PERSPECTIVES & RESEARCH
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Rethinking how technology quality is governed, assured and delivered through experience and informed analysis.
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Latest Thinking
Articles from TAL
Blind Spots, Rationality and Balance
The modern technology delivery portfolio engenders high-velocity and complex endeavours to meet what are often quite broad and even ambiguous requirements — an environment within which decision-making is rarely...
Quality Assurance vs. Testing – Part 5
Challenges in Delivering IT Quality Irrespective of how advanced technology becomes, enterprises and their IT departments face ever-present staple challenges in delivering high-quality technology solutions to their...
Who’s Watching the Watchers?
The Case for Quality as a Strategic Guide It is common for executive-level management to consider technology testing and associated QA as intrinsic components of delivery rather than distinct, value-generating...
AI and the Future of Technology Testing
AI’s Impact: Elevating the Role of Today’s Testers AI’s entry into the testing domain feels like it was always meant to be. The latent connection between AI and testing has always existed, rooted in the challenges...
Quality Assurance vs. Testing – Part 4
To fully understand Testing as part of Quality Control (QC), we must move beyond seeing it as merely a tool for bug detection. Instead, Testing should be viewed as a critical component of QC that involves...
Predictability Lost
The Importance of Backlog Management in Agile Agile methodologies promise flexibility and speed. The ‘Backlog’ enables these benefits, serving as a living, prioritised list of tasks, features, defect fixes, and...
Publications
Research, Guidance & Reference
Downloadable, more specialised treatments of TAL’s thinking and capabilities.
Service specification · v1.3
Expertise Catalogue
TAL's service fulfilment specification for technology and AI quality, risk and assurance management — the expertise, practices and deliverables behind iT-TRAC® and AISTA® — set out for evaluation and procurement. Version 1.3 adds AI assurance and management systems.
Guest paper
Proving AI Compliance
Firms are giving AI agents real credentials and real access, but existing controls cannot show whether any given action was lawful. This paper sets out how deterministic, rule-based checking produces the evidence a regulator expects — at the moment each interaction happens, rather than after the fact.
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