Microsoft’s rollout of autonomous artificial intelligence (AI) agents marks one of Big Tech’s strongest efforts yet to bring to market software that can independently handle customer service and business tasks with minimal human oversight.
The move, challenging Salesforce’s recent entry into the field of intelligent automationshows how enterprise software providers are rushing to give companies AI systems that can handle parts of their operations, from scheduling meetings to resolving customer complaints and processing orders.
Industry experts say this shift could reduce operational costs for early adopters while raising new questions about how companies should select and deploy advanced AI tools that aim to replicate human capabilities.
“Autonomous AI agents will be a game changer both customer service and operations,” JJ Lopez Murphyhead of data science and AI at Globaltold PYMNTS. “In terms of customer service, they will act more like intelligent advisors, helping people get the help they need faster with better, more personalized responses. This means happier customers and less pressure on support teams, while reducing costs.”
AI agents are computer programs that can sense their environment, make decisions, and take actions to achieve specific goals. They range from simple, rule-based systems to complex models that can learn from experience and adapt their behavior, similar to how a chess program observes the board, evaluates possible moves, and chooses actions to try to win the game.
Agents of change?
Microsoft’s autonomous AI agents, launching next month for Copilot, will allow companies to automate routine tasks such as investigating sales leads, tracking supplier delays, and managing customer service queries. The system pulls data from Microsoft 365, Dataverse, and Fabric platforms to perform tasks independently.
said Microsoft that early pilot results from companies like McKinsey show time savings, reducing customer onboarding processes from typical time frames to 10% of expected duration. Microsoft is releasing 10 ready-to-use agents that focus on specific business functions across sales, service, finance and supply chain management. However, details about their reliability and limitations are not yet public.
Agents such as those from Microsoft may have specific customer service and commercial applications. The agents drive personalized recommendations, use AI to analyze user behavior and provide customized suggestions. Mychailo Maksymenkohead of the sales force practice at the digital consultancy firm Customer timestold PYMNTS.
“This reduces waiting times, increases customer satisfaction and allows staff to focus on more complex tasks,” he says. “On the operations side, AI agents can automate daily processes such as data management, supply chain optimization and predictive analytics, driving cost savings and improving overall efficiency. As more companies adopt these resources, we may see a fundamental shift toward more seamless, 24/7 service models.”
In a recent example, Murphy pointed out that Target rolled out an AI tool to help employees quickly resolved on the work floor challenges, making daily operations more efficient.
“These types of AI agents can adapt on the fly – adjusting their approach, tools and goals in real time, which is perfect for handling complex or unexpected tasks that customers present to store associates,” he says. “Imagine not having to try to hack into the support chat just so you get a human agent because it will solve your problems automatically.”
Choosing a real estate agent
When selecting an AI agent system, Murphy cautioned that reliability varies significantly between platforms, with some more prone to errors and faulty decision-making than others.
“So it is important to choose platforms with solid reasoning skills and good self-checks,” he said. “It’s not that ‘one’ of them is hallucination-free, but the stronger the model, and the better you can control the environment with things like guardrails and other methods, the smoother the experience will be.”
According to Murphy, a crucial factor is how well the AI platform fits with your current tools and software, ideally allowing for easy adjustments and step-by-step implementation.
“And of course you have to think about costs. Don’t go overboard with your expenses, but make sure you get solid efficiency gains,” he said. “But most importantly, teach your team how to use AI agents properly and ensure they understand data privacy and ethical considerations.”
