Across the Middle East, governments and businesses are rapidly advancing digital strategies, embracing AI not just as a tool for automation but as a catalyst for public sector modernization and workforce transformation. In this environment, agentic AI is gaining traction across industries, from energy and finance to healthcare and government sectors.

These AI agents promise radical efficiency gains, from automating workflows to surfacing intelligent insights in real time. However, as organizations race to deploy them across departments, a crucial challenge remains: the people. Experts say HR is one of the safest and most strategic domains for introducing agentic AI.

Why HR is a Strategic Starting Point 

“HR processes are typically highly structured, well-documented, and governed by internal policies as well as external regulations,” says Antonio Rizzi, Area VP – Solution Consulting, South EMEA at ServiceNow.“This makes them particularly suitable for agentic AI, which relies on accessing and interpreting existing documentation, procedures, and knowledge bases to determine the steps needed to automate and resolve tasks.”

More importantly, HR is also universal. “HR platforms serve the entire employee population,” Rizzi explains. “So, introducing AI agents in this domain ensures broad visibility and impact. It’s one of the few areas where AI can touch every employee’s experience — from onboarding to benefits to training.”

One standout use case is when AI agents support employees during key life moments. “One customer built an agent that initiates HR system updates based on a photo of a birth certificate,” says Rizzi. “It then suggests next steps, like proactively applying for tax benefits or exploring parental leave. It’s a shift from reactive HR to a proactive, human-centric experience.”

AI as a Support, Not a Substitute 

While AI agents can be powerful, human oversight must remain central, especially in sensitive areas like HR, compliance, and decision-making under uncertainty, says Sumeet Agrawal, VP of Product Management for Agentic AI at Informatica.

“AI agents are most effective when they handle large-scale data processing, automate routine tasks, and surface insights to support human decision-making, not replace it,” says Agrawal. “Human judgment remains essential for ethical oversight, context-sensitive decisions, and accountability.”

Agrawal cautions against weak governance, noting, “History shows that poor oversight of technology can have lasting consequences. To build trust, AI must be governed responsibly with high-quality data, transparency, and safeguards against bias and misuse.”

The IT Imperative in an Agentic Workplace 

While HR defines the employee experience, IT defines the foundation on which AI agents operate. Sid Bhatia, Area VP & GM – Middle East, Turkey & Africa at Dataiku, says IT leaders must be the backbone of agentic AI success.

“Their role encompasses designing scalable infrastructure to support autonomous agents, enforcing ethical and regulatory guardrails, and ensuring seamless integration with legacy systems,” says Bhatia. “They also must prioritize security and foster organizational trust through change management.”

For scalable and explainable agentic AI, Bhatia outlines four core technical components: orchestration layers to manage workflows, modular design for flexibility, high-fidelity data pipelines, and built-in explainability tools.

Agrawal concurs, adding that thoughtful product design is key to user trust. “To address the ‘black box’ problem in AI, organizations should pair strong governance with clear UX patterns,” he says. “‘Why this result?’ prompts, decision-path visualizations, and traceable outputs help users understand how AI arrived at a conclusion. Embedding these features supports both confidence and compliance.”

Not Losing the Human Touch 

One of the primary challenges in deploying agentic AI is striking the right balance between autonomy and oversight. Bhatia recommends a tiered autonomy model.

“Low-risk decisions — like routine data processing — can be fully automated,” he explains. “High-impact actions, like financial approvals, should trigger human review. And asynchronous oversight, where humans audit decisions after execution, helps maintain speed without sacrificing accountability.”

Agrawal notes that designing agents that scale efficiently and still feel personal is possible. “It requires a strong foundation of well-governed data and flexible technology platforms,” he says. “Efficient scaling depends on optimized algorithms and architecture. Meaningful personalization relies on adaptive insights and learning from user interactions.”

How to Measure Trust and Value in Agentic AI 

Deploying agentic AI is only half the challenge. Measuring its impact — and trustworthiness — is equally critical.

Bhatia advises combining operational KPIs (task completion rate, latency, and error rates) with trust-focused metrics, such as audit trail completeness, explainability scores, and user adoption. “Together, these metrics provide a holistic view of agent efficacy, reliability, and alignment with enterprise goals,” he says.

Agrawal adds that transparency and traceability must be baked into AI workflows. “Immutable logging of agent decisions, inputs, and reasoning paths for post-hoc audits is a must. Continuous monitoring for drift or anomalies ensures agents stay aligned with ethical and operational standards.”

