Two thirds of SaaS AI Projects Could Be Undermined by Bad Data
A new report published today by Panintelligence, a provider of SaaS analytics software, indicates the extent of the AI rush in the SaaS (Software-as-a-Service) industry and warns that up to two-thirds of SaaS companies currently investing in AI could be training their models on poor quality data that undermine accuracy and could lead to unfair or discriminatory outcomes.
Panintelligence’s report – AI value or vanity? How SaaS companies are approaching innovation – was informed by research conducted during July and August 2023. It reveals that three-quarters (76%) of SaaS companies are currently using or testing AI in their businesses, and a further 23% are considering use cases. Just 2% of SaaS companies said they had no plans to use AI.
Two-thirds (67%) of SaaS companies have already added AI capabilities to their products. While machine learning is the most commonly used form – with nearly half (43%) of SaaS companies using it in their products – more than a third (38%) have launched Generative AI capabilities in the last 12 months, and another 15% are testing Generative AI applications ahead of planned launches.
Panintelligence’s report shows that the adoption of AI in SaaS picked up pace in 2023, but raises concerns that many companies need to pay more attention to data quality. Just 28% of SaaS companies – around a third of those developing AI functionality – are working on the kind of data quality initiatives required to support highly robust and accurate AI models.
Panintelligence’s research suggests the AI rush will continue into 2024, with more than half (56%) of SaaS companies planning to progress new AI innovations within the next six months:
28% of SaaS companies are testing predictive analytics that add data-driven functionality to their core products (nearly twice the number (15%) that have already adopted this form of AI).
The proportion of companies using deep learning could also double in 2024, with 17% testing this form of AI. 15% of companies have introduced deep learning to products so far.
Causal AI will also grow in prominence during 2024, driven by a desire to improve the accuracy of AI models and increasing regulatory pressure to show how they work. 6% of SaaS companies are now testing Causal AI for product use and 8% for operational purposes.
“AI hype is now a reality in SaaS: We’ve witnessed an AI rush in 2023, primarily around Generative AI, as the SaaS sector raced to put powerful new capabilities into the hands of hundreds of millions of people and businesses worldwide,” said Zandra Moore, CEO of Panintelligence.
“The SaaS sector is well placed to embrace AI and make it available at scale. However, companies that haven’t prioritised data quality could be training their models on data that compromise prediction accuracy and create unfair or discriminatory outcomes. Neglecting data quality today could cost SaaS companies dearly in regulatory action and retrospective data cleansing and processing fees.”