AI Agents: What You Need to Know to Boost Business Impact

Saving money with AI is a new business utopia. Near the vast opportunities of AI, there are a lot of tricks in handing off the leading roles to bots. But what if I decide that not all roles should transfer to the bots?

Let's figure out to be or not to be (like a classic said). So, let's take a ride on the facts.

AI as a Business Growth Driver

There’s a rumor going around: “Generative AI makes everything more efficient.” Or how about this one — “Now hiring: Team Lead for AI Bots Department…”

These are the kinds of clickbait titles designed to grab attention and pull you into the AI hype wave.

In the last 2-3 years, there has been a trend to implement AI in various business processes. By the beginning of 2025, around 72% companies are implementing AI in their work process.In fact, statistical data also show that in 2024, businesses had used AI tools almost doubling than in 2023. A crazy world and crazy strategies go around. 

Companies have increasingly looked at the benefits and bonuses that AI brings to the business. Some executives even prefer AI but simultaneously try to achieve two main goals: controlling costs and increasing efficiency. As we all know, implementing AI features in your product is not cheap.

Starbucks quickly saw that tapping into customer data—like purchase habits and visit frequency—was key to boosting lifetime value, gaining a real competitive edge, and maximizing it with AI potential.

But let’s jump on details: 32% of UK organizations consider digitalization to be a top priority in achieving optimized and flexible operations.

There are a lot of possibilities for applications of AI in business, but if we paint a picture with broad strokes, one of the key areas where AI can drive business growth is working with data. 

Companies are adopting data-driven marketing approaches to collect information from various channels, including social networks, email, and direct customer interactions.AI tools are designed to analyze this data at high speed, identifying patterns, correlations, or even anomalies that would take a normal person much longer to identify.

What's the Difference Between AI Agents and GPT

If you, like me, are wondering what the difference is between AI agents and GPT4, I did some research, and here are a few things I learned:

Purpose

Chat GPT is used to generate text or respond to input.

AI agent to achieve set goals.

Autonomy

Chat GPT, Gemini, and Copilot act strictly within the framework of the received prompt; that is, they perform the tasks that the user has just asked them to do.

In turn, the AI ​​agent was created to perform tasks independently. It can observe the environment and make decisions to achieve a specific goal (for example, sending emails, making transactions, or interacting with applications).

FYI: despite all its autonomy and independence, the AI ​​agent uses Chat GPT models to generate text.

Examples of use

ChatGPT and similar AI models are used to generate various types of text content.

AI agents are designed to perform specific tasks as automated assistants—self-driving cars are a prime example.

Interestingly, the more you engage AI with your data, the more accurate and tailored its recommendations become. It’s almost like upgrading its skills over time. Sounds like one of the most valuable investments, doesn’t it?

AI in Business Opportunities

The first application of AI that comes to mind is enhancing the personalized customer experience.

Personalized customer experience

What if I say that Amazon has been using ML for purchasing recommendations long ago, but now they have decided to strengthen buyers' activities via personal recommendations and all customer journeys of their client? 

For example, beyond general recommendations like similar items, they now suggest complete sets of related products. Impressive, right? Imagine you’re searching for gluten-free breakfast options—thanks to AI, Amazon intelligently highlights the term “gluten-free” in relevant product descriptions within your search results, making them stand out prominently.

Optimizing Operations

Using AI in business can automate repetitive tasks and reduce associated costs. Increased productivity is an additional benefit.A strong example of AI-driven optimization is predictive maintenance—servicing factory equipment before it breaks down and disrupts the entire AI in the supply chain. By interpreting sensor data, AI can forecast potential failures.

Similarly, in anti-money laundering efforts, AI can analyze transactions, identify suspicious patterns (such as transfers to high-risk countries or unusually large amounts), and help prevent illegal activity.

Marketing Campaigns

Nike ad campaign in South Korea is a good example of using AI with a large language model (LLM) to boost customer engagement.

When users searched for Nike sneakers, they encountered a chatbot-style AI search engine that recommended specific Nike models, gave detailed product explanations, and offered links to purchase. Is it an AI brand manager? You decide, but it walks potential customers through every step of the sales process, from product recommendations to buy assistance.

For businesses, integrating AI tools into the marketing technology stack can further personalize campaigns and boost engagement.

