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IDC PeerScape: Practices for Leveraging AI, ML, and Agentic Testing in Adoption Strategies for AI Assurance and Business Optimization

Publisher IDC
Published Jan 22, 2026
Length 9 Pages
SKU # IDC20786993

Description

This IDC PeerScape describes practices for speeding adoption of AI and agentic testing to address five challenges — cultural resistance and role redefinition, lack of standards and tool sprawl blockage, technical debt and "build it" bias issues, security and compliance AI barriers, and evolving AI maturity and adaptive processes — resulting from conversations with several peer organizations including a global bank, a global software and industrial simulation provider, and an international services and software company. "One of the biggest barriers to software deployments and a core priority for organizations continues to be software quality since the high costs of software failure are prohibitive," said Melinda Ballou, research director, AI Assurance, ALM, Quality and Portfolio Strategies at IDC. "Increasing complexity and dynamically changing AI and agent technology demand responses that are thoughtful, astute, and rapid. This IDC PeerScape is the first in a series to help create an AI transition path for organizations by leveraging the experience of peer organizations. As we move into 2026, collaboration across enterprises to benefit from common experiences and AI strategies is more vital than ever."

Table of Contents

9 Pages

IDC PeerScape Figure

Executive Summary

Peer Insights

Practice 1: Establish COE, Education, and Hands-On Workshops Underscoring AI Benefits and Reframe Roles to Position AI as an Enabler With Human Oversight, Rather Than a Threat

Challenge

Examples

Guidance

Practice 2: Combine Tools for Test Data Access, Management, and Execution; Build Shared Libraries and Metrics; Focus on API Tests; and Need Traceability Across Requirements, Changes, and Test Inventory

Challenge

Examples

Guidance

Practice 3: Evaluate TCO; Choose Vendors for Partnering Well, Excellent Road Maps, Support, and Governance; and Experiment in Sandboxes Under COE Oversight

Challenge

Examples

Guidance

Practice 4: Engage Security/Legal Teams Early; Define Cogent COE AI Policies and Processes and Multistage Approvals; and Choose Auditable, Compliant Platforms Standards

Challenge

Examples

Guidance

Practice 5: Target Initial Use Cases; Leverage Third-Party Support to Transition; and Harness Engaged, Knowledgeable Agile and AI-Informed Staff In-House for AI Assurance

Challenge

Examples

Guidance

Next Steps

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