A Collaborative Future 

Agentic AI has the power to transform enterprise productivity and decision-making. However, it can also alter workplace relationships and organizational culture. Getting it right means rethinking how employees interact with systems and each other.

As Rizzi puts it, agentic AI should be designed to “amplify human potential.” He adds: “Automation should help people do their best work, evolve their careers, and feel more connected to their organization.”

Agrawal agrees that AI agents are collaborators, not replacements, stating, “Strong collaboration between humans and AI, guided by clear best practices, is critical for sustainable success.”

In the Middle East’s ever-evolving enterprise landscape, those who balance technical excellence with human empathy and who align IT, HR, and business strategy will unlock AI’s potential and define the future of human-centered work.

What if your productive new digital employee was also your greatest vulnerability? AI agents — powered by large language models (LLMs) — are no longer futuristic concepts. Agentic AI tools are working alongside humans, automating workflows, making decisions, and helping teams achieve strategic outcomes across businesses. But AI agents also introduce new risks that, if left unmanaged, could compromise your company’s resilience, data integrity, and regulatory compliance.

Unlike older AI applications that operate within narrowly defined boundaries, like chatbots, search assistants, or recommendation engines, AI agents are designed for autonomy.

Among companies achieving enterprise-level value from AI, those posting strong financial performance and operational efficiency are 4.5 times more likely to have invested in agentic architectures, according to Accenture’s quarterly Pulse of Change surveys fielded from October to December 2024. (This research included 3,450 C-suite leaders and 3,000 non-C-suite employees from organizations with revenues greater than $500 million, in 22 industries and 20 countries.) These businesses are no longer experimenting with AI agents; they are scaling the work. But with greater autonomy comes a heightened need for trust — and trust cannot be assumed.

AI agents operate in dynamic, interconnected technology environments. They engage with application programming interfaces (APIs), access a company’s core data systems, and traverse cloud and legacy infrastructure and third-party platforms. An AI agent’s ability to act independently is an asset only if companies are confident that those actions will be secure, compliant, and aligned with business intent.

Yet, most companies are not ready for AI security risks. Only 42% of executives surveyed said they are balancing AI development with appropriate security investments. Just 37% have processes in place to assess the security of AI tools before deployment.

How can leaders bridge this preparedness gap? The experience of a leading Brazilian health care company illustrates three best practices for agentic AI security.

Dubai, United Arab Emirates– [June 11, 2025] – MIT Sloan Management Review (MIT SMR) Middle East, one of the world’s most respected sources of research-driven insights at the intersection of technology and management, announced the launch of the AI Research Forum, a new initiative including a flagship summit focused on Agentic AI.

The AI Research Forum will convene academic leaders, AI researchers, industry pioneers, and policy makers to explore breakthroughs in AI.

Shifting the Focus to Agentic AI

While most AI systems today are task-specific and reactive, Agentic AI represents a new paradigm in machine intelligence, defined by self-directed learning, autonomous action, and long-term planning. From autonomous vehicles and personal assistants to supply chain optimizers and digital co-workers, agentic AI is poised to reshape entire industries.

“Agentic AI is becoming the foundation for the next generation of enterprise systems and societal tools,” said Ravi Raman, Publisher, MIT SMR Middle East. “The AI Research Forum will be an authoritative, interdisciplinary platform for shaping how this powerful technology is designed, governed, and applied responsibly.”

About the AI Research Forum & Summit

The AI Research Forum will feature a year-long series of research collaborations, thought leadership content, and cross-industry roundtables. The summit, to be held in Dubai, will host keynotes, panels, and workshops led by experts

Focus areas will include:

Agentic Architectures – From goal modeling to memory and reasoning
AI + Human Collaboration – Designing co-agents, not just tools
Ethics, Governance & Alignment – Ensuring accountability in an autonomous system

Sectoral Impact – Applications across healthcare, finance, logistics, and education

A Global Knowledge Platform

The AI Research Forum will extend beyond the summit, publishing a series of white papers, executive briefings, and case studies in MIT Sloan Management Review Middle East, which now reaches over 180,000 readers across business, government, and academia.

As AI continues to reshape industries worldwide, Deloitte has unveiled its Global Agentic Network, a strategic initiative designed to scale AI-driven digital workforce solutions. With the Middle East rapidly advancing its digital transformation agenda, the region is a key focus for this launch.

The initiative supports organizations in deploying AI-powered agents that boost operational efficiency, drive growth, and reimagine work. As AI adoption accelerates across sectors in the GCC and beyond, Deloitte’s agentic AI solutions aim to integrate intelligent automation with human expertise.

