{"id":1545,"date":"2025-04-01T12:00:00","date_gmt":"2025-04-01T12:00:00","guid":{"rendered":"https:\/\/web-stil.info\/?p=1545"},"modified":"2025-05-02T22:15:20","modified_gmt":"2025-05-02T22:15:20","slug":"ai-agents-what-they-are-how-they-work-and-why-you-should-probably-invest-in-them-especially-if-youre-an-enterprise-level-business-new-data","status":"publish","type":"post","link":"https:\/\/web-stil.info\/index.php\/2025\/04\/01\/ai-agents-what-they-are-how-they-work-and-why-you-should-probably-invest-in-them-especially-if-youre-an-enterprise-level-business-new-data\/","title":{"rendered":"AI Agents: What They Are, How They Work, and Why You Should Probably Invest in Them (Especially If You\u2019re An Enterprise-Level Business) [+ New Data]"},"content":{"rendered":"
Before you start Googling: No, AI agents aren\u2019t secret spies fueled by mysterious government schemes. The <\/span>AI agents<\/a> I\u2019m talking about actually serve an entirely different purpose. <\/span><\/p>\n Despite their misleading name, AI agents were designed to assist, enhance, and optimize the operations and workflows of various businesses, especially enterprise-level ones. Although they\u2019re a relatively new technology, AI agents are already changing how companies troubleshoot issues, simplify processes, and increase employee productivity.<\/p>\n In this post, I\u2019ll talk about what AI agents are, how they serve different business needs, and (if you\u2019re considering using them) what to expect from their capabilities. Plus, you\u2019ll get some real, unfiltered, industry-informed advice from two very well-versed AI agent experts.<\/p>\n Let\u2019s get into it.<\/p>\n Table of Contents:<\/strong><\/p>\n <\/a> <\/p>\n As I mentioned earlier, AI agents are relatively new to enterprise-level companies. However, their adoption is growing rapidly as enterprise-level businesses recognize their ability to do the things that their human reps either 1) <\/strong>don\u2019t have the time to do or 2)<\/strong> no longer can do (not because they\u2019re not equipped to, but because they\u2019re focusing on more high-impact, strategic tasks and requests).<\/p>\n At the core of all AI agents is the capability to streamline decision-making and problem-solving efforts, making operations \u2014 no matter what department they\u2019re happening in \u2014 easier, faster, and less time-consuming<\/a>.<\/p>\n Thus, mostly<\/em> every AI agent can:<\/p>\n Beyond these functions, AI agents can also learn and adapt over time. Through machine learning, they refine their responses, optimize processes, and improve efficiency based on patterns, feedback, and data. This makes them an ideal investment for businesses looking to enhance productivity, reduce manual work, and make data-informed choices faster.<\/p>\n There\u2019s still much to learn about AI agents, from how they serve businesses and employees to the long-term impact of their integration across industries. But before I dive into the nitty-gritty details, I think it\u2019s important to cover some need-to-know statistics about overall AI usage in sales.<\/p>\n All of this said, visit the following section to explore key insights on how AI is shaping the sales landscape.<\/p>\n <\/a> <\/p>\n When it comes to using AI in the enterprise biz world, salesfolks are the most<\/em> keen on leveraging it to get things done.<\/p>\n Here\u2019s a closer look at salespeoples\u2019 overall sentiments around AI adoption and effectiveness, according to HubSpot\u2019s 2024 Sales Trends Report<\/a>:<\/p>\n Additionally, HubSpot\u2019s 2024 AI Trends for Sales Report<\/a> revealed the following:<\/p>\n So, what does this all mean? Well, a few things. Here\u2019s my short n\u2019 sweet summary:<\/p>\n With adoption rates rising and AI-driven tools proving their ROI, it\u2019s clear that AI agents are becoming essential assets for modern enterprise businesses. But beyond just the numbers, what exactly are these AI agents doing to drive such impact? And what should enterprise-level businesses know before investing in this new tech?<\/p>\n I tapped Jeannie Jaworski<\/a>, Senior Customer Success Manager at HubSpot, and Wesley Baum<\/a>, AI Specialist at Bluleadz, for answers to your (likely) questions, comments, and concerns. Scroll through the next few sections to read what they said.<\/p>\n <\/a> <\/p>\n AI agents can do many things, but their effectiveness in delivering results all depends on how they\u2019re programmed. Still, regardless of their assigned function or industry application, AI agents, ultimately, have been designed to work collaboratively \u2014 both with each other and with employees.<\/p>\n I chatted with Jeannie Jaworski<\/a>, Senior Customer Success Manager (North America) at HubSpot, to get her honest perspective on:<\/p>\n Check out what she had to say below:<\/p>\n When Jeannie and I got to chit-chatting, one of the first things I probed her about was the challenges she\u2019s seen her clients face while onboarding AI agents into their business. She told me (candidly, of course) that the thing folks worry about most is likely the same fear you\u2019ve already seen splashed across tons of news headlines: that AI is going to replace human reps.<\/p>\n \u201cI think there is still a level of concern about people wanting to make sure this doesn\u2019t replace their job,\u201d she told me. And although she acknowledged this widespread concern, Jeannie also made it very clear that she knows there\u2019s a different, more empowering way to look at the rise of AI.<\/p>\n \u201cI think that [AI agents] are really valuable if you can see, like, your employees are already doing things that they don\u2019t like to do because of the repetition involved, so those are the things you can outsource to the agent. So it\u2019s definitely not replacing an employee, it\u2019s just allowing employees to focus on things that do require the human touch, instead of the things that can be automated.\u201d<\/p>\n Finally, at the tail-end of our conversation, I asked Jeannie about what advice would she give to other enterprise-level businesses considering AI agents, and what factors should they evaluate before implementation.