AI Agents for Business: Full Guide 2024

Intro

Generative AI (Gen AI) is our past, present, and future. The rise of Gen AI has unlocked significant opportunities for multiple organizations, especially with the significant boost of AI agents for business and AI agents enterprise. These AI-powered software tools can plan and execute tasks or assist humans by providing specific services in absolutely different areas.

Just imagine that according to the recent McKinsey research, applying generative AI to customer care functions could increase productivity by between 30 to 45 percent. Jorge Amar, McKinsey’s Senior Partner, says: “My belief is that gen AI agents can and will transform various corporate services and workflows. It will help us automate a lot of tasks that were not adding value while creating a better experience for both employees and customers.” 

Their other partner Lari predicts that 50 percent of today’s work activities could be automated to occur around 2055.

Business process automation is one of the biggest fields where building AI agents for enterprise can be applied. AI agents for businesses have the powerful potential to accelerate the automation of numerous workflows that would otherwise demand significant resources. The impact of AI Agents Enterprise solutions extends even further, with an estimated 60 to 70 percent of work hours in the global economy theoretically automatable using existing technologies, including generative AI development. However, achieving this will require not an easy effort in developing solutions and driving AI Agents for enterprise adoption.

What is AI Agent and How it Works.

Let’s go back to our agent expert Lari Hämäläinen for a while. He defined AI Agents really well: “When we talk about gen AI agents, we mean software entities that can orchestrate complex workflows, coordinate activities among multiple agents, apply logic, and evaluate answers. These agents can help automate processes in organizations or augment workers and customers as they perform processes. This is valuable because it will not only help humans do their jobs better but also fully digitalize underlying processes and services.”

Open-source AI Agents as well as closed-source ones are usually used in the areas of a company’s workflow automation (human resources, finance, customer service, administration, marketing, sales, logistics, hiring, and many other departments). Their flexibility and ability to be combined in a multiagent system, allow them to be used in absolutely different businesses, starting with the cases when you need to build an MVP of AI Agent, and finishing with the complex enterprise custom development.

For a better understanding of how AI Agent works, let’s have a look at the schema below. Additionally, feel free to read our previous article about the origin and structure of AI agents. 

Overall, the workflow of AI Agent looks like this:

1. Businesses usually provide the data they need to use to get the desired outcome.
2. Agent receives the data and using an AI engine or additionally, such tools as Large Language Models, or Large Vision Models, processes this data. This is actually the process of business task automation itself. 
3. Optionally, all these processes may be managed by the user in software solutions, customized with multiple integrations or add-ons. 
4. Finally, the processed data is converted into the needed result (output). It can be a generated answer to the customer, a custom image, a PDF report, or anything else you need for your business.

Finally, if you would like to learn more about how AI Agents for enterprise could improve your workflow, don’t hesitate to contact us. Our AI experts will help you to understand how these agents work, and how exactly they may benefit your business.

AI Agent Use Cases For Business

Generative AI Agents offer a huge potential across various business use cases. AI Agent use cases can be different and depend on many factors: from automating complex workflows in logistics & retail to providing smart decisions in education & healthcare. By applying AI in different areas, businesses can significantly reduce the resources needed to perform routine tasks and improve overall efficiency.

Let’s have a look at the table below to see the real samples of AI agent use cases.

As far as we can see, AI agents are now being deployed in innovative roles such as AI employees, AI tutors, and AI Learning Management Systems (LMS). AI employees can take on routine tasks, freeing human workers to focus on strategic initiatives. For example, AI agents can manage scheduling, data entry, and basic HR tasks, significantly improving productivity and reducing operational costs. In sales and marketing, AI agents analyze customer data to personalize campaigns and predict market trends, ensuring businesses stay ahead of the competition.

Moreover, AI agents are also transforming education and legal areas. AI tutors provide personalized learning experiences by adapting content to students’ needs, offering instant feedback, and guiding learners through complex topics. AI LMS platforms automate administrative tasks such as grading, tracking student progress, and recommending learning paths, making education more efficient and tailored to each learner. 

Legal AI Automation is provided by agents that can process huge amounts of data, provide their compliance check, and output the needed results.

Real Examples of Using AI Agents in Business

We have already discovered that AI agents can be applied in different business fields. Now, let’s look at real examples of AI Agent use cases. 

IONI

IONI is an AI Agents Platform that allows you to create and customize agents up to your business requirements. You can start with a Free Trial option to see how it works and even test your data. 

IONI has already been used in the following business cases:

• Customer Support. Using IONI’s AI Chatbot we helped several companies (travel, healthcare, IT, logistics) to automate their customer service and increase CSAT. By using a Customer Support Agent these companies can now answer queries 24/7 and may save costs on hiring additional human agents.
• Travel. IONI’s agents' customization with our AI Text-to-Video Generation Tool allowed us to create a solution for a Travel Agency that needed to automate their visa processing workflow. Using AI Avatar integration and LLMs it was combined into a mobile application that helped users apply for visas and discuss all the needed questions.
• Education. IONI’s agents are successfully used in Online Education Projects. They may handle students’ onboarding, answer their questions, and even process the lessons workflow up to the set requirements.

To sum up, IONI may help you create agents to automate tasks related to data processing, documentation analysis, image recognition, and processing (computer vision), staff onboarding, and other cases. Feel free to contact us to learn more about it.

Relevance

Relevance is a modern AI platform designed to help businesses feel the power of artificial intelligence to gain deeper insights from their data. It specializes in understanding and analyzing unstructured data, such as text, images, and audio, which traditionally pose challenges for businesses to interpret and utilize effectively. 

