Key Takeaways
- Agentic AI is the latest evolution in AI and promises to rapidly change the way businesses operate.
- Moving beyond the prompt-and-response of generative AI, AI agents can act autonomously to solve complex problems, create strategies, make decisions, and adapt their actions.
- Businesses may still be introducing generative AI to their environments, but they need to start preparing now for the arrival of agentic AI.
If you're like most businesses, you probably have a few generative AI pilots or proofs-of-concept underway to see where you can use the emerging technology, and if you're ahead of the game, you have some use cases in production.
But just when you thought it was safe to venture into those generative AI waters, here comes agentic AI, and it's something you'll need to know about because it's promising to change the way businesses are run. It's a big enough deal that Forrester Research analysts listed it among the top 10 emerging technologies of 2024, and their counterparts at Gartner have it at number one of their list of strategic technology trends for 2025.
So what makes it such a game-changer? Previous generations of AI recognized and analyzed patterns in data to make predictions. With generative AI, the large language models (LLMs) take in prompts from humans and create conten—words, images, and videos—in response. It will become a cornerstone in modern business, but it's still limited in its ability to act independently.
A new way to AI
Agentic AI goes beyond that. These models and systems can act independently to solve multi-step, complex problems and reach goals, all with little to no human intervention. AI agents are software programs that can autonomously reason, plan iteratively, adapt to changes, interact with and learn from their environment, collaborate with other AI agents, analyze data, make predictions, and develop strategies. An AI agent can create its own prompts.
A generative AI system might be asked to come up with a description of a new product for a marketing blitz. An agentic AI system will be tasked with analyzing market data, coming up with a marketing plan that includes target demographics, partners, and budget allocation, and then launching the plan.
Not all AI agents are created equal. There are varying kinds of AI agents for different jobs, such as simple reflex agents that essentially absorb input from the environment around them and make decisions based on what they sense. Other agents armed with search and planning algorithms will plan and perform a sequence of actions to reach particular goals while learning agents use input from their environment and experiences to improve their behavior.
There also are master—or hierarchical—agents that organize, manage, and direct the actions of AI agents below them, essentially acting as the maestro to the orchestra.
Major IT vendors are furiously enabling agentic AI in their portfolios. Amazon Web Services (AWS), Microsoft, Cisco, Salesforce, SAP, Adobe, ServiceNow … the list keeps growing. Google unveiled the second generation of its Gemini AI this month, complete with multiple prototype AI agents.
Many business leaders are already turning an eye to AI agents. According to global consultancy company Capgemini, 10% of organizations already are using AI agents in their business, while a whopping 82% plan to integrate them in the next one to three years.
A growing list of use cases
The number of use cases for agentic AI seems to be growing just as quickly as the number of businesses wanting to use it and vendors integrating it into their portfolios. Here are some of the higher-profile use cases for the technology:
- Customer support: Customer service chatbots now will answer a single question. However, an AI agent will understand the context of the interaction and the problem and resolve it. Rather than simply pointing to an alternative flight, the agentic AI system can find the best option, book the flight, change tickets if needed, and reserve a rental car at the destination, all with no human guidance. In Capgemini's survey, 64% of business leaders said agentic AI will “significantly” improve customer service.
- Enterprise workflows: Vendors like Salesforce and ServiceNow are integrating AI agents into their products, which will streamline business processes to increase efficiencies. They can write and edit emails, schedule them for sending, include attachments, send them, and then follow up if there are questions or they go unanswered. Agents can listen to a conference call, create to-do lists based on it, develop and assign tasks, create a strategy, and decide next steps.
- Cybersecurity: Rather than simply detecting a possible attack and alerting analysts, AI agents will be able to detect an anomaly, analyze it, determine its risk, devise and execute a defense strategy, and mitigate the threat.
- Financial planning: Agents can create real-time insights by continuously analyzing financial data from multiple sources, track performance, recommend and make changes to investments or budgets, review the data, and make predictions. At the same time, they can autonomously monitor transactions, flag suspicious behavior, detect unusual account activity, and make adjustments to stave off potential fraud attempts.
- Supply chain: AI agents can proactively manage third-party vendor engagements by analyzing the market, comparing vendors, choosing which to partner with based on specific criteria, and then track their performance, manage their contracts, and make recommendations.
These are just a handful of the rapidly expanding use cases for agentic AI, but they illustrate the capabilities the technology can bring to businesses and the exponential effect it can have on everything from customer satisfaction to cost efficiencies.
The time to prepare is now
That said, to take advantage of AI agents, executives need to prepare their businesses. Here are key steps they need to take to lay the groundwork:
- Get your data ready: Agentic AI, like any AI, relies on high-quality, well-structured, secure, and highly varied data to learn and act on. A data strategy should not only cover collecting and managing it but also integrating it because agents pull data from multiple sources. Data governance is key to ensuring it's secure and complies with regulations.
- Have the business prepared: Adopting any AI requires ensuring that roles are redefined and employees are trained to work with it, monitor it, and get results from it. Agentic AI will change how a company operates in many ways, which means it will change the way employees work. If workers are ready to embrace it, the road forward will be smoother.
- Have AI discipline: Don't try to throw AI agents at everything. Most companies are just beginning to get their generative AI legs underneath them. Try using agents in a particular part of the business and work up from there.
- Choose the model to use: Like generative AI and predictive AI before it, agentic AI will need powerful—and expensive—infrastructure to run it. Is it best to use the cloud, where there is already scalable infrastructure with the IT and computer components to run the workloads? Or will some tasks need to run on premises for data security and sovereignty reasons? You likely are looking at a hybrid situation.
Agentic AI is on the doorstep, and it will change what businesses can do. Erik Pounds, Director of Product Marketing at Nvidia, called it the “next frontier of artificial intelligence.”
As with any technology, it brings benefits and challenges. The key is to understand what it can do, how to be ready for it, and what security and other hurdles will have to be dealt with. The time to start learning about it is now.
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