AI Agents: Transforming Industries and Customer Experiences

Artificial intelligence (AI) has rapidly become a central part of the workday for many. Now, the technology is poised to revolutionize entire industries.

“Artificial intelligence has been a useful tool. However, it hasn’t transformed how industries and businesses operate. That major change is happening now,” says Dan Bjurman.

From Support Tools to Autonomous Actors

While Generative AI has become important for many businesses in recent years, and most people use the technology daily at work and in their personal lives, Dan Bjurman believes that generative AI has not delivered the business value that many companies expected when the technology became widely available a few years ago.

Tools based on generative AI can already write emails, be good conversational partners, come up with ideas, and write summaries of meetings, to name a few examples.

But AI agents, which are quickly gaining traction, will do more than save time. They will change industries and sectors, according to Dan Bjurman.

“We are moving from using AI to work faster, smarter, and better, to AI actually performing tasks from start to finish. And the end result is just as good, if not better. It’s a quantum leap in a very short time,” he says.

Performing Concrete Actions

The market for AI agents is estimated to be worth $1 trillion by 2030. In addition to Salesforce, several major software vendors and most other tech giants are launching AI agents. The investments are massive.

What distinguishes AI agents from other tools is that, instead of “just” creating texts, presentations, calculations, and other things, they can perform concrete actions.

The greatest value of AI agents is realized on the business side. The international consulting firm McKinsey estimates that AI automation can free up 70 to 80 percent of the time for employees in sales, customer service, and marketing.

AI agents can be used to answer emails, handle customer inquiries, follow up with contacts, order products and services, optimize sales processes, marketing, and the handling of sales and returns.

What are AI Agents?

An AI agent is an autonomous, intelligent software that can make its own decisions and perform actions in real-time, without constant human intervention.

Autonomy: Makes its own decisions and performs actions without human intervention.
Continuous Learning: Improves based on feedback and data.
Real-time Response: Available 24/7 without downtime.
Scalable: Handles varying workloads without loss of quality.
Summarizes Data Sources: Connects to existing systems and data sources for complete automation.

Better Customer Experience

“There are almost no limitations to what an AI agent can do. And it does it itself. There is no need for human handling. This provides enormous savings in both time and money for companies of all sizes,” explains Dan Bjurman.

Most people are familiar with chatbots in customer service. These often only answer simple questions and may not provide a particularly good customer experience.

AI agents go further: They know your profile, order history, and customer relationship, and can not only answer questions but also perform concrete actions.

This could involve changing an order, updating a delivery address, checking stock balance, or handling a return and booking delivery.

“Today, most people prefer to talk to a human rather than a chatbot, but with an AI agent, this will soon change,” says Dan Bjurman.

Fully Staffed Around the Clock, Year-Round

There is a wide range of industries that have already adopted AI agents: from typical retail and e-commerce players to technology companies, travel companies, and logistics operators.

Those who are furthest ahead are building the entire customer management process with an “agent-first” mindset, according to Dan Bjurman.

“All businesses, regardless of industry or sector, public or private, communicate with customers and partners. This is where AI agents will have their greatest value. It will be challenging to maintain competitiveness and provide a good enough customer experience without AI agents in the future,” he says.

AI agents are never finished with the job or on leave. They never get overworked. They are connected 24/7, year-round. They communicate in all languages. They cost a fraction of an employee, and they make it possible to quickly and easily scale up. This makes it easy to handle increased volumes that may arise for various reasons.

“An example is in the retail sector, where there is enormous pressure on customer service after Christmas or Black Friday. AI agents can quickly and efficiently handle inquiries without the need to involve more people,” says Dan Bjurman.

Freeing Up Time for Employees

Operating a customer service center is costly, and there is often high staff turnover.

“In a customer center, the same questions often come up over and over again. Let AI agents handle the routine tasks, and let employees focus on the more complex and time-consuming issues that make a difference,” says Dan Bjurman.

It’s easy to get started with AI agents. Dan Bjurman explains that the technology can almost be regarded as “off-the-shelf.” Companies that implement AI agents usually need less than a week to set up the agent itself. With necessary testing and training, the projects often end up taking three to six weeks for simpler tasks.

“You often start small, with simple tasks, and gradually let the agent take over increasingly advanced tasks. The quality of AI agents depends on the data they have access to, so you often start where the data sources are good and expand over time, so that the agents can handle increasingly complex scenarios.”

How to Get Started with AI Agents

Identify Business Needs: Focus on the specific use cases where AI agents can provide the greatest value.
Evaluate Existing Solutions: Investigate which ready-made AI agents are available on the market today, so you don’t waste time building everything from scratch.
Build the Right Team: Combine expertise in AI development, data analysis, and business understanding.
Start Small: Develop a simple first version in a limited area for quick testing and feedback, and iterate from there to more complex scenarios.
Keep Track of Data and Security: Ensure good data quality, comply with privacy requirements, and don’t forget the ethical consequences.

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