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The connection between human expertise and generative AI capabilities is reshaping the testing landscape. It has emerged as a transformative force in quality engineering (QE).     Vikul Gupta (CTO, North America, Qualitest) digs into this topic.     His latest article published on Techstrong.ai talks about how generative AI has shifted the entire base toward new testing solutions.   𝐇𝐞𝐫𝐞 𝐚𝐫𝐞 𝐭𝐡𝐞 𝐤𝐞𝐲 𝐭𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬:   ✅Generative AI can auto-create test scenarios, test cases, features files, and even automation scripts.  ✅Generative AI is not about replacing human workers, but about enhancing their capabilities.   Read the full piece here https://bit.ly/3WdyO46 #GenerativeAI #QualityEngineering #GenAI

The products providing high value to the business without AI are better than the products leveraging AI with low value generated for business ! Product thinking should prioritise business value over heavy engineering. #productengineering #businessvalue #aiadoption

AI at work is not just about automation; it's about 'amplification'. By letting AI handle routine tasks, opportunities can be unearthed for creative problem-solving and innovation. For instance, utilizing AI-driven data insights can not only simplify processes but spark unexpected ideas for product improvement. The coexistence of AI and human ingenuity is proving to be a dynamic force, where AI doesn't replace but augments our capabilities. It's this synergy that drives a new wave of efficiency and imagination in work.

To truly create equitable AI, we need to consider three forces through which it might make society more or less equal: technological forces, supply-side forces, and demand-side forces. #machinelearning #automation #AIBias #ArtificialIntelligence

As organizations develop generative AI strategies and determine how the technology aligns with business goals, potential risks and controls must be part of the equation. Learn more about creating an independent validation and verification strategy in this RSM insight article:

As organizations develop generative AI strategies and determine how the technology aligns with business goals, potential risks and controls must be part of the equation. Learn more about creating an independent validation and verification strategy in this RSM insight article:

“Where data goes in, and intelligence comes out” One of the benchmarks to measure AI intelligence is the Turing Test, although some say this is an outdated way to assess. But the impact of AI is only just beginning – affecting nearly all aspects of our lives. One of the top tech industry companies, Nvidia, says that clusters – ones like those built by Meta or Tesla, as examples – are becoming AI factories, next-generation data centres “where the data comes in and intelligence comes out”. I’d love to hear what your thoughts are and how much AI your business is already including?

As organizations develop generative AI strategies and determine how the technology aligns with business goals, potential risks and controls must be part of the equation. Learn more about creating an independent validation and verification strategy in this RSM insight article:

As organizations develop generative AI strategies and determine how the technology aligns with business goals, potential risks and controls must be part of the equation. Learn more about creating an independent validation and verification strategy in this RSM insight article:

As organizations develop generative AI strategies and determine how the technology aligns with business goals, potential risks and controls must be part of the equation. Learn more about creating an independent validation and verification strategy in this RSM insight article: