Gartner: How Agentic AI is Shaping Business Decision-Making

The emergence of agentic AI represents a significant departure from conventional AI implementations that have dominated enterprise software over the past decade.

While previous generations of AI systems primarily focused on pattern recognition and predictive analytics, agentic AI introduces a new paradigm where AI systems can independently initiate actions, make decisions and execute complex workflows with minimal human intervention.

This shift marks a crucial evolution in how businesses leverage AI, moving from tools that simply support human decision-making to systems that can actively participate in organisational processes.

Gartner's analysis in its report "Top Strategic Technology Trends for 2025," identifies agentic AI as one of the most transformative forces set to reshape enterprise technology landscapes over the next 24 months.

The timing of this report is particularly significant as organisations seek to understand how to harness the potential of more autonomous AI systems to stay competitive whilst managing associated risks and governance challenges.

The report's findings are especially relevant for CTOs and technology leaders given the rapid advancement of LLMs and autonomous systems over the past 18 months, which have created new possibilities for AI agencies in enterprise environments.

Gartner's comprehensive analysis explores how agentic AI is poised to revolutionise enterprise software applications, examining both the transformative potential and inherent challenges that organizations must navigate as they adopt these advanced technologies.

Understanding agentic AI and its implications

According to Gartner, agentic AI is characterised by its ability to act on behalf of an organisation, making decisions based on data analysis and predefined goals.

Unlike traditional AI systems that require explicit instructions from users, agentic AI operates independently, enabling it to quickly analyse complex datasets, identify patterns and take action.

This capability is expected to significantly enhance decision-making processes across industries.

The company highlights some of the opportunities agentic AI brings to businesses:

• Agentic AI enhances decision-making by autonomously selecting actions for desired outcomes, improving performance over time.
• It quickly analyses complex data, reducing manual modelling and enabling scalable solutions.
• This technology upskills teams to manage projects through natural language, though it requires robust governance and orchestration tools.
• Effective implementation necessitates clear guidelines on autonomy, security, and data privacy.

The study predicts that by 2028, 33% of enterprise software applications will incorporate agentic AI, a substantial increase from less than 1% in 2024.

This shift will allow organisations to automate various tasks and workflows, thereby improving overall efficiency.

For instance, an agentic AI system could autonomously adjust marketing strategies based on real-time performance metrics.

Furthermore, these systems can facilitate enhanced collaboration among teams by providing insights derived from data that may not be readily apparent to human workers.

However, the integration of agentic AI also presents governance challenges.

As organisations increasingly rely on these autonomous systems, they must establish clear guidelines regarding their use.

This includes defining the levels of agency permitted within different workflows and ensuring robust security measures are implemented to protect sensitive data.

Gartner emphasises: “Agentic AI will introduce a goal-driven digital workforce that

autonomously makes plans and takes actions — an extension of the workforce that doesn’t need vacations or other benefits.”

Challenges agentic AI poses

While agentic AI presents numerous opportunities, it also introduces significant challenges that organisations must address.

Robotic process automation
A primary concern is the risk of repeating past mistakes seen with robotic process automation, where numerous bots were created without clear documentation or understanding of their functions.

This lack of clarity can lead to inefficiencies and operational confusion.

Low-code agentic AI solutions
Furthermore, employees may develop their own low-code agentic AI solutions within the IT environment, potentially bypassing established security and quality standards.

This decentralised approach can create vulnerabilities in data integrity and security.

Reliance on organisational data
​​​​​​​Agentic AI's reliance on organisational data for decision-making raises additional risks, particularly if the data quality is poor.

Gartner emphasises: “Agentic AI will introduce a goal-driven digital workforce that

autonomously makes plans and takes actions — an extension of the workforce that doesn’t need vacations or other benefits.”

Challenges agentic AI poses

While agentic AI presents numerous opportunities, it also introduces significant challenges that organisations must address.

Robotic process automation
A primary concern is the risk of repeating past mistakes seen with robotic process automation, where numerous bots were created without clear documentation or understanding of their functions.

This lack of clarity can lead to inefficiencies and operational confusion.

Low-code agentic AI solutions
Furthermore, employees may develop their own low-code agentic AI solutions within the IT environment, potentially bypassing established security and quality standards.

This decentralised approach can create vulnerabilities in data integrity and security.

Reliance on organisational data
​​​​​​​Agentic AI's reliance on organisational data for decision-making raises additional risks, particularly if the data quality is poor.

Despite Gartner emphasising the importance of utilising agentic AI, it also highlights the importance of designing workflows that seamlessly incorporate both human intelligence and machine capabilities.

It is this hybrid approach that can enhance overall productivity while ensuring that critical decision-making processes remain informed by human judgement.

Moreover, as organisations begin to adopt agentic AI at scale, there will be a growing need for training programmes aimed at equipping employees with the skills necessary to work alongside these advanced technologies effectively.

By fostering a culture of continuous learning and adaptation, businesses can ensure that their workforce remains agile in an increasingly automated environment.

Gartner summarises: “Agentic AI will eliminate the need to interact with websites and applications. Why bother when your AI agent can do it for you?”

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