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Business is on a never-ending quest to boost efficiency, cut costs, and increase productivity. Some of the earliest known businesses -- ancient Mesopotamian traders -- inspired the invention of writing. (Record keeping -- now that's a competitive advantage!)
Similar needs have existed in every economic period. The big difference now is that AI technology can boost these efficiencies in new and exponentially profitable ways. Agentic AI is at the core of this efficiency boost.
According to Dan Priest, chief AI officer at PwC US, "agentic AI refers to AI systems that can autonomously perceive, decide, and act within a defined scope to achieve goals, capable of collaborating with humans, systems, or other agents." (PwC, a.k.a. PricewaterhouseCoopers, is one of the "Big Four" -- the world's four largest professional services firms.)
Also: 5 ways to be a great AI agent manager, according to business leaders
Agentic AI systems are different from the previous generation of algorithmic business management systems we've been using for the past few decades. Agentic AI can understand context, respond to changing situations without running from a script, and work toward defined goals autonomously.
Compared to traditional automation (and some human managers), agentic AI systems can be flexible, handle ambiguity, and make informed decisions at the speed of business operations. Agentic AI, Priest says, "helps organizations operate with greater speed, intelligence, and scalability, fundamentally transforming how work gets done and decisions are made."
Common barriers to AI integration
However, you can't simple wave a magic wand and get enterprise-wide agentic AI that works perfectly. There are many challenges, including the existing technical debt deeply entrenched with legacy tools and processes, aversion to change, regulatory challenges, and lack of understanding and technical AI skills within the organization.
"Common barriers to achieving integrated agent systems include fragmented data environments, lack of interoperability between tools, and siloed organizational structures," says PwC's AI expert.
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