Agentic AI refers to software agents capable of autonomously executing tasks, managing workflows, and adapting based on input from users or other systems. Powered by large language models and machine learning, these agents continuously evolve, making them ideal for complex business environments.

The Global Agentic Network spans Deloitte’s operations across EMEA, Asia Pacific, and North America, enabling enterprises to access cutting-edge AI capabilities. In the Middle East, the initiative aligns with national strategies focused on AI innovation, economic diversification, and future-ready infrastructure.

Deloitte is already working with regional clients in key sectors—such as energy, government, and financial services—to deploy agentic AI that streamlines decision-making, improves productivity, and delivers scalable value.

“The Middle East is on a rapid trajectory toward AI-led transformation, and agentic AI is a game-changer for how businesses operate,” said Yousef Barkawie, Deloitte Middle East Gen AI Leader. “At Deloitte, we’re helping our clients navigate the world of AI transformation by architecting and building the capabilities and trust needed for them to scale out their AI deployments and transform at the core. This is an exciting moment to help shape what the future of work looks like in our region, especially as governments and industries double down on innovation and future-readiness.”

The Global Agentic Network includes collaborations with leading technology providers and features tools like Zora AI™, Deloitte’s proprietary suite of AI agents capable of autonomously performing complex business functions. These agents are already being used internally as part of Deloitte’s goal to become an AI-fueled organization by 2030.

This initiative also supports Deloitte’s broader commitment to workforce upskilling and embedding AI into core service offerings—enabling faster, more adaptive, and insight-driven client solutions.

In the Middle East, Deloitte is actively expanding local AI capabilities and supporting clients in the responsible integration of agentic AI. By bridging the gap between traditional automation and intelligent enterprise solutions, the firm is helping organizations unlock new levels of performance and prepare for the future of work.

As AI systems gain autonomy and begin to operate with less direct human oversight, a new category of AI tools is emerging to manage the risks: guardian agents. These technologies are designed to monitor, guide, and, when necessary, intervene in the behavior of other AI agents—particularly in enterprise settings where the stakes are high. 

According to Gartner Inc., guardian agents will represent 10 to 15% of the agentic AI market by 2030, signaling their growing importance in AI governance and cybersecurity strategies.

Guardian agents operate both as AI assistants that support tasks such as content review and monitoring, and as autonomous or semi-autonomous systems capable of executing or blocking actions based on predefined goals.

A recent Gartner webinar poll revealed that adoption of AI agents is already underway. Among 147 CIOs and IT leaders surveyed, 24% reported deploying a few AI agents (fewer than a dozen), and 4% said they had deployed more than a dozen. Meanwhile, 50% are in the research or experimental phase, and another 17% plan to implement the technology by the end of 2026.

“Agentic AI will lead to unwanted outcomes if it is not controlled with the right guardrails,” said Avivah Litan, VP Distinguished Analyst at Gartner. “Guardian agents leverage a broad spectrum of agentic AI capabilities and AI-based, deterministic evaluations to oversee and manage the full range of agent capabilities, balancing runtime decision making with risk management.”

As enterprise use of agentic AI grows, so does the associated risk. 52% of 125 respondents from the same poll indicated their AI agents focus on internal administrative functions such as IT, HR, and accounting. Meanwhile, 23% reported external, customer-facing applications.

Gartner highlights several major threats to agentic AI systems, including data poisoning, credential hijacking, and agents interacting with malicious or deceptive online sources. These vulnerabilities can lead to unauthorized access, operational disruptions, and reputational harm.

“The rapid acceleration and increasing agency of AI agents necessitates a shift beyond traditional human oversight,” Litan said. “As enterprises move towards complex multi-agent systems that communicate at breakneck speed, humans cannot keep up with the potential for errors and malicious activities. This escalating threat landscape underscores the urgent need for guardian agents, which provide automated oversight, control, and security for AI applications and agents.”

To address these concerns, Gartner recommends CIOs and security leaders prioritize three core functions of guardian agents:

• Reviewers: Evaluate AI-generated content for accuracy and compliance.
• Monitors: Track AI behavior for follow-up by humans or other AI systems.
• Protectors: Intervene in real time to adjust or block risky or unauthorized actions.
  
  

Regardless of how they are deployed, Gartner notes that guardian agents are essential for maintaining the integrity of increasingly complex AI ecosystems. The firm predicts that by 2028, 70% of AI applications will incorporate multi-agent systems—making automated governance tools not just useful, but critical.