Cognigy: What is Agentic AI & Why Will it Change the World?
"Everyone is talking about agentic AI," says Niall Carter, Assistant Vice President UK&I at Cognigy, and it's hard to argue with him. If 2024 was the year of Gen AI, then 2025 has been all about agentic.
According to Gartner, 33% of all software used by enterprises will include some form of agentic AI by 2028.
What's more, analysts at IDC recently reported that 70% of companies across the APAC region expect agentic AI to completely disrupt business models by the end of 2027.
All this expansion is likely to result in some quite staggering financial growth. Financial experts believe that the global agentic AI market will be worth US$196.6bn in less than a decade.
But what exactly is agentic AI? What distinguishes it from other kinds of AI technology? And why do experts believe it will quite so revolutionary?
Niall spoke with AI Magazine to answer all these questions and more.
The next generation of assistance
For the past few years, Gen AI has been in the limelight. Since the launch of ChatGPT in late 2022, businesses and casual users alike have been enthralled by Gen AI. But despite its seemingly boundless potential, Niall believes that it has some definite limitations as a technology.
“Gen AI is fundamentally a passive technology,” he says.
“It requires prompting. It will create the most human-like exchange or breath-taking art, analyse your data or write your code, but only in response to an instruction.
“There’s logic and comprehension under the hood. But the actual execution is a reactive transaction, even with recent iterative and multi-modal capabilities.
“This means that autonomy is what sets agentic AI apart,” he says, “as agentic AI describes the use of AI-powered agents and digital assistants that can observe, reason, plan and act without human prompting."
“Rather than responding to specific instructions, they are goal-oriented.
“This means they pursue a goal proactively until it is achieved, breaking it down into logical steps, just like humans do.
“They can do so because they are integrated with back-end systems, tools and knowledge and given executional permissions, such as triggering workflows, retrieving and inputting information, or sending messages.
“This all adds up to an agent that can actively fulfil a role, not just singular functions.”
A giant leap forward
Niall believes that one of the biggest benefits of agentic AI is the fact that it can be 'deterministic', meaning that it's easy to predict what a system will do with a certain prompt. This sort of reliability lets businesses deploy agentic AI to speed up their workflows, improving efficiency while retaining accuracy.
“If something is deterministic – AI or otherwise – it gives you consistent outputs or results because it follows pre-determined rules and logic,” he says.
“It’s largely what programming pre-AI has been. It’s reliable.”
Yet, for Niall, there is a “defined, or rather a determined, path of instruction," when it comes to AI.
"It’s what makes deterministic AI more explainable and transparent, which is useful for precise or science-based use cases,” he says.
“But most real-world tasks aren’t this linear, this neat."
“Most tasks are more conceptual and goal-oriented.”
Niall is a proponent of the idea that digital assistants should have the ability to reason, solve problems, think ahead, multi-task and work in groups if they are to have real value.
“Most importantly, they need to be self-starting, autonomous and proactive,” he says.
“This is the difference between deterministic systems and agentic AI.
“AI agents may even use deterministic tools to achieve their goal, but the difference is that agentic AI can decide when, how and why to use them — operating autonomously, adapting to changing circumstances, pursuing and reviewing outcomes without needing to be prompted at every step.”
Agentic in action
Niall's company, Cognigy, provides businesses with conversational AI models, particularly in the context of customer service. Indeed, customer support teams have been some of the earliest adopters of agentic AI systems.
“By upgrading old chat-bots that only respond to FAQs and rely on keywords, AI agents use Gen AI and combine it with the ability to follow structured processes to provide human-like, goal-oriented interactions,” he says.
AI agents in customer service can:
- Provide service updates or issue refunds
- Book flights or insurance
- Chase up invoices
- Account for customer preferences, external variables and company policies
“They also have persistent short or long-term memory (another distinguishing feature from traditional Gen AI),” Niall explains, “enabling them to continue conversations and tasks over multiple sessions and across channels.
“These characteristics make agentic AI an incredibly versatile and effective tool – one that really blossoms at scale. Its actions translate to measurable, value-based metrics and demonstrably relieve human teams of repetitive, high-volume tasks.”
Experts see the rise of AI in customer service as far more than a passing craze. Gartner believes that agentic AI is here to stay, forecasting that it will be resolving 80% of customer problems by 2029, all without human intervention.
One of Cognigy's most high profile clients is Bosch, the German utilities and technology company. So far, Bosch has introduced 90 agents to its business, with the AI helping to solve customer queries and HR issues.
“Agentic systems embody a new kind of human-AI collaboration,” Niall concludes.
“They’re making companies more resilient, agile and productive – enabling staff to focus on more satisfying, value-driving activities – and providing customers with satisfying and responsive experiences with no wait times.
“Agentic AI is a big deal.”
