Agentic AI, systems capable of autonomously planning, reasoning, and executing complex tasks, promises to redefine enterprise operations. Yet as 2026 unfolds, a stark chasm separates lofty expectations from operational readiness. A sponsored Harvard Business Review report from AWS reveals organizations grappling with deployment hurdles, while recent surveys underscore surging investments amid persistent failures.

Nine percent of firms have fully deployed agentic AI, with half piloting use cases, but only 6% fully trust these systems for core processes, per Fortune coverage of HBR data. Cybersecurity concerns top barriers at 31%, followed by data quality issues at 23%. “Without high-quality data and a unified governance model, agents can produce unreliable results,” warns Salesforce CIO Dan Shmitt in a CIO analysis.

Gartner’s stark forecast looms large: over 40% of agentic AI projects will be canceled by 2027 due to costs, unclear value, and risk controls, as detailed in Forbes. This prediction echoes across reports, signaling 2026 as a make-or-break year.

Expectations Soar Amid Pilot Proliferation

Enterprise enthusiasm runs high. Dynatrace’s Pulse of Agentic AI 2026 finds 74% anticipating budget increases, prioritizing real-time insights (51%), reliability (50%), and efficiency (50%) for top ROI in IT ops (44%) and cybersecurity (27%), per their press release. PwC predicts 2026 as the year agents deliver value, shifting from demos to industrial-strength deployments in a 2026 AI Business Predictions report.

Industry leaders concur. “2026 will be the year that starts to separate the winning approaches from the failed approaches,” states Asana CIO Saket Srivastava in CIO. Deloitte notes leading firms reimagining operations by treating agents as workers, though 42% lack formal strategies, according to their Insights.

Readiness Gaps Fuel Deployment Failures

Infrastructure lags critically. Only 20% deem tech stacks fully ready, 15% data systems, and 12% governance frameworks, per HBR via Fortune. Half of projects stall at pilots due to legacy integration and compliance, as ITPro notes in X discussions. “The gap isn’t technology. It’s readiness,” posts analyst Michael Fauscette on X.

Organizational redesign proves essential. IBM CIO Matt Lyteson urges targeted outcomes and curiosity in CIO: “Every day, every week, we’re learning something new.” Yet fear of workforce displacement and rigid processes derail efforts, per HBR.

Governance Emerges as Scale Imperative

Trust deficits amplify risks. A Conversation U.S. survey cited on X shows 41% regular use but only 27% proper oversight. “Agentic AI introduces new challenges for safety and security,” warns the World Economic Forum. Dynatrace emphasizes observability for reliability.

Multi-agent orchestration demands “governance agents” for monitoring, per MachineLearningMastery. X threads highlight observability as key to scaling, with 89% exploring but under 10% succeeding.

Sector-Specific Trajectories Take Shape

Retail leads with Microsoft’s agentic solutions for automation, per their announcement. Logistics eyes autonomous robots, as AIBusiness predicts real-time learning. Healthcare anticipates $150 billion savings by 2026 via monitoring, per OneReach.ai.

Public sector trends include agentic AI for citizen services amid modernization mandates, notes NTT DATA. Gartner forecasts 40% of enterprise apps with task-specific agents by year-end.

Pathways to Production Success

Leaders prioritize data readiness and process redesign. “Apply AI to processes, not to people,” advises Deloitte, requiring ROI sign-off. MachineLearningMastery stresses agent-first thinking with metrics.

Forbes outlines leadership shifts: agent managers with HR training for supervision. “Leadership readiness will be the key difference,” per Forbes. X analysts echo: treat agents as long-running systems with policy enforcement.

2026 tests resolve. Leaders bridging readiness gaps via governance, data foundations, and targeted pilots will capture agentic AI’s transformative edge, while others face cancellations and competitive erosion.