<\/p>\n Her response was indicative of two things: 1)<\/strong> data is everything and 2) <\/strong>you can\u2019t measure AI effectiveness in a vacuum, then expect a clear path to meaningful improvement.<\/p>\n \u201cIt\u2019s really important for you to be collecting data, not just about the AI agents\u2019 performance, but the human agents\u2019 performance,\u201d Jeannie shared. She then further explained, \u201cA lot of these tools \u2014 like HubSpot\u2019s Breeze AI customer agent<\/a> \u2014 will have built-in analytics to tell you about the quantity of the chats, the amount they were able to resolve on their own \u2026 all of that is built in. But if you haven\u2019t built that out for your human agents, you won\u2019t have anything to compare [that data] to.\u201d<\/p>\n Jeannie went on to emphasize how getting granular with these data assessments is crucial to identifying areas for growth, pinpointing performance gaps, and, most importantly, enhancing the overall customer experience. \u201cIt\u2019s important to [measure] things like CSAT to understand the satisfaction that your customers have when interacting with both your human and AI agents,\u201d she said.<\/p>\n \u201cIf we\u2019re not understanding how our human agents are able to respond and how customers feel about that, we\u2019re missing the opportunity to see the success and the impact of responsiveness that AI agents have on a business\u2019s customer experience.\u201d<\/p>\n <\/a> <\/p>\n Wesley Baum, Bluleadz\u2019s AI Specialist, knows everything<\/em> there is to know about building and deploying enterprise AI agents. Heck, it\u2019s quite literally what he does for a living.<\/p>\n So when we both had a free moment to connect, I asked him everything (yes, everything<\/em>) I could about:<\/p>\n So, if you\u2019re looking to give AI agents a try but \u2026<\/p>\n Then you\u2019re in the right place. Here\u2019s an overview of the most valuable insights that Wesley shared with me below:<\/p>\n During our conversation, I asked Wesley about the key steps involved in building an AI agent and, more importantly, what challenges he\u2019s seen typically arise for businesses as they seek to customize an AI agent for their specific needs and workflows.<\/p>\n He shared that there are a couple of main components when building an agent. They\u2019re as follows:<\/p>\n Once you have all these pillars in place, Wesley says you can then start building out the AI agent of your dreams. He explained, \u201cOnce you have a model selected, you have your prompting and your roll down; you\u2019ve identified a use case, of course, for this agent, you gave it their context using RAG systems<\/a>, you actually have to build out the tools, right?\u201d<\/p>\n Wesley then went on to share that this component of building an AI agent is more varied but, truthfully, not as complex.<\/p>\n \u201cReally, it\u2019s just certain APIs,\u201d he added. Generative AI APIs are just application programming interfaces that allow developers to integrate AI models capable of creating content \u2014 such as text, images, code, or audio \u2014 into their own apps, tools, or platforms.<\/p>\n \u201cMost of the agents that [businesses] are going to get value from, that enterprise solutions are going to build upon, will be through orchestrating APIs. Because it\u2019s consistent,\u201d he told me. \u201cAnd so, those APIs are the tools in which an agent would interact with your text and the same way that you would interact with the UI.\u201d<\/p>\n When I asked Wesley about what challenges he\u2019s seen his clients face the most when implementing an AI agent, he pointed out (similarly to Jeannie) one distinct thing: Data collection.<\/p>\n \u201cThe biggest issue people don\u2019t expect is data. It\u2019s all about data,\u201d Wesley said. He even admitted that when he\u2019s onboarding customers onto HubSpot\u2019s CRM, the first thing he asks about is data architecture.<\/p>\n He also emphasized that he isn\u2019t afraid to ask super specific questions, such as:<\/p>\n \u201cAll of this is very useful because, without proper data, ChatGPT\u2019s not gonna change your business unless it\u2019s built specifically for that, which is reliant upon your data quality.\u201d<\/p>\n Lastly, toward the end of our one-on-one conversation, I asked Wesley about how he anticipates AI agents evolving in the next few years and what emerging trends enterprises should pay attention to when considering AI adoption.<\/p>\n Not only did he keep it real with me but, furthermore, he underscored how personalization and scalability, inevitably, go hand-in-hand.<\/p>\n \u201c[AI agents] have to be customized specifically to how every business does business,\u201d he stated. \u201cOne-size-fits-all agents \u2026 they\u2019re not going to dramatically change your business with AI. It will have an impact, but it won\u2019t be transformative in the way that an eco-system of multi-agent systems \u2014 all working well within your tech stack, for your clients, for your products, communicating with your teams \u2014 would. All of it has to be customized.\u201d<\/p>\n<\/a><\/span><\/p>\n
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Statistics You Should Know About AI Usage in Sales<\/h2>\n
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What do AI agents do?<\/h2>\n
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1. AI agents are here to improve how your reps work, not replace them.<\/h3>\n
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2. If you collect data now, your AI agents (and your human ones) will reap the rewards later.<\/h3>\n
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How To Build an AI Agent, According to Wesley Baum, Bluleadz\u2019s AI Specialist<\/h2>\n
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1. The hardest part about building an AI agent? Knowing what\u2019s needed to make it thrive.<\/h3>\n
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2. When it comes to building a proficient AI agent, it\u2019s all about data.<\/h3>\n
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3. There will be a rising demand for customized, business-specific AI agent ecosystems.<\/h3>\n
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