If you've read the article The history of Saas: pass, journey and future, you know that the evolution of this market and how it has become established as the main way to generate increased productivity is enormous. However, despite being used by many big techs, little is said about the use of AI (artificial intelligence) applied to SaaS solutions and how this addition to all tools and platforms has the potential to create amazing innovations that can revolutionize the way we produce, entertain ourselves and even how we eat.
AI and machine learning were extremely difficult to build and apply to smaller companies, restricted only to giants with capital many times in the billions of dollars a year. But this reality is changing, with recent advances such as the availability of an almost infinite amount of data and the processing power of affordable computing, it has become possible for smaller companies to use these new technologies to improve and leverage their tools.
The revolution that these two new technologies are already compared to the great revolutions of humanity such as the discovery of fire or electrical energy. Projected to have a market value of around $733 billion by the year 2027, it shows one of the most favorable scenarios for turning good ideas into radical changes in the lifestyle of the world's population and building fortune.
Analyzing all the data provided by user interactions, such as clicks, screen time on each page, what their likes and interests are, through machine learning in the future it will be possible to customize individually for each of the thousands or even billions of users a different experience in the same mobile app.
Do you have a SaaS product? So you know that updating it is always a requirement so that it always remains with some degree of importance and use by users, but when you always add new features to your product, a good part of the user experience begins to decline due to the accumulation of tools that pollute the screen and can even make pages load slowly.
Imagine now, inserting an AI that learns what features each user uses and creates a personalized interface for him only with the functions he uses the most and leaves hidden functions that the consumer was never interested in opening? Wouldn't that be awesome?
The possibilities for individual customization continue, a SaaS product usually has several plans to accommodate the needs of each user, to acquire and retain as many buyers as possible, by adding AI in this tool, it is possible to offer unique plans for each type different user, taking into account several factors that can influence the amount charged, such as the amount of features, the average time each user uses these functions, and the level of demand for a certain action that can be done.
An important part of the entire SaaS market consists of B2B businesses, focused on providing solutions directly to companies, and this business model is perfect to meet this demand. AI significantly extends the solutions provided by automating various processes and tasks, which previously required a person especially for this for a full salary and can now be replaced by software that perform the same functions with the same efficiency and with high productivity.
An easy-to-understand example is the already established Chatbots, which talk to customers and are able to understand the problem to be solved, a great evolution in the area of customer service and support, powered by the power of machine learning, using the entire experience accessing the data and analyzing it in real time quickly to find the best and most agile solutions while showing affection and respect for the consumer, preventing your buyer from feeling undervalued.
The central challenge for most SaaS companies today is still the feeling created of customer devaluation, a consequence of a reduced team of collaborators while the number of users is gigantic, creating an environment of endless requests and endless waiting time.
Another automated process that still starts the implementation cycle is the automatic problem-solving bots, working as “hunters” for errors and system failures related to each individual account, identifying what needs to be solved before the user himself notices the problem and resolving before it annoys the consumer.
Data hosted in the cloud generates a new problem for society as a whole: security systems become less and less efficient at the scale that it is possible for a user with sufficient experience and intelligence to penetrate the various layers created to prevent intrusions. The opportunity that AI offers here is to anticipate new forms of intrusion that may arise and alert the development team to shield this flaw before someone with unwanted intent finds out first.
Oracle already uses machine learning with artificial intelligence added to its cloud-based security services, the insertion of this feature has facilitated several fully automated threat and failure discoveries in record time!
Bots are also able to quickly identify, through the user's behavioral history, based on data collected over time, when an account has been accessed by someone other than the usual person, generating alerts and warning the account owner to always be on guard. Social platforms such as Facebook and Google already use this feature and many people have benefited from it, managing to prevent losing all their data.
Little explored yet, there is a path full of opportunities for SaaS investment and ventures in conjunction with AI for process management and releases. Government organizations have to deal with hundreds and thousands of cases a day in several different areas of the structure of society, the justice sector of each country has different laws with different terms and "arms", just to define where each process started is destined for, a lot of time and money is spent on professionals just reviewing and targeting all these files.
With machine learning, AI can do this process, greatly reducing the time required by the public sphere of justice, eliminating some barriers such as human failures that occur because of self-interest conflicts and reducing expenses with possible problems that generate indemnities of the state to its citizens.
SaaS Healthcare Companies are at the forefront in implementing AI, using machine learning resources, the results obtained tell administrators what problems are most reported by their customers, facilitate the release of surgeries and treatments that were previously extremely bureaucratic and reduce the wastage of scarce resources that are acquired and stored, generating unnecessary additional expenses.