The numbers tell a compelling story: 79% of organizations have already adopted AI agents in some capacity, and 88% plan to increase their AI budgets in the next 12 months specifically because of agentic AI’s potential, according to PwC’s AI Agent Survey.
Yet here’s where things get interesting — and a bit sobering. While enthusiasm is high, some analysts expect many agentic AI projects will be canceled by the end of 2027 due to escalating costs, unclear business value, or inadequate risk controls.
So what separates the organizations that will thrive with AI agents from those destined to join the cancellation statistics?
After working with organizations navigating this transformation, several patterns have emerged. Success isn’t about having the most sophisticated AI models — it’s about how thoughtfully you approach deployment, governance, and the fundamental redesign of how work gets done.
Here are seven essential practices that can help you beat the odds and unlock real value from your agent investments.
Learn how agentic AI can fast-track activities, such as hiring, by automating multiple tasks.
1. Select the right leaders
Before you deploy a single agent, ask yourself a crucial question: Do your leaders genuinely value unique human capabilities alongside agentic AI, or do they see agents as a path to replacement rather than augmentation?
This isn’t just a philosophical exercise — your leadership philosophy shapes your entire agent deployment strategy. The most successful organizations champion the complementary strength of humans and agents, demonstrate cultural fit with appreciation for diverse talent and unique skills, and maintain the ability to reimagine roles rather than eliminate them. Importantly, they also cultivate a growth mindset about organizational transformation.
According to McKinsey’s latest research, AI high performers are nearly three times more likely than other firms to fundamentally redesign workflows when deploying AI. That kind of transformation requires leaders who see beyond efficiency gains to envision entirely new ways of working whilst protecting uniquely human capabilities.
2. Commit to major process overhaul
Here’s a hard truth: if you’re simply refining existing processes with agents, you’re leaving exponential value on the table. The organizations achieving 10-25% EBITDA gains aren’t automating their current workflows — they’re redesigning them from scratch.
Think exponential gains, not incremental improvements. This means questioning the entire workflow, not just adding automation; looking for opportunities to eliminate non-value steps; rethinking sequences, dependencies, and decision points; and aiming for 10x capability, not 10% efficiency.
MIT Sloan Management Review found that 66% of organizations further along in agentic AI adoption expect changes in how they’re organized and how jobs are defined, compared to just 42% of organizations just beginning adoption.
This kind of transformation requires cross-functional process redesign teams — people who can challenge assumptions and rebuild workflows with fresh eyes.
3. Secure board and CEO ownership
Perhaps the most critical success factor? Frame your agent initiative as business transformation, not a technology project. This distinction matters enormously.
Successful deployment requires board-level governance and strategic oversight of agent deployment, with CEO/COO actively leading the transformation narrative. The initiative must be integrated into business strategy, not relegated to the IT roadmap, with resource allocation that reflects its strategic importance and regular board reporting on outcomes and risks.
PwC’s recent AI Agent survey revealed that while 79% of organizations are adopting AI agents, 68% report that half or fewer of their employees actually interact with agents in their everyday work. This gap between deployment and adoption often stems from treating agents as a technology project rather than a strategic transformation with C-suite ownership.
4. Foster an experimentation culture
Build organizational capability for safe learning and testing, but do so within clear boundaries that maintain psychological safety to innovate.
The best-performing organizations establish permission to run controlled experiments and fail safely, create rapid iteration and feedback loops on agent behavior, assemble cross-functional teams exploring agent use cases, define clear governance for what’s testable versus production-only, and ensure learning is shared broadly across the organization.
This balanced approach matters because the technology is evolving rapidly. Analysts expect nearly a third of organizations to be using agentic AI by 2028. Organizations need the muscle to experiment and adapt continuously.
Related content: Learn more about agentic AI in HR in our ultimate guide.
5. Strike a smart governance balance
Here’s the paradox: you need rigorous oversight for risk and safety, while still protecting efficiency and innovation. Over-governance stifles progress; under-governance creates unacceptable risk.
Smart governance means establishing clear policies on agent decision authority and escalation paths, implementing risk frameworks that distinguish low-risk from high-stakes decisions, building audit and compliance mechanisms without bureaucracy, fast-tracking approval for low-risk agent implementations, and maintaining continuous monitoring with feedback loops to adjust agent behavior and targets.
According to McKinsey, only 39% of organizations report EBIT impact at the enterprise level from AI, despite widespread adoption. This value gap often stems from governance approaches that either strangle innovation or fail to ensure agents are actually delivering business outcomes.
6. Develop new metrics and feedback systems
Traditional KPIs weren’t designed for agent-led work, and that creates an accountability gap. When you’re less directly involved, it’s harder to measure what matters.
You need new KPIs and feedback systems specifically designed for agent-led work:
- Move beyond task completion to quality and outcome metrics.
- Build feedback loops from end users and affected stakeholders.
- Track agent decision patterns and drift over time.
- Measure business impact, not just operational efficiency.
- Establish regular review cycles to adjust agent behavior and targets.
IBM research found that 76% of leaders indicate that focusing on complex, high-leverage problems with agentic AI is more likely to yield competitive advantage than simply automating existing tasks faster.
But you can’t capture that advantage if you’re still measuring success with yesterday’s metrics.
7. Rethink learning and mobility
Agents create a rare opportunity to redesign career paths and development. How does your workforce grow alongside agent capability?
Forward-thinking organizations are shifting their skills focus toward agent management, oversight, and judgment. Career paths are evolving from task execution to strategy and judgment.
They’re creating internal mobility into agent-adjacent and AI-enabled roles, implementing continuous upskilling programs for an agent-ready workforce, and building education partnerships to develop the future talent pipeline.
This isn’t just about preparing your current workforce — it’s about positioning your organization to attract the talent that will drive competitive advantage in an agent-augmented future.
The transformation imperative
The evidence is clear: organizations are moving quickly to adopt AI agents, but adoption alone won’t deliver transformation. PwC found that 73% of survey respondents agree that how they use AI agents will give them a significant competitive advantage in the coming year.
The question is whether you’ll be among the organizations that capture that advantage — or among those whose projects get canceled.
The difference comes down to these seven practices. Select leaders who value human-agent collaboration. Redesign processes from the ground up. Secure C-suite ownership. Build an experimentation culture. Balance governance with innovation. Create new metrics for new ways of working. And reimagine how your people grow alongside these new capabilities.
The race isn’t just about who deploys agents first — it’s about who deploys them most thoughtfully. Those who do will find themselves not just more efficient, but fundamentally transformed in how they create value, serve customers, and compete in the marketplace.
Experience agentic AI in action — see how AI Interviewer can help your business join those already scaling agentic AI, not just experimenting with it.
Teresa Wykes is Senior Director of Talent-centered Transformation at Eightfold.