Eliza wants to know how you feel.
Before we go any further, please know that Eliza, or ELIZA, wasn’t a human being, but an early conversational artificial intelligence agent developed in 1966 by the computer science Joseph Weizenbaum.
Eliza the agent could act like a therapist by reflecting users’ statements, though it had no real understanding of language. When a user stated, “I feel sad today,” Eliza asked, “Why do you feel sad today?”
We’ve come a long way since Eliza made those simple inquiries.
Today, AI agents can control your smart-home devices, or help you find products and compare prices, monitor your health metrics, remind you to take your medications and suggest lifestyle changes based on your personal health data.
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Big Tech Has Gone Big on AI
Some of the big players using agentic AI include software giant Microsoft (MSFT), Alphabet’s (GOOGL) search engine kingpin Google, and Big Blue itself, IBM (IBM), are integrating it to automate tasks, enhance customer experiences and improve decision-making.
Google Cloud recently launched Gemini Enterprise, a unified agentic AI platform positioned as a single front door for artificial intelligence in the workplace.
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“Gemini Enterprise is designed on the premise that true business transformation in the era of AI must go beyond simple chatbots,” said Sundar Pichai, CEO of Alphabet.
“You need a comprehensive and integrated platform that brings all your company’s data, tools, and people together in one secure place.”
A recent report by McKinsey said agentic AI “promises to radically remake the entire shopping experience.”
“Agentic commerce — shopping powered by AI agents acting on our behalf — represents a seismic shift in the marketplace,” the firm said.
“It moves us toward a world in which AI anticipates consumer needs, navigates shopping options, negotiates deals, and executes transactions, all in alignment with human intent yet acting independently via multistep chains of actions enabled by reasoning models.”
There’s a lot of money involved here.
By 2030, McKinsey said, the US business-to-consumer retail market alone could see as much as $1 trillion in revenue from agentic commerce, with global projections reaching as high as $3 trillion to $5 trillion.
“This isn’t just an evolution of e-commerce,” McKinsey said. “It’s a rethinking of shopping itself, in which the boundaries between platforms, services and experiences give way to an integrated intent-driven flow, through highly personalized consumer journeys that deliver a fast, frictionless outcome.”
The research and consulting firm said that all kinds of businesses — brands, retailers, marketplaces, logistics and commerce service providers, and payments players — “will need to adapt to the new paradigm and successfully navigate the challenges of trust, risk, and innovation.”
“Agentic commerce requires a fundamental rethinking of how value is created, captured and delivered,” the McKinsey report said. “Companies that adapt quickly will not only meet evolving consumer expectations but also redefine their industries.”
JPMorgan CEO: AI Is Bank’s Biggest Issue
“Those that hesitate risk losing ground as AI agents become the new gatekeepers of commerce.”
JPMorgan (JPM) CEO Jamie Dimon said AI might be the biggest issue with which the bank is grappling, according to Bloomberg.
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“We are completely convinced [that] the consequences will be extraordinary and possibly as transformational as some of the major technological inventions of the past several hundred years,” Dimon said in JPM’s annual letter to holders. “Think the printing press, the steam engine, electricity, computing and the internet, among others.”
Venture capital investment in agentic AI between fourth-quarter 2024 and first-quarter 2025 more than tripled (up 265%), according to Pitchbook data.
Gartner: There’s a Risk in AI Efforts
However, the research and advisory firm Gartner said that by the end of 2027, more than 40% of agentic AI projects will be canceled.
“The main reasons include escalating costs, unclear business value and inadequate risk controls,” Anushree Verma, a senior director analyst at Gartner, wrote in the Harvard Business Review.
“As the hype intensifies, so does the risk of misapplication, leading to failed initiatives that erode trust in both the technology and its providers.”
Verma said business leaders had to resist the temptation to deploy agentic AI indiscriminately and instead focus on cases in which agentic AI’s unique capabilities create measurable business value.
“Success depends on a disciplined approach to use-case selection, a clear-eyed assessment of technology maturity, and a willingness to leverage alternative AI techniques when they are more appropriate,” she said.
Gartner recommended that business leaders first evaluate where agentic AI is truly the best fit.
“Not every workflow or customer pain point requires the autonomy and complexity of agentic AI,” Verma said. “In many cases, traditional automation techniques, machine learning, or even traditional software may deliver equal or greater value at a fraction of the cost and risk.”
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