Temporary Automation Demand Persistence and Core Capability Investment…

Research Question

What evidence exists that temporary automation workarounds displace investment in core software delivery, and what is the observed persistence rate of those workarounds after the underlying systems capability gap has been closed?

Findings

Executive Summary

Temporary automation workarounds displace core software-delivery demand mainly by giving users a faster local path when central Information Technology delivery or sanctioned tools cannot meet their needs, but the accessible public evidence does not publish a robust displacement percentage.

The same evidence base shows strong persistence risk, because major automation platforms and bot vendors expose explicit controls for inactivity review, orphan detection, dependency-aware deletion, and end-of-life planning.

The reviewed public evidence base does not yield a reliable cross-organisational rate for how often those workarounds survive after the underlying capability gap has actually been closed.

The strongest supported response is therefore to treat temporary automation as a governed bridge, not as a standing substitute, by linking local automation to central review, registry fields, observable retirement triggers, and an explicit path back into core software delivery.

That conclusion does not rule out complementarity, because governed citizen-development programmes can also surface demand and process knowledge that later help core-system teams build the durable fix.

Key Findings

1. Temporary automation displaces core software-delivery demand primarily by giving users a faster local alternative when central Information Technology delivery or sanctioned tools cannot meet workflow needs with adequate speed or fit.
2. Automation adoption often scales ahead of enterprise strategy and Information Technology readiness, which supports the inference that local delivery can expand before the organisation closes the underlying capability gap in software.
3. Post-rollout shadow Artificial Intelligence behaviour shows that sanctioned provision does not reliably eliminate workaround demand when users still perceive external tools as better, easier, or faster than approved enterprise options.
4. Robotic Process Automation and adjacent workaround programmes can create additive operating cost because bot support and upgrade effort persists while the cost of the underlying legacy system remains in place.
5. Major automation platforms have built retirement features around inactivity, ownerlessness, approvals, and dependency checks, which supports the inference that persistence of unused or obsolete workarounds is common enough to require explicit lifecycle controls.
6. The reviewed public evidence base does not yield a reliable cross-organisational persistence rate after the underlying capability gap has been closed, so the requested rate question remains unresolved rather than answered with confidence.
7. The evidence most consistently points to central repositories, code review, role-based access control, separate environments, business-Information Technology collaboration, and leadership-backed programme design as the governance bundle most likely to protect core build capacity.
8. The most defensible operating model is to treat temporary automation as a governed bridge with explicit end-of-life conditions and observable replacement signals, not as a standing substitute for fixing the underlying system.

Assumptions

• Assumption: Low-code apps, RPA bots, and AI-agent workarounds can be analysed together when they serve the same bridging role over an unresolved systems capability gap. Justification: The tooling differs, but the lifecycle logic, persistence risk, and retirement problem recur across all three classes.
• Assumption: Built-in lifecycle controls are a reasonable proxy for the operational significance of workaround persistence even when public retirement-rate datasets are absent. Justification: Platform vendors and bot operators usually expose such controls only for problems that appear repeatedly in live estates.

Analysis

The evidence shows a strong and repeated behavioural mechanism, not a complete financial ledger.

Low-code studies, automation surveys, and shadow Artificial Intelligence reporting all point to the same sequence: users adopt local workarounds when central delivery or approved tools fail to meet immediate workflow needs, and those local successes can reduce the felt urgency of deeper remediation even when the underlying gap remains open.

The persistence side of the question is materially weaker on direct metrics, but strong enough on lifecycle design to reject the idea that workarounds self-retire once better systems exist.

That makes the key trade-off speed versus durable capability.

A credible alternative interpretation is complementarity rather than displacement, because coordinated citizen-development programmes can surface demand, improve process understanding, and feed later core-system change.

The evidence supports that alternative only when local automation remains inside business-Information Technology collaboration and lifecycle controls, which means complementarity is conditional rather than automatic.

If organisations reward local speed without registry, review, and retirement design, temporary automation becomes a competing delivery lane that absorbs attention and leaves the underlying gap intact.

