Latest news with #AIagents
Entrepreneur
2 hours ago
- Business
- Entrepreneur
How I Streamlined My Financial Reporting for Less Than $50 a Year
Disclosure: Our goal is to feature products and services that we think you'll find interesting and useful. If you purchase them, Entrepreneur may get a small share of the revenue from the sale from our commerce partners. Written by Natalie Nguyen As someone who manages multiple revenue streams—from client work to small investments—I've learned that real-time financial insight isn't a "nice to have." It's a necessity. But hiring a full-time analyst isn't in the cards for every entrepreneur, especially when you're running lean. That's why I tried the Amsflow Pro Plan, and it's been one of the most efficient upgrades to my business stack this year. Right now, you can get a 1-year subscription for $49.99 (normally $228), and it's packed with features designed specifically for professionals who need high-quality financial analysis. Amsflow uses AI agents (Lisa and X-Ray) to process and analyze up to 10 years of financial data. In my case, I connected data from a couple of ventures and started receiving automatic reports on trend shifts, anomalies, and KPIs—without having to sort through spreadsheets or create custom dashboards myself. It also pushes out price, technical, and fundamental alerts, which I've set to notify me when certain revenue or cost thresholds are hit. The dashboards are surprisingly intuitive. I use the returns heat maps to get a quick visual on what's working and what's not, and the screener agent helps me evaluate new opportunities based on specific criteria I set—whether I'm tracking a new investment or reevaluating client accounts. For entrepreneurs who are juggling multiple hats, Amsflow feels like having a part-time analyst in your back pocket. It helps me make faster, better-informed financial decisions, which is the whole point when you're trying to grow a business without wasting time or budget. Best of all, it's scalable. I don't need to upgrade or worry about hidden fees as I expand. If your business relies on clear, consistent financial oversight, this tool pays for itself almost immediately. Grab your Amsflow Pro one-year plan for just $49.99 and make smarter decisions with your finances. Amsflow AI Financial Analysis: Pro Plan See Deal StackSocial prices subject to change.
Forbes
8 hours ago
- Business
- Forbes
Are AI Agents The Future Of Customer Service?
If you've ever tried canceling an internet subscription or disputing an unexpected charge, you know the drill: Hold music, chatbot loops and long wait times. For consumers, it's often a friction-filled experience. For companies, it's both a cost center and a branding liability. In 2024, Qualtrics XM Institute reported that poor customer experience was putting $3.7 trillion in global sales at risk. And while many companies have deployed AI assistants to handle routine tasks, those tools typically stop short of full resolution. A new generation of AI agents may finally change that — not just answering questions, but planning, executing and resolving complex, multi-step requests on a user's behalf. And that shift has real business implications. From AI Chatbots To AI Agents Generative AI tools like ChatGPT are designed to assist with language — answering, summarizing, or completing tasks based on user prompts. But they depend on constant human input. AI agents, on the other hand, are built for autonomy. They can reason, plan and take action — from negotiating bills to rescheduling flights or resolving disputes — across multiple systems, often without further user guidance. That distinction matters to experts like Stanley Wei, cofounder of Pine AI. 'We believe the future of customer service is fully autonomous,' told me. 'Our goal is to handle the details that matter most to users with minimal friction.' Wei sees this evolution as more than just efficiency. 'The agent model is evolving quickly,' he said. 'What used to be script-driven bots are now systems that reason through ambiguous instructions, update actions in real time and learn from user feedback.' Take Pine AI, for instance. Its system includes a planning agent, a task execution agent, and a user-facing agent that communicates across email, web, or phone. Wei says this modular approach allows each agent to specialize, similar to how enterprises separate front-office and back-office operations. 