By delivering tools online through subscription models, software as a service (SaaS) changes how an enterprise operates. Still, for some, functionality is limited, so vertical SaaS adds industry-specific features. Then there are advancements like artificial intelligence (AI) and robotic process automation (RPA), which will use virtual robots to replicate human behavior and eliminate rote tasks.
Now, Enterprise Software is entering a new era with proxy AI, powered by autonomous agents that not only mimic humans, they analyze data, make decisions, perform tasks and perform self-pruning workflows in real time. Proxy AI goes far beyond traditional SaaS or RPA. It is software that acts as a workforce in the digital realm, integrating in the technology stack and producing measurable business outcomes. Individual AI agents drawn through large language models can perform inference at a high level, making it possible.
Without human prompts, each agent can also be assigned to their own goals. One can focus on new sales, another can facilitate customer service, and the third manages real-time changes in production-the possibilities seem endless. And, unlike generative AI models like chatgpt, not only do agents re-spray and spit out content, but they even browse the database and build their own workflows to complete a given task.
According to Gartner, about one-third of software applications in businesses will sell less than one percent between 2024 and 2024. The findings announced by Clodra in mid-April – based on polls from 1,484 global IT leaders – 83% of AI is crucial to AI leaders.
Additionally, a tough 96% said they plan to develop deployments over the next 12 months, with half adding that these could be massive rollouts across the organization.
Bridging the gap
Salesforce CEO Marc Benioff called agent AI “a new workforce model, a new productivity model and a new economic model”. The number of popular participation in the U.S. labor force remains below pre-pandemic figures, and there are far more jobs today than unemployed candidates. The main goal of AI is to eliminate rote tasks, but at the same time, employees need to be able to generate more. With this in mind, digital labor should be used to increase labor and increase productivity, increase efficiency and enable organizations to compete.
Agent AI can bridge the gap between people and products in a variety of ways. For example, a sales executive may use a customer relationship management (CRM) solution to control a large number of existing and prospects and generate sales. AI brokers can communicate with this foundation, identify opportunities, make records up to date, and even make smaller sales. If you work for your team every day and all day, saving time on manual labor, the possibility of selling will have a significant impact.
The pain of this technology is growing, especially in pricing agent AI. The “Per Seating” model may be changed to the “Per Task” being performed. Agent AI can also turn more value-based models into value-based models that have “used” to solve functions and produce guaranteed results for AI agents. Salesforce reported Agentforce’s Record product deals just a few months ago, Agenforce is its platform for building, customizing and deploying autonomous agents, but recently it changed its pricing model to a consumer-based agent that directly links costs to results.
Responsibility and Accountability
Although proxy AI is needed to solve many problems, it is certain that the way to choose a software vendor needs to be changed. Traditional evaluations focus primarily on feature sets, but with Agesic AI, businesses must weigh supplier reliability and responsibility history and whether they can align with the company’s specific goals.
Accountability should be the focus of decision makers because they no longer just buy software. Instead, they give digital intelligence approval to do things on their behalf, which can create legal and compliance issues. That is, businesses need to consider their responsibilities, explore risks in depth, tend to be auditable, and keep regulatory guidelines at the forefront. Additionally, organizations must determine who is actually responsible if the AI agent rogues, and the programs that include or close it.
Steps to be taken
With proxy AI, many of us will see significant changes in the way we do business. Here are some actions you can take right away to keep the process going.
For beginners, recheck your tech stack with the emphasis on the rule-based features that AI agents may eliminate. Consider which software may have interoperability issues or require new application programming interfaces. Be sure to avoid siloed decisions – Agent AI can affect many aspects of the business, thus including leaders in law, IT and operations. It is also crucial to develop employee policies.
You have to understand the ability of AI agents to work, and the complexity it can eliminate. This means you also need to rethink the software cost model and the ROI they can provide. It’s about quantity and efficiency, so seating, license and subscription costs are no longer the standard to be used.
Proxy AI will greatly affect SaaS, but will not completely replace it. We will see a technology collaboration guided by the goal of increasing the workforce. Nevertheless, businesses fundamentally need to change the way they work with software. Proxy AI is here, the faster you can understand what it can do and put it into practice, the more you can consolidate your future position and success.