Financial Flow Management

Research claims that AI-powered forecasting models can reduce error rates by up to 50% by analyzing vast volumes of financial data sets and identifying subtle patterns humans might miss.

Accordingly, forecasting in this format can help companies anticipate financial needs and manage liquidity. However, the most interesting thing about this is that AI algorithms include real-time data analysis.

This format of using AI tools can be a salvation for retail businesses to highlight periods of low cash flow due to slow inventory turnover and adjust purchasing strategies to avoid crises.

If you are now thinking about how to properly apply it to your business, then you are on the right track. Cool tip for a growing SaaS business, you can use AI tools to predict customer payment delays, and accordingly improve the cash flow that works for you

Client segmentation with AI

Traditional segmentation includes essential characteristics: demographic data, psychographics, and behavioral. The traditional approach is limited and assumes that people within a basic set of characteristics act the same. AI-based segmentation has the advantage of skipping the assumption, focusing on data, and allowing the business to focus on specific processes. 

For example, AI tools for analyzing customer sentiment will help you determine in which segments of your audience people are more likely to cancel their subscription to your product and analyze the "health" of this segment so that you can focus on increasing sales. The approach also lets you closely assess the customer life cycle and identify the most valuable customers.

Good question if you want to know how to build customer segments with AI. Check this video to find access to AI oriented marketing future. 

Customer lifetime value prediction

Accurate Customer Lifetime Value (LTV) metrics help you make data-driven decisions on where to invest your marketing budget and identify your most valuable customers.

Still unsure whether to measure LTV (CLTV or CLV)? Here’s an insight that changed my perspective: Whether you actively track customer relationships or not, they already exist. Your customers are moving through different stages of their journey with you—understanding their value allows you to optimize engagement and maximize long-term profitability.

A typical approach to calculating lifetime value looks at past data sets to determine which existing customers may be the most valuable.

AI tools, in turn, analyze huge amounts of data and can predict which customers are likely to cut back on their spending, decrease their frequency of purchases, or stop interacting with the company by analyzing their behavior patterns.

And, of course, using customer lifetime value data with AI, a business strategy can direct maximum ai personalization at all touchpoints.

Inside AI Agents: Strategies, Adoption, and Impact

AI agents are covered in advertising noise, as their creators, major market players like Microsoft, Oracle, Salesforce, and others, are making huge bets on their development and widespread implementation by various businesses.

What are AI agents, and will they be so indispensable in 2025?

A summary of statistics tells us that AI is a super-complex software solution that can automate most routine tasks to free up the team's time for creative and strategic tasks. AI agents work on the same systems as best AI chatbots but can act independently or collaborate to achieve large-scale goals and take on the coverage of a specific chain of business processes.

Let's go through the chronology of events. In October 2024, Microsoft announced that Copilot Studio would allow enterprises to create autonomous business agents to connect to CRM systems and solve business problems. The company soon increased its influence in the AI ​​agent market and created special AI agents for specific use cases.

Salesforce also released two versions of its agents, Agentforce and Agentforce 2.0, in late 2024. These agents included a library of ready-made skills and workflow integrations.

Integrating a cost-effective AI agent into a business is like buying a franchise: a ready-made solution with turnkey capabilities that minimizes startup costs, adapts quickly, and delivers predictable returns.The only difference is that a franchise scales a business, and an AI agent enhances processes.

Accenture predicts that AI chatbots may become the primary "users" of corporate systems by 2030, performing tasks that currently require human participation.

Is this scary? We'll live and see, but we need to understand now that there will be new challenges related to data security and the changing role of employees.

AI Agents: Practical Applications

When considering what are the challenges of using AI in supply chains, businesses often face issues like data silos, integration with legacy systems, and ensuring real-time data accuracy across multiple stakeholders. Let’s explore more details.

IT Solution Development

Have you heard about Devin ai? Well, it was declared the world's first AI software engineer, meaning AI can solve real-world coding problems.

Workflow Automation

Since Microsoft's AI agents have appeared, they can act as assistants inside Word or Outlook to perform routine tasks.

For example, if a client has sent a request to perform a transaction, Outlook or Word is open, and the AI ​​agent gets access to the company's data and executes the request. Does it affect security? Perhaps, but we are already sending the risks associated with AI to the trash bin.

