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GenAI Is Improving But Still Experiencing Growing Pains

Rob Mason
Applause

Generative Artificial Intelligence (GenAI) is continuing to see massive adoption and expanding use cases, despite some ongoing concerns related to bias and performance. This is clear from the results of Applause's 2024 GenAI Survey, which examined how digital quality professionals use and experience GenAI technology. The survey collected input from more than 6,300 people, including consumers, software developers and QA testers. Here's what we found.

GenAI Is Still Seeing Growth and Improvement

A vast majority of respondents (75%) said that GenAI chatbots are getting better at managing toxic and inaccurate responses, which have long been a major concern for the technology. Additionally:

■ 91% of respondents are using GenAI for research, and 33% do so daily.

■ 81% of respondents have used GenAI chatbots for answering basic search queries in place of traditional search engines, and 32% of respondents do so daily.

■ Of respondents using GenAI for software development and testing, 51% use it for debugging code, 48% use it for test reporting, 46% use it for building test cases, and 42% use it for building applications.

The number of software developers leveraging GenAI, including those who use it on a daily basis for their work, has seen a big uptick from last year, where only 59% said their workplace even allowed for GenAI use. As GenAI has gone more mainstream, it's become more widely accepted and used in the workplace, while the performance of responses has improved.

GenAI Growing Pains

There is still plenty of room for improvement as concerns around GenAI persists. Half (50%) of respondents are still experiencing bias and 38% have seen inaccurate responses. Additionally:

■ Only 19% of users said the GenAI chatbot they used understood their prompt and gave a helpful response every time.

■ 89% of respondents are concerned about providing private information to GenAI chatbots, and 11% said they never would.

Even as performance improves and GenAI is used more widely and frequently, concerns and issues still remain over inaccurate responses, system bias and data privacy.

Additional Key Findings

As more GenAI applications are developed for users, ChatGPT is still leading the field in terms of popularity, with 91% of respondents using it. Meanwhile, 63% of respondents use Gemini, and 55% use Microsoft Copilot. Other chatbots listed ranked as follows:

■ 32% of respondents use Grok

■ 29% of respondents use Pi

■ 24% of respondents use Perplexity

■ 23% of respondents use Claude

■ 21% of respondents use Poe

Additionally, 38% of respondents shared that they use different chatbots for different tasks, and 27% have replaced one GenAI chatbot with another due to performance. Use cases are also expanding for GenAI as 61% of respondents said that multimedia is essential for a large portion of their GenAI usage.

GenAI Remains On the Rise

Despite ongoing concerns, users clearly see the potential in GenAI. Everyone from consumers to developers are using more GenAI apps for more tasks more often. To unlock even greater potential value for users, companies developing GenAI applications must take model training and testing seriously. In particular, they must include real users in testing to identify issues and subtleties in meaning that only humans can gauge.

One specific approach that can help fine-tune and improve GenAI responses is red teaming, a practice with origins in cybersecurity. A so-called red team of testers work to identify biased or inaccurate responses so they know where the model still needs improvement. The more diverse the red team, the better companies can mitigate biases toward or against different communities.

Rob Mason is CTO of Applause

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GenAI Is Improving But Still Experiencing Growing Pains

Rob Mason
Applause

Generative Artificial Intelligence (GenAI) is continuing to see massive adoption and expanding use cases, despite some ongoing concerns related to bias and performance. This is clear from the results of Applause's 2024 GenAI Survey, which examined how digital quality professionals use and experience GenAI technology. The survey collected input from more than 6,300 people, including consumers, software developers and QA testers. Here's what we found.

GenAI Is Still Seeing Growth and Improvement

A vast majority of respondents (75%) said that GenAI chatbots are getting better at managing toxic and inaccurate responses, which have long been a major concern for the technology. Additionally:

■ 91% of respondents are using GenAI for research, and 33% do so daily.

■ 81% of respondents have used GenAI chatbots for answering basic search queries in place of traditional search engines, and 32% of respondents do so daily.

■ Of respondents using GenAI for software development and testing, 51% use it for debugging code, 48% use it for test reporting, 46% use it for building test cases, and 42% use it for building applications.

The number of software developers leveraging GenAI, including those who use it on a daily basis for their work, has seen a big uptick from last year, where only 59% said their workplace even allowed for GenAI use. As GenAI has gone more mainstream, it's become more widely accepted and used in the workplace, while the performance of responses has improved.

GenAI Growing Pains

There is still plenty of room for improvement as concerns around GenAI persists. Half (50%) of respondents are still experiencing bias and 38% have seen inaccurate responses. Additionally:

■ Only 19% of users said the GenAI chatbot they used understood their prompt and gave a helpful response every time.

■ 89% of respondents are concerned about providing private information to GenAI chatbots, and 11% said they never would.

Even as performance improves and GenAI is used more widely and frequently, concerns and issues still remain over inaccurate responses, system bias and data privacy.

Additional Key Findings

As more GenAI applications are developed for users, ChatGPT is still leading the field in terms of popularity, with 91% of respondents using it. Meanwhile, 63% of respondents use Gemini, and 55% use Microsoft Copilot. Other chatbots listed ranked as follows:

■ 32% of respondents use Grok

■ 29% of respondents use Pi

■ 24% of respondents use Perplexity

■ 23% of respondents use Claude

■ 21% of respondents use Poe

Additionally, 38% of respondents shared that they use different chatbots for different tasks, and 27% have replaced one GenAI chatbot with another due to performance. Use cases are also expanding for GenAI as 61% of respondents said that multimedia is essential for a large portion of their GenAI usage.

GenAI Remains On the Rise

Despite ongoing concerns, users clearly see the potential in GenAI. Everyone from consumers to developers are using more GenAI apps for more tasks more often. To unlock even greater potential value for users, companies developing GenAI applications must take model training and testing seriously. In particular, they must include real users in testing to identify issues and subtleties in meaning that only humans can gauge.

One specific approach that can help fine-tune and improve GenAI responses is red teaming, a practice with origins in cybersecurity. A so-called red team of testers work to identify biased or inaccurate responses so they know where the model still needs improvement. The more diverse the red team, the better companies can mitigate biases toward or against different communities.

Rob Mason is CTO of Applause

Hot Topics

The Latest

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

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Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...

In March, New Relic published the State of Observability for Media and Entertainment Report to share insights, data, and analysis into the adoption and business value of observability across the media and entertainment industry. Here are six key takeaways from the report ...

Regardless of their scale, business decisions often take time, effort, and a lot of back-and-forth discussion to reach any sort of actionable conclusion ... Any means of streamlining this process and getting from complex problems to optimal solutions more efficiently and reliably is key. How can organizations optimize their decision-making to save time and reduce excess effort from those involved? ...