'We've found that agent specialization — instead of one monolithic system — leads to faster, more accurate outcomes,' he said. Instead of reactive chat support, companies can now offer proactive AI agents that complete user objectives end-to-end and do it at scale. The ROI Of Autonomy Customer service doesn't just cost time; it costs money. For B2C brands, support operations often represent a major expense line, especially in industries with high churn or complex issue resolution. Gartner predicts that by 2030, AI agents will handle 80% of common customer service tasks and reduce operational costs by up to 30%. That's not just a margin boost, but also a competitive advantage. 'We built our system to understand, plan and execute tasks in a way that mirrors human workflows, but with faster turnaround and greater consistency,' Wei said. Rather than depending solely on API integrations or rigid scripts, Pine AI's agents can interact directly with graphical user interfaces — logging into websites, filling out dynamic forms and navigating complex web environments much like a human would. That capability matters in the real world, where many support processes still live behind inconsistent or third-party front ends. While automation works well for routine tasks, Wei explained that the hardest part is teaching agents to manage unexpected or complex situations. 'In customer service, the hardest 20% of tasks account for 80% of the frustration. The agent needs not just to act, but to know when to escalate or pause,' he said. Several other companies are also pushing this frontier of agentic AI in the customer service world. Adept AI, for example, is building enterprise-wide agents that can operate software tools like a trained employee. Cognosys AI offers agents that manage everything from food orders to customer complaints, especially in hospitality and quick-service environments. While their target markets differ from company to company, they all have a similar thesis at their core: The notion that autonomous execution is the next evolution of AI productivity. Turning AI Agents Into Revenue Engines Beyond support cost reduction, AI agents also introduce a new kind of revenue opportunity. Companies that develop vertical-specific agents — for customer support, sales, travel, or billing — are already exploring monetization through subscription models, usage-based pricing, and white-labeled integrations. In short, AI agents aren't just service tools; they're becoming business platforms. But while that potential is exciting, their success largely depends on trust and performance. 'Building an agent that can handle the diversity and complexity of real-world customer requests was our biggest challenge,' Wei said. Accuracy, memory and user context all matter, and users have little patience for hallucinations or missteps, especially during important interactions. That means building not just smart agents, but accountable ones. Companies must ensure agents are equipped with ethical guardrails, fallback protocols and privacy-safe data practices. While AI agents can operate independently, human oversight is still essential — particularly in regulated or high-risk domains. Forrester analysts Stephanie Liu and William McKeon-White advise enterprises to approach this shift strategically. 'The right approach to AI agents is to tune out the hype and start small,' they write. 'Instead of focusing entirely on outcomes, fine-tuning agent tasks and setting boundaries should be the immediate priority.' When AI Works For You Statista forecasts that by 2031, most consumers will prefer using AI agents over websites to complete tasks and access information. That signals a broader shift: Not just toward smarter systems, but toward systems that act on your behalf. The stakes are high. In service-driven industries, responsiveness and resolution speed are critical to retention. While human workers can offer empathy and nuance, AI agents promise always-on execution — with consistent tone, full context recall and no wait times. Wei believes the shift to AI agents is less about replacing websites and more about removing friction in decision-heavy interactions. 'The ideal experience is one where the system already knows what you need and takes care of it before you ask,' he said. 'That's where we see the opportunity: Not in mimicking humans, but in delivering outcomes with less effort from the user.' Done right, agentic systems have the potential to transform how businesses interact with customers — not by replacing the human touch, but by reducing the burden of everyday digital friction. In a market where loyalty often comes down to ease, that transformation may prove more valuable than any product upgrade.
