In an era where technology is advancing rapidly, agentic artificial intelligence (AI) is emerging as the next leap in the AI revolution. By 2028, this transformative technology will facilitate 15% of daily autonomous decisions, revolutionizing global decision-making processes, according to Gartner.
Agentic AI integrates sophisticated decision-making capabilities with modern technology. Unlike traditional AI systems, agentic AI goes beyond pre-programmed responses and content-generating strategies. The system works independently by interpreting context, evaluating options, and executing actions to accomplish the assigned tasks with minimal human supervision.
As AI continues to evolve, this new approach holds an enormous potential to enhance productivity, ultimately establishing a virtual workforce that will revolutionize various industries.
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Navigating AI’s Third Wave of Advancement
Poised to become integral to the modern workplace, agentic AI functions as a sophisticated virtual worker capable of decision-making and action.
These AI agents can seamlessly retrieve and analyze information, optimize workflows, and assist with daily tasks. According to PwC, agentic AI displays goal-oriented behavior and can interact with its surroundings to adapt to new information and strategies.
Highly effective in customer service and supply chain management, AI agents are set to transform various industries as well, including healthcare, logistics, and telecommunications. By deploying AI models, Siemens AG reduced maintenance costs by 20% and increased production uptime by 15%, according to PwC. Moreover, Amazon’s recommendation algorithm catalyzed a 35% increase in sales through personalized recommendations and improved loyalty ratings by 20%. Similarly, telecommunications company, AT&T, reduced operational expenses by 15%.
Human resources can also utilize agentic AI to automate and support the recruitment process. Agentic AI is capable of screening resumes, scheduling interviews, and tracking employee performance.
Deloitte predicts that 25% of companies that currently employ generative AI (GenAI) capabilities will launch agentic AI pilots or proofs of concept (PoCs) in 2025; this number will grow to 50% in 2027. In tandem with this projection, Capgemini foresees that 82% of organizations plan to integrate AI agents into their operations within one to three years.
Furthermore, agentic AI’s integration with the Internet of Things (IoT) will enable seamless communication between devices and accelerate the progress of smart environments.
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“Poised to become integral to the modern workplace, agentic AI functions as a sophisticated virtual worker capable of decision-making and action.”
Challenges in Agentic AI
While agentic AI holds immense potential, its deployment comes with complex challenges. Firstly, agentic AI’s autonomous decision-making capabilities blur the lines between autonomous trust and human intervention as, like any other AI system, agentic AI can produce errors.
Implementing a robust scaffolding—encompassing foundational models such as machine learning (ML), natural language processing (NLP), multimodality, synthetic data sets, Retrieval Augmented Generated (RAG)-based capabilities—and exposing the agent to real-world scenarios is crucial for improving decision-making. Deployers must reassess if these AI agents can be trusted to make important decisions.
Moreover, it can be challenging to control agentic AI due to its autonomous nature, heightening the risk of errors and unintended actions. These systems may also be vulnerable to security threats and data breaches, potentially compromising data integrity and generating inaccurate information.
The emergence of agentic AI has fueled concerns surrounding job displacement. Its autonomy and decision-making capabilities require little-to-no human involvement, rendering current job roles in this niche obsolete. Companies must upskill their employees and establish new roles to support the balance, ultimately keeping pace with the technological trend.
As AI can make decisions autonomously, it is paramount to ensure agentic AI operates in compliance with legal and ethical standards. According to Gartner, the rise of AI agents will drive the creation of both new technologies and AI governance initiatives to prevent disinformation and misuse.
Addressing these challenges requires a collaborative effort between deployers, governments, and private stakeholders to ensure the responsible and controlled deployment of agentic AI systems.
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“As AI can make decisions autonomously, it is paramount to ensure agentic AI operates in compliance with legal and ethical standards.”
Advancements in Agentic AI
Despite its early developments, agentic AI has seen remarkable progress, with major technology players laying the groundwork for its widespread deployment.
In 2024, cloud-based software company, Salesforce, introduced two autonomous AI sales agents to accelerate sales growth: Einstein SDR (sales development representative) and Einstein Sales Coach. The Einstein SDR agent can autonomously make decisions and actions that align with its desired outcome while the Einstein Sales Coach agent supports sellers by providing personalized feedback through role-play sessions. Additionally, Salesforce launched its Agentforce 2.0 in December, 2024, utilizing autonomous AI agents to improve workflow. This advanced reasoning engine is set to redefine productivity and customer experience by enabling a limitless digital-labor-driven workforce.
Emerging as a frontrunner in agentic AI deployment, this year, NVIDIA unveiled its agentic AI blueprint (NVIDIA AI Blueprint), enabling developers to deploy custom AI agents that reason, plan, and act on analyzed data. NVIDIA also released its Llama Nemotron family of agentic AI models, which ensure the highest accuracy across a wide range of agentic tasks and exceptional compute efficiency and boast an open license for enterprise use.
Recently, ADNOC and AIQ launched the world’s first agentic AI solution dedicated to the energy sector. The PoC trial of ENERGYai incorporated a 70 billion LLM parameter with ADNOC’s petabytes of proprietary data, enhancing ADNOC’s sustainability efforts.
OpenAI has begun leveraging AI agent capabilities by introducing ChatGPT’s ‘Tasks’—a feature that schedules reminders and recurring actions. This feature sets the stage for a future in which agentic AI assists users with daily tasks.
Other technology companies are also making strides in agentic AI. Enterprise AI company, Ema, launched its Persona builder platform, which facilitates complex workflows. “With over 200 pre-built connectors, Ema’s Personas seamlessly integrate with internal data sources, create knowledge graphs, learn from human feedback, and operate tools to perform effectively in various enterprise roles. This innovation eliminates the need for extensive model training or manual fine-tuning once a Persona is built,” explained Ema CEO, Surojit Chatterjee.
Google also recently launched Agentspace. This service aids enterprise customers in creating and deploying AI agents that answer complex questions, generate suggestions, and execute actions.
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“The rapid development of autonomous systems offers unprecedented opportunities to deliver enhanced decision-making processes, business operations, and solutions to complex challenges.”
Final Thoughts
As we stand on the cusp of AI’s transformation, agentic AI is evidently redefining human-machine communication. The rapid development of autonomous systems offers unprecedented opportunities to deliver enhanced decision-making processes, business operations, and solutions to complex challenges.
The goal not only encompasses doing more with less; it also includes redefining possibilities through autonomous systems.
As agentic systems continue to advance, responsible, collaborative innovation will be required to avoid bias and unintended consequences. This new leap in AI represents the manifestation of the long-awaited vision for an intelligent world.
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