
AI is on the move, and the next big step is agentic AI. More than just another incremental update, this is a shift toward smarter, more autonomous systems that can take charge and make decisions without constant input.
“By 2028, 33% of enterprise software applications will include agentic AI, up from less than 1% in 2024, enabling 15% of day-to-day work decisions to be made autonomous.” Gartner
But what is agentic AI, exactly?
In simple terms, it’s the kind of AI that doesn’t need to be micromanaged. Think of it as traditional AI’s brainy, self-sufficient cousin. Instead of waiting around for instructions, it takes the initiative – perceiving, deciding and acting to achieve its goals.
Most AI solutions we’re familiar with need us to give them detailed instructions or prompts to get results – and the outcomes can be hit or miss, depending on how skilled we are at crafting these prompts. Agentic AI offers a whole new layer of autonomy. It operates independently, setting its own smaller tasks to achieve bigger goals, all while staying within the limits you’ve set.
Automation that thinks
You can use AI agents to enhance the capabilities of your existing process automation tools, whether you’re using RPA, workflow automation or another type of solution.
By integrating agentic AI into your existing set-up, you can unlock greater efficiency and create process automation systems that are not only faster and more accurate but also capable of proactive problem-solving and continuous improvement.
“Within three years, agentic AI will impact every area of the business for both buyer and seller, transforming human and nonhuman interactions throughout the purchasing journey and post-sale customer experience.” – Jessie Johnson, Principal Analyst, Forrester
What makes Agentic AI unique?
It’s proactive
Agentic AI doesn’t sit idle waiting for orders, it takes the initiative. It spots opportunities, identifies problems and acts to address them before you’ve even noticed. Picture a co-worker who refills the printer paper without anyone asking.
It’s goal-driven
AI agents are designed to focus on achieving specific outcomes or objectives. Instead of simply executing predefined tasks, they use advanced reasoning and planning to determine the best way to reach a goal.
For example, an AI agent in Customer Support might aim to resolve a customer’s issue as efficiently and effectively as possible. It can consider multiple factors like the customer’s history, available solutions and real-time feedback to adapt its approach and find the most suitable resolution.
It’s agile
Agentic AI learns from experience and adapts its approach. If something changes, it adjusts its behaviour to keep up. It’s like a driver who knows how to take a detour when the main road is blocked.
It has contextual awareness
This type of AI is great at understanding its surroundings. It gathers and analyses information to make well-informed decisions. Instead of relying on guesswork, it connects the dots across different areas to provide accurate and relevant responses.
It can be a team player
Even though AI agents are designed to be more independent than traditional AI solutions, they know how to collaborate. Agentic AI works well alongside humans or other AI systems, adjusting its approach based on what’s needed. Think of it as the team member who knows when to lead, when to assist and when to step back.
Quick comparison: AI agents vs. Traditional AI solutions
AI agent | Traditional AI | |
Working style | Acts independently | Follows pre-defined rules |
Taking initiative | Initiates actions proactively | Waits for instructions |
Ability to learn | Adapts and improves | No learning or adaptation |
Context awareness | Combines information from different sources | Operates in isolation |
Approach | Plans and reasons to achieve goals | Completes tasks one step at a time |
Ability to collaborate | Collaborates with other agents or humans | Functions in isolation |
Decision-making | Weighs trade-offs and adapts in real time | Uses fixed decision rules |
Scalability | Flexible, works in many areas | Narrowly focused, requires redesign for scaling |
How to use Agentic AI in your business
There are so many different ways that Agentic AI can be used in a business context, and as the technology develops the world should truly be your oyster in terms of applying AI Agents to all kinds of business automation processes. For now, here are a couple of examples of what can be achieved:
Use case 1: Complaints handling
In a customer service or success team, agentic AI can take automation to a new level of efficiency. Rather than following a predefined script, it can work dynamically, combining automation with intelligence to handle complaints independently. For example, it might analyse the customer’s issue, cross-reference it with previous cases and decide whether to process a refund, schedule a replacement, or escalate the case to a human agent.
Along the way, it uses automation tools to complete smaller tasks, like checking the customer’s purchase history or confirming warranty details, ensuring the larger goal of resolving the complaint is achieved quickly and efficiently, all while staying within company policies and adapting to the context.
Traditional AI, by contrast, uses automation in a more straightforward way. For instance, a rule-based chatbot might walk customers through troubleshooting steps or pass the issue to a human agent if it can’t find a match in its database. While this type of automation is useful for routine tasks, it relies on fixed decision trees and lacks the flexibility to handle unexpected or complex scenarios.
The difference lies in how agentic AI integrates automation with decision-making. It not only executes automated tasks but also coordinates them intelligently, adapting to new information and adjusting its actions as needed.
Use case 2: New employee onboarding
This can be a time-consuming process, but agentic AI streamlines it by combining automation with intelligence. For example, it can autonomously create a personalised onboarding plan for each new hire based on their role, department and skill level. It can schedule training sessions, assign relevant resources and monitor progress. If a new employee struggles with a task or falls behind, the AI proactively adjusts the plan, offers additional resources, or notifies their manager to step in. Throughout the process, it automates smaller tasks like sending welcome emails, setting up IT accounts and ensuring compliance with necessary paperwork.
Traditional AI, on the other hand, focuses on automating repetitive parts of the onboarding process. It might send out pre-written welcome emails, generate a checklist of tasks, or assign general training modules to all new employees. While it’s certainly a great time saver, it does require more human input, relying on managers or HR teams to tailor the experience, track progress or resolve any issues that arise.
What to consider when implementing Agentic AI
While this next wave of intelligent automation offers immense potential, there are a few things to consider.
Ensure it’s an enabler, not a competitor
To make sure your agentic AI project is ethical and doesn’t make your employees feel anxious or overwhelmed, focus on making each AI agent a team player rather than a replacement.
Keep things transparent. Let employees know how and why the AI is being used, and give them opportunities to learn and grow alongside it.
Regular check-ins to spot any hiccups or biases are key, and always keep human oversight in the loop. Think of AI as an assistant that makes everyone’s life easier, not a competitor!
Do you have the expertise you need to maximise the potential of Agentic AI?
Implementing AI agents effectively will require expert guidance, as setting up an agentic AI system is more complex than traditional AI solutions and involves a lot of build effort. It involves designing systems that can operate independently while maintaining the necessary checks and balances to prevent errors, compliance breaches or audit risks.
For example:
- Policies need to be clearly defined to ensure the AI operates within legal and organisational boundaries.
- Monitoring and reporting tools must be in place to track decision-making processes and outcomes.
- Regular reviews help to refine the system and address any gaps as laws, policies and business goals evolve.
- Technology hype also means you need to be aware of what can be achieved safely today against what the marketing machines say.
At jaam, we have agentic AI specialists on our team, along with decades of process automation experience. We’re well placed to help you explore, plan and implement an agentic AI solution that is effective, safe, compliant, ethical and aligned with your organisation’s values.
We’re right on the cusp of seeing some truly amazing developments in agentic AI. 2025 is shaping up to be a pivotal year, as more businesses explore how this exciting technology can redefine processes and create new opportunities for innovation.
If you’d like to discuss how agentic AI could work for your organisation, jaam’s experts are here to chat about the possibilities. Get in touch here.