Forbes
a day ago
- Business
- Forbes
AI Agent Bosses Are Here—And They're Redefining How We Lead
AI agent bosses are the latest trend in workplaces. HR managers are working on navigating the inevitable shift without raising anxiety. AI agents aren't just digital assistants. They're autonomous systems with the power to assign tasks, track performance and make decisions, functions once reserved for human managers. What makes this different from past waves of automation is 'who' the AI is starting to replace. It's not the frontline workers, but the managers themselves. As AI agents begin to handle the responsibilities once owned by supervisors, team leads and even directors, companies are confronting a new kind of disruption: one that changes not what work gets done, but how leadership operates. The shift is beyond technological; it's organizational and deeply personal. Microsoft's 2025 Work Trend Index reveals just how accelerated the rise of agent bosses is becoming. Leaders' ambitions are soaring. Eighty-two percent say they'll leverage digital labor to expand capacity within the next 12 to 18 months, while 46% already use AI agents to automate team workflows or business processes. Across the global workforce, 53% of leaders insist productivity must rise, yet 80% of employees feel they lack the time or energy to meet current demands. Adoption gaps between leaders and employees are stark: 67% of leaders are familiar with AI agents, compared to just 40% of employees, and 79% of leaders believe AI will accelerate their career trajectory, versus 67% of employees. Eighty-three percent of senior leaders expect AI to grant earlier access to strategic work. Many are planning new hires, with 35% considering AI trainers and 78% targeting AI-focused roles. The AI agent boss era isn't coming; it's already reshaping how organizations define leadership and structure teams. The Shifting Role Of Human Leaders Until recently, AI lived comfortably in the realm of augmentation, boosting productivity without replacing judgment. But agent-based systems are changing that dynamic. Built on large language models and reinforced learning, these agents operate independently, directing human work without day-to-day human supervision. Some organizations are already experimenting with AI, assigning work, reviewing deliverables and delivering feedback. In effect, humans are beginning to report to software. If AI agents can handle task management, performance tracking and process optimization, what's left for traditional managers? The answer: oversight, orchestration and emotional intelligence. Human leaders are now managing teams of employees who work directly under AI bosses. This shifts leadership upward into a new layer of abstraction, where the job is less about assigning tasks and more about training agents and translating strategy into algorithms. Leadership is becoming less operational and more architectural. But Can An Agent Inspire? AI agent bosses optimize, delegate and even coach. But they can't empathize, mentor or lead through uncertainty the way people can. That's where the limits of algorithmic leadership become clear. Leadership involves navigating conflict resolution and ensuring that values align. These are dimensions where humans still have a competitive edge. So, Are AI Bosses Taking Over? Not entirely, but they're definitely moving in. What's more likely is a hybrid structure, where human leaders manage systems that manage people. It's a subtle but profound shift in how authority flows. The AI boss is not here to replace all leaders. But it is reshaping leadership, redefining influence and challenging every assumption about what it means to lead in the first place.
Bloomberg
2 days ago
- Business
- Bloomberg
OpenAI-Challenger Manus Preps Big Upgrade to Main Agent Platform
Chinese-founded startup Manus is rolling out a feature that allows broad research by assigning tasks to scores of AI agents working in tandem, in potentially the biggest update since launching its signature artificial intelligence platform in March. The function, called Wide Research, will enable Manus to process large numbers of data entries simultaneously by roping in multiple AI agents, according to people familiar with its tech development. The tool will become available as soon as this week, the people said, starting with a top-tier subscription priced at $199 a month.
Yahoo
2 days ago
- Business
- Yahoo
What I learned at Fortune Brainstorm AI Singapore
Hello and welcome to Eye on AI. In this edition…China launches its own AI Action Plan…Meta hires an OpenAI veteran for new 'chief scientist' role, raising questions about status of AI 'godfather' LeCun…what if AI doesn't speed up scientific progress?…and economists can't agree on the impact AI superintelligence could have.I spent last week in Singapore at Fortune Brainstorm AI Singapore. It was our second time hosting this event in the thriving city-state, and I was eager to find out what had changed since last year. Here are some of the key thoughts and impressions I took away from the conference:The pace of AI adoption is equally fast everywhere. With previous technological waves, many Asian companies and countries lagged the U.S., Europe, and China in adoption. But that's not the case with AI. Instead, the pace of deployment seems equally fast—and equally ambitious— wants AI agents. Few are actually using them yet. Everyone anticipated AI agents last year; now they're here from OpenAI, Google, Anthropic, and others. Yet adoption still trails the hype everywhere. Why?Agents, by their very nature, are higher risk than most kinds of predictive AI or generative AI that simply produces content. And right now, AI agents are often not that reliable. Some of the ways to make them more reliable—such as using multiple agents, each assigned a specific task within a workflow and with some agents assigned to check the work of others—are also a