Imagine a scenario where you need to contact a call centre regarding a complex billing issue, writes Chris Wiggett, head: data and analytics at NTT Data in Middle East and Africa.
But first, an AI agent immediately analyses your query, finds relevant information in the company’s database and suggests potential solutions to the human agent. Now, the human agent can respond to you more efficiently and accurately. You spend less time on the call and enjoy the overall customer experience.
The AI agent can also automate routine tasks such as sending you a follow-up email to check whether you’re satisfied with the resolution of your issue, freeing the human agents to focus on more complex issues.
It’s a win-win scenario for the customer and the call centre alike, but how did we get here?
The advent of generative AI (GenAI) has been a milestone in the evolution of AI-driven technologies. Unlike narrow AI, which is tailored to specific tasks, it can perform an array of intellectual tasks similar to those a human can undertake – like analysing data, writing and illustrating. Within this broad spectrum, agentic modelling has emerged as a specialised area focused on developing autonomous agents that can act on behalf of humans.
It involves creating systems that process data and perform predefined operations, with some level of autonomy in decision-making. These systems learn from interactions with their environment, adapt to new situations and make choices that align with their programmed goals or objectives.
GenAI as a corporate priority
Organisations across industries are now incorporating GenAI into their strategic planning. A common business goal is to use these tools to simplify complex processes and enhance digital capabilities to improve the customer experience (CX) – and boost customer retention.
More than 90% of organisations agree that improvements in CX and employee experience will directly affect their net profit, according to NTT Data’s 2023 Global Customer Experience Report.
At the same time, 64% of organisations believe that AI will boost their overall productivity, a Forbes Advisor survey found. This illustrates rising confidence in AI’s potential to transform business operations.
The GenAI market is responding to the need for platforms that meet these requirements by developing models tailored to industry-specific requirements.
This is contributing to exponential growth in the market. According to an IDC forecast, spending on GenAI – including software, hardware, and IT and business services – is expected to reach $151,1-billion in 2027, with a compound annual growth rate of 86,1% between 2023 and 2027.
Agentic modelling and artificial general intelligence
In this context, the interactive agent foundation model is a framework for AI systems that can interact effectively with humans or other virtual agents in a dynamic environment. These models provide a base for more complex functions that let AI agents understand and respond to inputs, make decisions and take contextually appropriate actions.
In our customer-service example, agentic models gather data from multiple sources and provide real-time assistance to both human agents and customers during customer interactions, thereby helping the call-centre operators make more informed decisions and improving the quality of service.
Process-aware agentic models in business operations more generally can employ GenAI capabilities to improve the employee experience, facilitate task completion and streamline workflows.
Applying agentic modelling
The interactive agent foundation model represents a move towards artificial general intelligence, a sophisticated form of AI capable of reasoning, planning, problem-solving, abstract thinking, understanding complex concepts and rapid learning from experiences.
This model’s flexibility and broad applicability show potential for use in various fields including robotics, gaming and healthcare. As these agents learn to understand text-based commands and operate within simulated settings, the model facilitates the creation of smart robots and virtual assistants that can interpret and execute intricate instructions across industries.
As part of Microsoft’s AI for Good initiative, agentic models are being used to autonomously analyse data, predict outcomes and make informed decisions to advance goals in sustainability, health, humanitarian aid and social justice.
However, these developments also raise questions about the ethics and implications of AI systems making decisions that can affect humans and their environment.
These concerns underscore the importance of working with expert service providers to implement smart, AI-driven solutions safely and securely.
The start of a new cycle of innovation
Advancements in GenAI and agentic modelling are set to revolutionise the technological landscape, offering unprecedented levels of autonomy and adaptability.
These technologies are not only enhancing organisations’ current capabilities. They’re also paving the way for innovations that will redefine AI’s potential to drive progress and create value – if it’s used responsibly and ethically, with a deep understanding of the risks involved and how to manage them.