The power of artificial intelligence (AI), with its ability to analyze vast amounts of data and assist in decision making, has become a powerful tool for Software-as-a-Service (SaaS) businesses. The SaaS industry, which gives organizations access to a myriad of software applications through subscription models, is taking notice of the steep increase of integrating generative AI into SaaS solutions.
According to a report by Omdia, global AI software revenue is expected to hit $118.6 billion by 2025, an increase from $9.5 billion in 2018. Further, the report indicates that AI will be integrated into nearly every new software product and service by 2025. In addition, IBM found that 35 percent of SaaS businesses are already using AI and another 42 percent plan to use it in the near future.
Client benefits of introducing AI into SaaS businesses
Sadagopan Singam, EVP, Global Head of SaaS and Commercial Applications, Digital Business Services at HCLTech notes that AI can provide a benefit if there are very well-established datasets and SaaS providers have the best form of data available inside enterprises, by the fact that everything is done in the SaaS model.
When an organization has datasets of this scale, the opportunities to run AI algorithms are many times bigger and can provide the best possible types of upsides to enterprises wanting to leverage them in client service, breakthrough analytics, supply chain visibility, demand forecasting, improving the quality of feedback the enterprise can collect and product client behavior.
“They can improve lives and drive much better effects for various parts of an enterprise’s business processes,” says Singam. “And that is where the real opportunity exists. Every conceivable use case that can be thought of to reside inside an enterprise gains more legs and more strength if it is collaborating on a SaaS platform.”
How AI can protect data in the SaaS landscape
AI can be utilized to strengthen the security of SaaS applications through the detection and mitigation of potential cyber threats. AI algorithms can also be used to identify abnormal user behavior and proactively detect and respond to security threats.
“Not only can AI support the business processes and think through the business outcomes differently, it can also look at the environment, look at patterns where enterprises become vulnerable from cyberattacks, data pilferage, data theft or data mishandling,” says Singam.
Singam notes that a well evolved and well-trained machine learning model can predict the areas where things can go wrong or the people around whom things can go wrong, with a reasonable degree of accuracy. The model can then create those early warning signals for enterprises to be prepared to avoid or overwrite those concerns.
Key challenges of AI in SaaS
Utilizing AI for SaaS businesses is not without challenges despite its enormous potential for businesses. There are challenges to be addressed when implementing AI, as well as ethical considerations with the solution.
First, bias in AI algorithms can result in unfair or discriminatory outcomes. For example, SaaS applications for hiring employees or banking applications can lead to discriminatory consequences and harm already marginalized groups.
Second, the large amount of data needed to train AI effectively does raise concerns about privacy and data protection. When collecting and analyzing user data with AI, SaaS companies should be transparent about their data collection and use best practices for ensuring the protection of user data.
“Simplicity is the motherboard of excellence for enterprises. If you’re going to carry the AI algorithms to a greater level beyond what is required, it can provide a complex set of assessments and recommendations that may be variable, confusing or not driving the right optimal outcomes for enterprise,” says Singam.
Intricate and challenging AI algorithms can make it a challenge to hold companies accountable for their actions. By being proactive in addressing these challenges, SaaS companies can ensure AI-powered products are practical and ethical.
Leveraging AI for positive business outcomes
When it comes to using AI by SaaS businesses, HCLTech can help enterprises get the right level of balance between automation and human involvement, as well as getting predictive analytics correct.
“Another area where HCLTech can help enterprises is by being able to create the right blend of AI solutions and the right absorption that they will be able to digest,” says Singam. “Additionally, the right blend of AI solutions set the bar in terms of what to monitor on business outcomes in a way that it’s not an overreach or an under leverage.”
Further, Singam said that HCLTech can consistently benchmark enterprises across various dimensions to make sure that they stay ahead of the game, amongst their peers or across multiple competitive players across industries and geographies.
