Edward Kiledjian

Understanding the next phase of intelligent systems in business

As artificial intelligence evolves, a new generation of autonomous systems is reshaping how work gets done. These so-called agentic AI systems mark a shift from passive automation to goal-driven autonomy—and they are moving swiftly from theory to enterprise deployment.

For business professionals and future leaders, understanding this transition is foundational.

What is agentic AI?

Agentic AI refers to intelligent systems that can plan, act and adapt with minimal human oversight. These agents do more than respond to prompts. They interpret high-level objectives, break them down into actionable steps, interact with tools and data, and iteratively refine their execution.

While generative AI creates content in response to instructions, agentic AI manages entire workflows—handling decision-making, operations and adjustments without manual intervention (Wikipedia, Medium).

What makes agentic AI distinct?

Agentic systems combine LLMs with reinforcement learning and real-time feedback to deliver four essential capabilities:

• Autonomy – Managing multi-step tasks independently
• Goal orientation – Pursuing outcomes, not just outputs
• Tool integration – Operating across platforms to execute end-to-end workflows
• Continuous learning – Adapting strategies through iterative feedback

This enables agentic AI to act as a digital collaborator (Reuters).

Who is leading the shift?

Global tech leaders and sector innovators are driving development:

• OpenAI, Microsoft, IBM, NVIDIA and UiPath are embedding agentic models into enterprise tools.
• Salesforce (Agentforce) and Google Cloud are advancing multi-agent collaboration.

This cross-sector momentum reflects growing demands for agility, scale and intelligent decision support.

When will it scale?

Agentic AI is now entering production:

• Gartner projects that more than 40 per cent of agentic AI projects will be cancelled by end-2027 due to cost pressures and unclear business value (Reuters, maxitech.com, PR Newswire, hrdive.com).
• Gartner also found 33 per cent of enterprise software apps will include agentic AI by 2028, up from less than 1 per cent in 2024 (Atera).
• Deloitte forecasts that 25 per cent of organisations using generative AI will launch agentic pilot projects in 2025, rising to 50 per cent by 2027 (Axios).
• Salesforce CEO Marc Benioff predicts over one billion AI agents will be in active use globally by the end of fiscal 2026 (maxitech.com).
• Market size is expected to grow from about US$5.1 billion in 2024 to around US$47 billion by 2030 (LinkedIn).

However, analysts caution that scaling agentic AI effectively will require strong governance, cost controls and clear ROI frameworks.

What will it actually do?

Agentic AI will underpin a wide range of business use cases:

• Customer operations – Agents may resolve issues, book services, update records and handle escalations end to end.
• Supply chain – Systems could monitor inventories, predict disruptions and coordinate logistics in real time.
• Finance and compliance – Agents may detect fraud patterns, validate transactions and create audit artefacts automatically.
• Cybersecurity – Multi-agent systems could proactively detect, triage and mitigate threats—suggested recently by RSA and Deloitte as essential to agent risk frameworks (RCR Wireless News, Wikipedia).
• Business strategy – By analysing performance data, agents may support planning cycles or assist with scenario modelling.

These systems are designed to augment—not replace—human expertise, enabling professionals to focus on higher-order judgement and insight.

Why it matters

Agentic AI is not just a technology evolution—it’s a structural shift in enterprise design. As agents become more capable, the professional role transitions: from direct execution to orchestration, from oversight to strategic enablement.

Future leaders must become fluent at defining outcomes, assigning constraints and governing autonomous systems. In this transformation, success lies not in doing more—it lies in guiding better.