Text and Image Creation

It seems that this is where it all began. But AI agents are more intellectually savvy. Now, you can "feed" them not just scripts but all contact and public information, and the AI ​​agent issues a report based on your data quickly.

HR AI agents

Currently, a low-risk application of AI agents is in AI talent acquisition—supporting internal teams with candidate search, employee support, and seamless onboarding.

If you're not yet sure how much AI can help you in your business, check out 25 powerful ways AI agents can boost productivity and generate leads for your business.

There are different types of AI agents; let's look at specific examples of such agents.

E-commerce AI agents

E-commerce platforms use AI agents to improve the shopping experience. They can place orders automatically, provide delivery updates, and, of course, personalized recommendations.

Some of the first brands to work with e-commerce AI agents were eBay, Etsy, and Instacart.

For such cooperation, the e-commerce giants attracted the AI ​​agent Operator from Open AI. The operator will be able to order products, type the text the user needs, and find a gift. If necessary, users can intervene at any time and make adjustments.

Sales and Marketing AI agents

All businesses, without exception, can use AI agents in the marketing and sales departments. We have already discussed the use cases above; the main ones are collecting and processing data from leads, sending personalized messages, qualifying leads, etc.

AgentForce from Salesforce and AI Accelerator from Microsoft are predicted to become some of the giants of AI agents in marketing and sales. They integrate with the business CRM system, and their main task is to speed up the completion of deals.

Agent developer companies predict that agents will be able to join sales calls in real-time and provide instant feedback.

A great example is the integration of Agentforce and Slack. Now, you can add Agentforce AI to any Slack conversation for real-time assistance. The user only needs to mention the AI ​​agent directly in the dialogue.

“Right now, thousands of customers are working with thousands of agents and humans, all in tandem. As a CEO, I’m not just managing human beings, but I’m also managing agents. There is an agentic layer around support today at Salesforce.”

Marc Benioff, CEO, Salesforce 

AI agents as a support service

It is important to understand that an AI agent is not just a chatbot. An AI agent performs tasks on your behalf. Depending on the type of AI agent for the support service, it can change passwords, process orders, and give product recommendations. It is already a little scary; how deeply does an AI agent penetrate your business? Let's move on.

Top roles of AI chatbots in customer service:

• Hybrid customer support system- the implementation of AI agents in real conversations;

•  Receiving information in real-time;

•  Sentiment analysis and forecasting customer needs.

Top 3 AI Agents for Support Services:

• IBM Watson Assistant Personalized chatbot based on artificial intelligence and virtual assistants

• Zendesk Provides self-service and targeted support, empowering customers to find answers themselves.

• CodeConductor Real-time solutions with predictive roi analytics to serve customers faster and more efficiently.

You can also check out a broader list of AI marketing tools on Marketing Kawowarka’s full 2025 overview.

AI Agents in Hospitality

AI agents can increase hotel sales. It sounds like something very hyped, but let's look at the facts: AI agents in hotels are used to improve the experience of interacting with guests by analyzing their preferences and behavior. This option works both during the guest's stay in the form of a digital concierge and in pre-check-in and post-check-out mode.

Radisson Hotel plans to implement an AI agent to automate routine tasks, namely: processing incoming and outgoing calls, capturing and re-engaging qualified leads, and providing permanent customer support in more than 50 languages.

If you have a desire to test the AI ​​agent, catch a video in which it has already been done for you, but the AI ​​agent is tested not by a person, but by another AI agent. 

Content Recommendation Systems

This option helps analyze the content viewed by the user and recommend what he will like. However, a custom approach to this process is interesting. For example, Netflix reports that personalization goes beyond the application's homepage to minimize the time spent searching and selecting the desired options.

Crypto AI Agents

It is becoming increasingly difficult to keep track of changes in the world of digital assets, and AI agents are actively helping to organize this process. They analyze data and market trends, which helps to manage the associated risks.

If we talk about blockchain-based AI agents, the picture becomes even broader: they cannot track transactions in the chain, initiate deals, interact with smart contracts, or even act on behalf of a player in a game.

Jeremiah Owyang, partner at Blitzscaling Ventures, revealed an interesting thought about this. He outlined that today's world is moving from B2B and B2C to B2AI agents. He meant that AI agents will become guides between business and people. What do you think about this? Share in the comments.

