“Alfa is the culmination of everything we’ve learned about how asset managers want to work with AI,” Joshua Pantony, chief executive of the investment research firm, said in a news release Monday (July 7).
“It’s fast, powerful, and most importantly, it’s agentic. That means it works on your behalf, behind the scenes, to find the insights in the noise. This is what the future of AI in finance looks like: research and ideas delivered before you even ask,” Pantony said.
Among Alfa’s offerings is the ability to extract key performance indicators such as margins, multiples and segment revenue and automatically source them from filings. It also includes email monitoring, searching inboxes for important updates, documents and disclosures.
The launch of the new version of Alfa is happening at a time when companies are embracing AI, “not just as a tool, but as a colleague, a software system capable of thinking, doing, and even acting on its own,” as PYMNTS wrote last week.
“That, after all, is the promise of agentic AI: systems that can not only generate content or parse data, but go beyond passive tasks to autonomously make decisions, initiate workflows, and even interact with other software to complete tasks end to end,” the report added. “It’s AI not just with brains, but with agency.”
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These systems are in play in industries like customer service, software development, finance, logistics and healthcare, doing things like booking meetings, launching marketing campaigns, processing invoices, or overseeing entire workflows autonomously.
But although some business leaders hold lofty views for autonomous AI, new research by PYMNTS Intelligence finds a trust gap among executives when it comes to agentic AI that indicates deep concerns about accountability and compliance.
All the same, full-scale enterprise adoption is limited. Despite its growing capabilities, agentic AI is being employed in experimental or limited test settings, with most systems functioning under human supervision.
“But why are mid-market companies hesitating to unleash the full power of autonomous AI? The answer is both strategic and psychological. While the technological potential is enormous, the readiness of systems (and humans) is far less clear,” PYMNTS wrote. “For AI to take action autonomously, executives must trust not just the output, but the entire decision-making process behind it. That trust is hard to earn — and easy to lose.”
