Microsoft released 10 AI agents today for:
You cannot drive on Highway 101N in SF Bay Area without seeing an advertisement for an AI SDR agent from several companies. A16z has recently invested in an AI AE company. There is confusion about build vs. buy. Product and Engineering teams want to build them in-house and customer-facing teams do not have million dollar budgets and a year for a fully flushed out product.
Before Microsoft added the supply-chain operations agent, SDR, AE, and Customer Service Representatives have been common.
AI agents can be simple to really complicated and advanced. Let's look at the autonomous car journey as an analogy.
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Cars have evolved from fully manual to highly autonomous systems, much like how software tools have transformed.
Initially, you had to manage everything while driving, then came cruise control and lane-keeping assist, which helped but still needed your attention. Over time, cars could handle more tasks, like Tesla’s early Autopilot, until today, where fully autonomous vehicles are a reality in some situations.
This journey mirrors how software has gone from simple tools to copilots and now fully autonomous AI agents.
Just like cars, software tools started as basic assistants where you had to do most of the work.
Then came copilots, which help you with real-time suggestions and efficiency improvements but keep you in control. Think of tools like Microsoft Office 365’s Copilot or GitHub Copilot—they help you write, analyze, or code, but you remain in the driver’s seat.
As technology advanced, simple AI agents emerged that could handle specific tasks autonomously, like scheduling or customer service. These agents perform well-defined tasks within a limited scope but still need human oversight for complex decisions.
Now, decision-making autonomous AI agents are here. These agents can learn, adapt, and make decisions across multiple domains. They handle complex tasks, analyze data, and can work without human intervention, much like fully autonomous cars navigating diverse environments.
AI agents are already everywhere, from mobile apps to websites.
Copilots: Microsoft Office 365’s Copilot and GitHub Copilot are tools that boost team productivity by offering intelligent assistance while you stay in control. In Office 365, Copilot helps you generate content, analyze data, and create presentations based on your prompts in Word, Excel, and PowerPoint. Similarly, GitHub Copilot suggests code snippets and functions as you type, helping developers write code more efficiently—it acts as a helpful companion rather than taking over.
Writing tools: Notion AI and Grammarly are examples of writing tools that use AI agents to enhance your productivity and writing quality. Notion AI assists within its workspace by generating text, brainstorming ideas, and summarizing content, interacting with you to improve your writing process. Similarly, Grammarly acts as an AI agent that provides real-time grammar and style suggestions, tone detection, and clarity improvements, helping you refine your writing across various platforms. Additionally, the latest versions of macOS, iOS, and iPadOS have built-in writing tools that leverage AI to assist users with content creation and editing, making the writing experience more intuitive and efficient.
Personal AI Agents: Replika and Cleo are AI agents that engage users through chat to offer personalized assistance in different domains. Replika acts as a personal AI friend you can chat with about anything, providing companionship and learning from your conversations to become more personalized over time. Cleo, on the other hand, is a conversational AI agent for personal finance that helps you manage finances, track spending, and set budgeting goals by offering insights and suggestions based on your financial activity.
AI Assistant Agents: Siri, Amazon Alexa, and Google Assistant are AI voice assistants that perform various tasks through voice interaction. Siri, integrated into Apple devices, sends messages, sets reminders, provides information, and controls smart home accessories, acting as a personal AI agent. Alexa, embedded in Amazon Echo devices, handles tasks like playing music, controlling smart home devices, answering questions, and providing news updates. Google Assistant, available on Android devices and smart speakers, engages in two-way conversations to help with scheduling, answering queries, and managing smart home devices.
B2B AI Agents: Salesforce Einstein, Zendesk Answer Bot, and Cast incorporate AI agents to enhance their respective services. Einstein provides predictive analytics, automates data entry, and aids decision-making within Salesforce’s CRM platform. Zendesk Answer Bot autonomously interacts with users to resolve customer support issues by suggesting relevant help articles. Cast offers AI-generated presentations with a presenter that can be interrupted to answer audience questions in real time from both internalized knowledge and real time data access, acting like a human presenter while delivering personalized content in 13 languages.
Several platforms now allow businesses to create custom AI agents. OpenAI’s API with function calling, Microsoft’s Azure Bot Service, and Agentforce are all powerful platforms for building AI agents, each offering unique capabilities.
Despite their growing presence, AI agents are just one part of a larger solution. The real value lies in the core features and services of the product. AI agents enhance interaction and accessibility but don’t replace the underlying offerings.
For example, while an AI agent can help automate a process, the heavy lifting—data management, infrastructure, and domain-specific algorithms—still happens behind the scenes. The illusion that AI agents can be quickly integrated is misleading; they require significant effort in training, context understanding, and system integration.
AI agents are transforming how we interact with technology, enhancing user experiences, and automating tasks. However, they are not a replacement for the core functionalities of products. As businesses and users, recognizing this balance between innovation and practicality is key to navigating the evolving tech landscape.