result, Vivek Luthra, Accenture's Asia-Pacific data and AI lead, said that most businesses are using AI to assist human workers within existing workflows. In some cases, they may be using AI as an 'advisor' to provide decision support. But few are automating entire however, predicts this will change dramatically. By 2028, he forecasts that one-third of large companies will have deployed AI agents, and that about 15% of day-to-day workflows could be fully automated. (Accenture is a sponsor of Brainstorm AI.) This is because costs will continue to come down, models will continue to become more capable and reliable, and more companies will figure out how to redesign workflows to take advantage of these new agentic impact on the job market is not easy to discern—yet. Pei Ying Chua, LinkedIn's APAC head economist, told the conference that despite anecdotal reports that young graduates are struggling to find work, there's not yet much evidence of this in the data on open roles that LinkedIn tracks. That said, there has been an uptick in the average number of applications required before coders land a the same panel with Chua, both Madhu Kurup, vice president of engineering at Indeed, and Sun Sun Lim, vice president at Singapore Management University, emphasized the need for employees to acquire both AI skills—techniques for prompting models, familiarity with how to build an AI agent, an understanding and of the strengths and weaknesses of different kinds of AI—as well as human 'soft skills.' As AI transforms all jobs, soft skills like flexibility, resilience, and critical thinking matter more than ever, the two panelists O'Reilly, Workday's general manager for ASEAN, said that she thinks AI will lead many companies to adopt an organizational structure based more around teams from diverse functional areas coming together for specific projects and then being reconfigured for the next project. She said this would be like an 'internal gig economy' for employees. Traditional reporting lines and vertical organization would need to change in favor of a flatter, more dynamic org chart, she is destiny. From several panels at Brainstorm AI Singapore, it was clear that access to AI infrastructure is going to be critical. This is true even when countries don't want to build their own models. Just running models—what's known as 'inference'—also requires a lot of AI building data center capacity requires big investments in energy. Rangu Salgame, CEO and co-founder of Princeton Digital Group, said that in the near-term fossil fuels, especially natural gas, would likely be used to power the data center buildout in Asia—which is not great news for climate policy. But in the medium-term, he saw great potential for AI data centers to force countries to build out renewable energy capacity, such as solar power and offshore AI matters. Delivering it is challenging. Everyone is talking about the need for sovereign AI—and that was certainly the case in Southeast Asia, too. Governments want the ability to control their own destiny when it comes to AI technology and not become overly dependent on solutions from the U.S. and China. But achieving that independence is tricky, as was clear from several of the sessions at Brainstorm increasingly capable open-source models are giving governments some options in terms of which models they choose to build their solutions on, there are still some big there's the huge cost of building out data center capacity and constructing the power plants and upgrading national grids to support it, which I mentioned above. Then there is the issue of training AI models that are adept at local languages and also understand cultural nuance. This requires curating data sets specific to local context, said Kasima Tharnpipitchai, head of AI strategy at SCB 10X, which is building an LLM for the Thai language. 'There are no tricks here, you really have to do the work,' he said. 'It really is just effort. It's almost brute force.'Embodied AI is China's big strength. While it often looks like the U.S. and China are evenly matched when it comes to the capabilities of AI models, China has a massive advantage when it comes to 'embodied AI'—that is, AI that will live in physical devices, from robotaxis to humanoid robots. That was the message from Rui Ma, founder of Tech Buzz China, who spoke on a fascinating panel looking at the geopolitics of AI. China controls almost the entire robotics supply chain and is making rapid progress creating cheap and practical robots designed for factories, as well as general purpose humanoid robots. (One of those humanoid robots—Terri, which uses software from Hong Kong startup Auki Labs, but whose body comes from Chinese robotics company Unitree—wowed delegates at Brainstorm AI.)There is a middle path between the U.S. and China. Singapore has consistently tried to thread a path between the two superpowers. And at Brainstorm AI, the country's digital minister Josephine Teo said that the country was finding places to act as a bridge between the U.S. and China. For instance, in late April, Singapore played a key role in hosting a meeting of AI safety researchers from both the U.S., China, and elsewhere that arrived at what is called the 'Singapore Consensus'—an agreement that AI systems should be reliable, secure, and aligned with human values, as well as a shared vision about ways to ensure that is the case. With that, here's more AI news. Jeremy Before we get to the news, I want to flag my most recent Fortune magazine feature on AI darling Perplexity. If you want to know why the 'answer engine' company is now worth $18 billion and why tech giants from Google to Apple are watching its every move, please give the story a read. Note: The essay above was written and edited by Fortune staff. The news items below were selected by the newsletter author, created using AI, and then edited and fact-checked. This story was originally featured on
