Evaluating AI Tools – A Practical Framework for Testers and Leaders
The AI ecosystem is exploding with tools that promise to accelerate delivery, improve quality, and transform the way we work. Yet for many teams, evaluating these tools is overwhelming - flashy demos and marketing claims rarely answer the real questions:
Will this work in our context? Can it scale? Is it sustainable?
This talk presents a structured framework to cut through the hype and make confident, informed decisions. The framework covers six key dimensions:
- capabilities,
- inputs
- outputs
- LLM considerations,
- control
- cost transparency
The framework gives testers and leaders a holistic lens to evaluate any AI solution. Rather than prescribing which tools to use, it provides a mindset and practical checklist to guide your own assessments.
We will look at how these dimensions uncover strengths, risks, and trade-offs: from integration and extensibility, to handling data securely, to balancing automation with human oversight. The framework also highlights how to engage stakeholders, avoid vendor lock-in, and measure long-term value instead of short-term gains.
Attendees will leave with clarity, structure, and confidence - equipped to evaluate AI tools objectively and ensure that the ones they adopt truly deliver meaningful impact.
About Ajay
Ajay Balamurugadas, Head of Customer Success & Strategy at PostQode.AI, has over 19 years of experience in software testing. Renowned for simplifying complex testing environments, he has led testing across product companies, startups, and large enterprises. His strengths include exploratory testing, stakeholder management, and process improvement. A respected mentor, speaker, and author, Ajay actively contributes to initiatives like Weekend Testing and Happy Book Reading, empowering the global testing community through learning and growth. Known for practical insights, he is dedicated to advancing the field of software testing and inspiring professionals toward excellence in quality engineering.
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