AI Agents in Healthcare

The main task of AI agents in the healthcare sector is to reduce the administrative burden by automating the process of making an appointment or supporting routine patient questions.

However, AI agents that help coordinate the treatment process are already becoming more active. 

For example, Eleos has developed an AI agent that provides proactive information in the background to help doctors analyze their patients and identify errors in documentation.

As AI agents receive updates, they can perform more complex tasks, such as extracting patient data, indicating potential diagnoses, suggesting treatment options, and, most interestingly, taking into account side effects and allergic reactions.

Where to Invest in AI Agent for Maximum Impact: How does AI reduce costs

We don’t know how AI agents will impact business and the labor market; we can only assume that the paradigm will change and labor supply will partially change directions due to the trend of increasing process automation and the need to interpret and implement AI ideas.

From a business focus point, it remains clear that all business processes require large investments to integrate AI agents. Ideally, according to its industry, each company should have an initial direction that will help optimize the result.

Let’s explore several strategies to reduce AI-related investments by focusing on high-impact areas:

• Customer Support

Implementing an AI agent in your customer support team can significantly reduce wait times, handle multiple conversations simultaneously, and improve over time by learning from each interaction.

• Procurement Process

AI agents can analyze large volumes of data to support informed decision-making. With better inventory management and resource allocation, this leads to substantial cost savings.

• Invoice and Document Processing

AI agents equipped with Optical Character Recognition (OCR) and Natural Language Processing (NLP) can automate document handling without compromising accuracy or quality.

• Marketing Operations

Integrate an AI agent into your martech stack to streamline content management at scale, optimize ad spend, and precisely target high-value customer segments. (Just be mindful—there are ongoing discussions about how Google evaluates fully AI-generated content.)

Key AI Agents on the Market 

As of early 2025, the development of AI agents has reached significant volumes and results. The AI ​​agent market is projected to grow from $5.1 billion to $47.1 billion by 2030.

Key business players and giants of information services and processes: Microsoft, Google, Amazon, Oracle, and Salesforce have launched AI agents explicitly tailored for business operations.

Here are some key facts from the AI ​​agent universe that may interest you. Oracle Miracle Agent is part of a suite of over 50 AI agents. These agents are trained to automate routine tasks: collecting data from commercial proposals, paying invoices, generating purchase requests, etc.

Microsoft introduced its Copilot Studio, which allows you to create custom AI agents for business automation.

OpenAI's Operator aims to make AI agents universal tools for everyday use, and Salesforce Agentforce is so imbued with the idea of ​​adaptation that it made it possible to quickly adapt its AI agents to different roles using tools that Salesforce itself provides (for example, the MuleSoft API). They even have ready-made templates for setting up AI agent roles (for example, a personal buyer or a sales representative)

Problems with implementing AI agents include:

• Difficulty of integration with legacy systems due to compatibility issues.

• Problems with data privacy, especially in industries such as healthcare, where data security is one of the key factors for the success of a healthcare provider.

• A long process of integrating an AI agent.

These are all solvable problems, and soon the market will offer a wide range of services and solutions tailored to them—striking a balance between supply and demand.

Summary

AI in Business – Smart Growth or Overhyped Dream?

The excitement around AI is hard to ignore—and for good reason.

One major strength lies in working with data. AI can analyze massive volumes from various channels—email, CRM, social media—and spot patterns no human could catch in time. This enables everything from personalized product recommendations to risk forecasting in finance.

Beyond classic AI tools like ChatGPT, AI agents emerge as the next evolution.

Unlike static models, agents operate more autonomously—carrying out tasks, making decisions, and interacting with systems. Think of them as intelligent co-workers in customer support, marketing, procurement, and development.

However, while success stories from Amazon, Nike, Salesforce, and Radisson Hotels show the possibilities, challenges remain—especially with integration, privacy, and long-term maintenance.

It’s not a question of replacing people with bots. It’s about enhancing processes and freeing up time for human teams to focus on what really matters: strategy, creativity, and long-term thinking.

In short, AI isn’t a magic fix—but when applied intentionally, it can become one of the most valuable tools for scaling a business with clarity and control.

To dive deeper into marketing innovations like AI, you can explore the Marketing Kawowarka blog for broader insights and up-to-date trends in the industry.