Using machine learning and natural language processing (NLP)  in their AI agents, Relevance AI allows startups, SMBs, and enterprises to enjoy more informed decision-making and strategic planning. What sets Relevance AI apart is its user-friendly interface and the flexibility it offers to businesses across various industries. Whether you’re in marketing or customer service, the platform provides AI Agents that can be integrated seamlessly into existing workflows. 

Finally, this platform can build and deploy AI models without needing extensive coding knowledge, making it accessible even to non-technical users. By simplifying the process of data analysis and making AI more accessible, Relevance AI helps businesses stay competitive in an increasingly data-driven world.

ELAI

Elai is a custom software platform that functions as an AI agent and can simulate the feeling of human interaction, making the content it generates more relatable and engaging. In other words, this is an AI Twins builder or AI Avatar Generator.

The avatars created by Elai can convey emotion and adapt their tone to match the content’s context, creating a sense of presence that enhances viewer engagement. This emotional humanity together with natural-sounding speech, makes this AI agent look more human-oriented.

Elai is a game-changer for many startups and enterprises. Elai’s AI Agents for business are used in:

• Education (as AI Tutors). The tool helped educational institutions generate AI-based video tutorials using AI avatars that simulate live instructors. These AI tutors explain complex concepts in an engaging, relatable manner and replace human teachers.

• 24/7 Customer Support.  Elai’s avatars are used as virtual customer support agents, providing consistent assistance to customers with a friendly, human-like touch.
• Marketing and Sales. This AI Twins builder generates targeted video content for many software development companies and digital marketing agencies. They do not need to spend a lot of time on film-making anymore.

Beam

Beam is a custom AI agent platform that enables business owners to create highly personalized, context-aware customer experiences. The platform is developed to integrate seamlessly with existing systems and 3rd party APIs, allowing businesses to automate routine tasks, and provide instant responses to customer inquiries. This helps companies and enterprises improve customer satisfaction, reduce operational costs, and increase CSAT.

Beam AI can continuously learn and adapt from every interaction, making it more effective over time. This dynamic learning capability ensures that the AI agent becomes increasingly attuned to customer needs and preferences, enabling more accurate and relevant responses. By offering a scalable, intelligent, and user-friendly platform, Beam helps businesses to boost their profits and improve customer engagement.

5 Tips on ROIs After AI Agent Integration

There are many ways how AI Agents can benefit your business but not all of them can bring you ROIs. Let’s have a look at the real examples (tips) that will help you to understand how it works.

Tip 1. Cut Operational Costs by Automating Repetitive Tasks

Implement AI agents to your company to take over time-consuming, repetitive tasks like searching and data entry, appointment scheduling, or handling common customer queries. This automation can significantly reduce labor costs and minimize human error. AI Employees are no longer the future - it is our present.

Real Business Case. An eCommerce company automated order processing and inventory management with AI agents, reducing operational costs by 30% and allowing staff to focus on strategic growth initiatives.

Tip 2. Boost Revenue by Improving Customer Experience. 

You can integrate AI agents to provide 24/7 customer support, ensuring quick, accurate responses that improve customer satisfaction and loyalty. Satisfied customers are more likely to return and spend more, increasing your revenue over time.

Real Business Case. Online IT School used an AI-powered chatbot connected to Slack to resolve customer issues instantly, resulting in a 35% increase in customer retention and a 25% rise in average customer spend.

Tip 3. Raise Profit Margins by Optimizing Decision-Making

AI agents can be particularly used to analyze large datasets and generate insights that inform smarter business decisions. You can significantly boost your profit margins by reducing risk and identifying profitable opportunities.

Real Business Case. A financial services company integrated AI to analyze market data, leading to more accurate investment decisions and a 29% improvement in portfolio performance, driving higher client returns and firm profits.

Tip 4. Increase Marketing ROI with Personalized Campaigns.

You may use AI agents to segment your customer base and deliver highly targeted, personalized marketing & sales campaigns. By increasing the relevance of your lead generation campaigns, you’ll see higher conversion rates and a better return on your marketing costs.

Real Business Case. A big retail enterprise used AI to create personalized email campaigns, which resulted in a 41% increase in click-through rates and a 24% uptick in sales, significantly increasing marketing and sales ROI.

Tip 5. Speed Up Your Operations to Reduce Costs

We recommend integrating AI agents into your business operational processes to identify inefficiencies and optimize workflows. This option can help you to reduce costs and improve overall business performance, leading to greater profitability.

Real Business Case. A manufacturing firm used AI agents to monitor production lines in real-time, reducing downtime by 35% and cutting operational costs by 20%, which directly enhanced the company’s profit margins.

Overall, these tips show practical steps that your company can take to integrate AI agents effectively, ensuring a strong ROI and financial outcomes.

Conclusion

The rapid growth of generative AI has transformed how businesses can regularly use AI agents and AI Chatbots, especially those that are based on LLMs. In the early stages of LLMs, limitations such as hallucinations and high processing costs confined their use to simpler tasks, like offering expertise or generating images. Complex workflows were out of reach due to the compounded inaccuracies that could arise when LLMs with only 80 percent accuracy were applied to multi-step processes.

However, the late advancements have significantly broadened the potential applications of LLMs. Innovations in the accuracy of LLMs, such as GPT-4 Omni or LLaMa 3 improved memory structures, enhanced logic frameworks, and better evaluation methods have opened the way for these models to handle more complex workflows. LLMs can now self-correct and provide higher accuracy, especially when paired with experienced humans to manage tricky cases. This top-notch collaboration of AI technologies and human skills results in high-quality outcomes.

To sum up, in recent years, the nature of many generative AI case studies has given way to a trend towards standardization and industrialization, resembling packaged software. This shift will streamline implementation and reduce costs, making it easier for businesses to deploy AI agents across a broader range of real-world applications, including niche use cases for multiple enterprises.