Risks, Gaps, and Uncertainties

• The reviewed public sources used here do not yield a reliable cross-organisational persistence percentage after gap closure, so the rate question remains unresolved.
• The evidence for displacement is behavioural and organisational rather than financial-accounting grade, so the item supports a mechanism and direction of effect but not a precise crowd-out percentage.
• Vendor and platform sources can show lifecycle mechanics clearly, but they underreport estate-wide outcome metrics, so future work should seek longitudinal inventory data from live programmes.

Open Questions

• Which organisations publish longitudinal inventory data that could reveal actual retirement rates for apps, flows, bots, and agents after replacement capabilities go live?
• Which budget-governance mechanisms best prevent temporary automation success from delaying approval for deeper system remediation?
• How different is the persistence pattern between centrally registered enterprise agents and consumer-style shadow Artificial Intelligence use?

sources

• [ ] IEEE Xplore document 10095722 - checked; the page resolved to unrelated publication metadata in this session and was not used for downstream support.
• [ ] Institute for Robotic Process Automation and Artificial Intelligence (AI) - checked; the community homepage contained no specific decommission, persistence, or displacement evidence used downstream.
• [x] Deloitte (2020) Pursuing organisation-wide reimagination - global intelligent automation survey with adoption, strategy, and barrier data.
• [ ] Harvard Business Review May 2016 issue index - replacement for the dead seeded direct article URL; the article text itself was not accessible in this session.
• [x] Binzer et al. (2024) Establishing a Low-Code/No-Code-Enabled Citizen Development Strategy - 24-company study on citizen-development strategy design.
• [x] Viljoen et al. (2024) Governing Citizen Development to Address Low-Code Platform Challenges - 30-interview study on governance, shadow Information Technology (IT), and technical debt risk.
• [x] Binzer et al. (2025) Bridging Business and Information Technology (IT) Through Low-Code/No-Code - 18-firm multi-case study on collaboration mechanisms and coordinated scaling.
• [x] Ajimati et al. (2025) Adoption of low-code and no-code development - systematic literature review of 40 primary studies.
• [x] Digital.gov (2021) 5 tips for implementing citizen development in your RPA program - official governance guidance for citizen-development RPA programmes.
• [x] IBM (2025) Is rising AI adoption creating shadow AI risks? - survey evidence on continued unofficial AI use when employer tools are inadequate.
• [x] IBM (n.d.) Shadow AI - definition and causal framing for unsanctioned AI adoption when approved options are too slow or insufficient.
• [x] Microsoft (2026) Set up inactivity notifications components - inactivity review, approvals, and optional auto-delete process.
• [x] Microsoft (2026) Power Platform inventory - inventory, ownerlessness detection, and fast update surfaces.
• [x] Microsoft (2026) Automatic deletion of Power Platform environments - inactivity windows, disablement, and deletion rules.
• [x] Microsoft (2026) Set up clean-up for orphaned objects - manager-routed reassignment workflow for ownerless resources.
• [x] Microsoft (2026) Reactive governance - real-time governance actions for ownerless and inactive resources.
• [x] UiPath (2026) Deleting Data - administrative delete permissions and dependency-aware deletion block.
• [x] Pega (2021) When is it time to retire your RPA bots? - official lifecycle and end-of-life guidance for bots layered on legacy systems.
• [x] Mitchell (2026) Decommission Trigger Design for Temporary Bridge Agents - prior completed item on machine-verifiable retirement triggers.
• [x] Mitchell (2026) Agent Operational Cost vs Gap Closure Cost - prior completed item on recurring workaround cost versus closing the gap in software.
• [x] Mitchell (2026) Empirical evidence on rollout of organisation-wide low-code and no-code programs - prior completed item on rollout evidence and governance patterns.
• [x] Mitchell (2026) Shadow AI behavioural drivers and governance effectiveness - prior completed item on post-rollout bypass behaviour.
• [x] Mitchell (2026) Systems capability debt, citizen development, and agentic AI risk - prior completed item linking workaround persistence to unresolved capability gaps.