In the evolving world of enterprise operations, the Software as a Service (SaaS) model has revolutionized how businesses access tools by offering subscriptions. This paved the way for more specific solutions in the form of vertical SaaS. We then saw the emergence of artificial intelligence (AI) and robotic process automation (RPA), providing ways to replicate human actions with virtual bots and eliminate repetitive tasks. Today, the newest player on the scene is agentic AI — a technology taking automation several steps further.
Agentic AI takes the figure of automation beyond simple replication of human behavior. These autonomous AI agents break new ground by doing things like analyzing data, making decisions, executing tasks, and orchestrating workflows all in real time and without needing human prompts. The potential and implications are profound.
For instance, imagine having different AI agents handling separate operations in your business, independently. One agent could be driving new sales while another handles customer service. A third might be working on real-time adjustments in your supply chain. Unlike generative AI models such as ChatGPT, which primarily produce content, agentic AI agents can autonomously scour databases, establish workflows, and complete intricate tasks — they are uniquely equipped to transform business operations.
The adoption of agentic AI in enterprise software is growing rapidly. A Gartner report predicts that only 1% of enterprise software included agentic AI capabilities in 2024, but this figure is expected to rise to 33% by 2028. Notably, a recent survey by Cloudera says 83% of global IT leaders believe AI agents are crucial for staying competitive, and about 60% fear falling behind if they don’t adopt quickly.
In a labor market where job vacancies outnumber available workers, businesses are looking for solutions that improve productivity without straining staff. Salesforce CEO Marc Benioff sees agentic AI as the future, describing it as “a new labor model, new productivity model, and a new economic model”. Imagine the efficiency and potential impact on earnings with an AI agent autonomously updating customer records, identifying new leads, and even clinching minor deals across a team.
As exciting as this new technology is, adopting agentic AI presents its own unique challenges. One of those challenges is finding the right pricing model. The traditional per-seat or subscription-based models may not be applicable here. Instead, pricing may lean towards a per-task or value-based model where agents are hired to deliver specific outcomes.
Adopting agentic AI means delegating decision-making to digital entities and this unavoidably comes with questions of accountability, compliance, and risk. Businesses must establish clear governance structures, but before that, they need to have measures in place to tackle incidents where an AI agent messes up or breaks a rule, be it shutting down or reprogramming rogue agents.
Agentic AI doesn’t aim to replace SaaS but to enhance it instead. Also, it’s becoming increasingly apparent that the future of technology lies in collaboration between AI agents and human workers. To fully benefit, enterprises need to rethink how they evaluate, implement, and interact with business software.
AI agents are more than just another tool — they are digital workforces. The sooner businesses can understand their potential and take appropriate action, the better they’ll be positioned for the future. Agentic AI is not a concept of the future, rather, it’s already reshaping the business landscape today.
Have a look at the original article on Unite.AI for an in-depth analysis.
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