill development. They will treat negotiation not just as a transaction, but as a hybrid practice—part machine-driven, part deeply human.
And for everyday workers—whether they’re buying a car, negotiating a contract, or preparing for a tough conversation—the presence of a smart, tireless negotiation partner may soon feel as normal as having email on their phone.
Report
62% of leaders welcome AI, but only 55% of employees feel the same way. Closing this AI trust gap and ensuring that your organization is prepared for widespread AI implementation will prove decisive to your company's future success.