Early RPA projects fell short
Poor scalability and rigidity caused nearly half of early RPA initiatives to miss their objectives.
EY / iOPEXAgentic AI
One orchestrates tasks. The other automates outcomes.
Where your automation strategy stands today determines where it arrives tomorrow.
$1.04THyperautomation enablement software market by 2026
<5% → 40%Enterprise apps with AI agents, 2025 to 2026
$450B+Agentic AI enterprise revenue projected by 2035
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How They Differ
Same goal: automate work. Different architectures, different capabilities.
Dimension
Hyperautomation
Agentic AI
Scope
End-to-end process orchestration across RPA, ML, NLP, and workflow tools
Goal-oriented autonomous outcomes with self-directed planning and execution
Data Handling
Structured + unstructured via dedicated NLP/ML layers
Unstructured data handled natively through LLM reasoning
Execution
Flexible workflows with ML feedback loops, still script-dependent
Autonomous, adaptive, self-improving with real-time context awareness
Decision-Making
Rule-based + ML classification (deterministic core)
Probabilistic and learning-driven with multi-step reasoning
Human Role
Human-in-the-loop: humans execute alongside bots
Human-on-the-loop: oversight and exception management only
Learning
Requires manual retraining and reconfiguration
Continuous, real-time learning from environment feedback
Failure Mode
Stops at unseen input; bots break when UIs change
Recovers from partial failure through reasoning and tool fallback
The Agentic AI Trajectory
Key milestones from Gartner research, plotted on a timeline.
- 2025
Less than 5% of enterprise apps include task-specific AI agents. Agentic AI generates roughly 2% of enterprise software revenue.
Gartner, Aug 2025 - 2026
40% of enterprise apps will feature task-specific AI agents. Hyperautomation enablement software reaches roughly $1.04T.
Gartner, Aug 2025 - 2027
One-third of agentic AI implementations will combine agents with different skills for complex tasks.
40%+ of agentic AI projects cancelled due to costs, unclear value, or risk gaps.
Gartner, Jun 2025 - 2028
15% of daily work decisions made autonomously by agentic AI (up from 0% in 2024). 60% of brands use agentic AI for 1:1 customer interactions.
Gartner, Jan 2026 - 2029
80% of common customer service issues resolved autonomously without human intervention.
Gartner, Mar 2025 - 2035
30% of enterprise app software revenue driven by agentic AI, surpassing $450 billion.
Gartner
The RPA & Hyperautomation Pain Points
The hidden costs and failure modes driving organisations toward agentic architectures.
Spent on maintenance per $1 on licensing
For every dollar spent on RPA licensing, $3.41 to $4.00 goes to consulting and maintenance.
Blueprint SystemsAnnual maintenance drag
RPA maintenance consumes 25-35% of the initial investment every year. Bots break when underlying applications change.
Industry AnalysisStill in industrial-age operating models
Only 1% of organisations operate as decentralised networks ready for autonomous AI.
Gartner / AccioAnnual maintenance per bot
Total per-bot costs including setup and ongoing maintenance reach $30K+ annually at enterprise scale.
SmartDev / SCIMUSFragmentation is the real problem
RPA bots and AI models run in isolation. No system knows the other exists, compounding operational risk.
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What Early Adopters Are Seeing
Real ROI data from organisations deploying agentic AI in production.
Average ROI on AI agent investments
Industry AverageAchieve returns within year one
OneReachOperational cost reductions across sectors
Cross-IndustryError reduction in repetitive processes
Cross-IndustryAnnual gross profit boost at a Forbes-recognised retailer from agentic sales agents
Forbes / OneReachReduction in legal research hours using AI agents at BakerHostetler
BakerHostetlerFaster complex case resolution at ServiceNow, generating $325M annualised value
ServiceNowThe Cancellation Warning
Gartner predicts 40%+ of agentic AI projects will be cancelled by end of 2027. Here is why.
Four Foundations for a Successful Transition
Hyperautomation is the foundation for agentic AI. These four pillars determine readiness.
Process Understanding
Deep workflow mapping through process mining drives agent design alignment. Understand what you automate before agents can reason about it.
Data Readiness
Resolve silos and ensure quality to create the "data fabric" agents require. Fragmented data produces fragmented agent behaviour.
Scalability & Orchestration
Existing infrastructure enables multi-agent collaboration. The orchestration backbone built for hyperautomation carries forward.
Mindset Shift
Move from "human-in-the-loop" to "human-on-the-loop." Automation-first thinking prepares the organisation for agent autonomy.
Who Is Moving Already
Adoption momentum from C-suite surveys and analyst reports.
of leaders say scaling AI agents in the next 12 months is a competitive advantage
Capgeminiof CIOs consider agent-based AI a strategic priority
Futurum Groupof senior executives plan to increase AI budgets in the next 12 months
PwCof enterprises using GenAI will deploy autonomous agents by 2027 (up from 25%)
Deloitteof healthcare organisations already use AI agents
KPMGof organisations believe "AI agents are the new enterprise apps"
IDCInfographic SourcesShow referencesHide references
We reviewed the sources below to support the statistics, benchmarks, and frameworks referenced in this infographic.
Headline adoption stat: enterprise apps with AI agents growing from less than 5% to 40% in one year
Cancellation warning: escalating costs, unclear business value, inadequate risk controls
Timeline 2028 milestone: brand adoption of agentic AI for customer interactions
Timeline 2029 milestone: autonomous customer service resolution
Supply chain AI market projection
Hyperautomation enablement software market reaching roughly $1.04T by 2026
15% of daily work decisions made autonomously by 2028
Four-foundation transition framework: process understanding, data readiness, orchestration, mindset shift
ROI benchmarks (171% average), case studies ($77M retail, 60% legal, 52% ServiceNow), adoption survey data
Comparison matrix dimensions, 30-50% RPA project shortfall stat, evolution framework
$3.41 maintenance cost per $1 licensing stat
Failure reasons: unclear ROI, governance risks, workflow integration, agent washing
89% of organisations still in industrial-age operating models
$10K-$100K annual maintenance per bot, 25-35% annual maintenance drag
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